copy the ShardokEngine instead of using a shared_ptr across multiple threads

2026-07-29 06:35:41 +00:00 · 2025-08-22 16:11:02 -07:00
1230 changed files with 39698 additions and 76543 deletions
@@ -1,8 +1,5 @@
 bazel-1.0.0.bazelrc

-# for now: filter out annoying TASTY warnings
-common --ui_event_filters=-INFO
-
 common --enable_bzlmod

 # Don't use toolchains_llvm for the swift app build
@@ -19,9 +16,9 @@ common --worker_sandboxing
 common --local_test_jobs=64
 common --jobs=64

-common --cxxopt="--std=c++23"
+common --cxxopt="--std=c++20"
 common --cxxopt="-Wno-deprecated-non-prototype"
-common --host_cxxopt="--std=c++23"
+common --host_cxxopt="--std=c++20"

 common --javacopt="-Xlint:-options"

@@ -29,9 +26,6 @@ common --javacopt="-Xlint:-options"
 common --linkopt=-Wl
 common:macos --linkopt=-Wl,-no_warn_duplicate_libraries

-# Fix Xcode version caching issue - avoids need for `bazel clean --expunge` after Xcode updates
-common:macos --repo_env=DEVELOPER_DIR=/Applications/Xcode.app/Contents/Developer
-
 common --java_language_version=17
 common --java_runtime_version=remotejdk_17
 common --tool_java_language_version=17
@@ -1,3 +0,0 @@
-CompileFlags:
-  Add:
-    - "-std=c++23"
@@ -34,54 +34,10 @@ jobs:
      with:
        lfs: false
    - name: Run tests
-      id: test
-      continue-on-error: true
      run: bazel test --build_event_json_file=test.json //src/test/... //src/main/go/...
-    - name: Collect failed test logs
-      if: always()
-      run: |
-        # Remove any existing failed_test_logs directory and create fresh
-        rm -rf failed_test_logs
-        mkdir -p failed_test_logs
-        # Extract failed test targets from test.json and copy their logs
-        # The test.json is in JSONL format - one JSON object per line
-        # We look for lines with testResult that have a status other than PASSED
-        if [ -f test.json ]; then
-          grep '"testResult"' test.json | \
-            grep '"status"' | \
-            grep -v '"status":"PASSED"' | \
-            grep -o '"label":"[^"]*"' | \
-            cut -d'"' -f4 | \
-            sort -u | \
-            while read target; do
-              # Convert target like //src/test/cpp/...:test_name to path
-              log_path=$(echo "$target" | sed 's|^//||' | sed 's|:|/|')
-              if [ -f "bazel-testlogs/$log_path/test.log" ]; then
-                log_name=$(echo "$log_path" | tr '/' '_')
-                if cp "bazel-testlogs/$log_path/test.log" "failed_test_logs/${log_name}.log"; then
-                  echo "Collected log for failed test: $target"
-                else
-                  echo "Error: Failed to copy log for $target"
-                fi
-              fi
-            done
-        fi
-        # List what we collected
-        echo "Collected logs:"
-        ls -lh failed_test_logs/ 2>/dev/null || echo "No logs collected"
    - name: Archive test results
-      if: always()
+      if: success() || failure()
      uses: actions/upload-artifact@v4
      with:
        name: test.json
        path: test.json
-    - name: Archive failed test logs
-      if: always()
-      uses: actions/upload-artifact@v4
-      with:
-        name: failed-test-logs
-        path: failed_test_logs/
-        if-no-files-found: ignore
-    - name: Fail if tests failed
-      if: steps.test.outcome == 'failure'
-      run: exit 1
@@ -20,7 +20,7 @@ project/boot/
 project/plugins/project/
 project/target/
 bazel-bin
-bazel-eagle0*
+bazel-eagle0
 bazel-out
 bazel-testlogs
 .ijwb
@@ -32,9 +32,9 @@ buildWin.sh
 __pycache__/
 scripts/refresh_name_layers/vendor/
 scripts/refresh_name_layers/refresh_name_layers.zip
+.pre-commit-config.yaml
 .bazelbsp
 .bsp
 .metals
 api_keys.txt

-src/main/csharp/net/eagle0/clients/unity/eagle0/ProjectSettings/Packages/com.unity.dedicated-server/
@@ -1,44 +0,0 @@
-# See https://pre-commit.com for more information
-# See https://pre-commit.com/hooks.html for more hooks
-repos:
-   repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.3.0
-    hooks:
-    -   id: check-added-large-files
-    -   id: no-commit-to-branch
-        args: [--branch, main]
-   repo: https://github.com/pocc/pre-commit-hooks
-    rev: v1.3.5
-    hooks:
-    -   id: clang-format
-        args: [-i, --no-diff]
-        types_or: ["c++", "c#"]
-        exclude: ^src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins
-   repo: https://github.com/yoheimuta/protolint
-    rev: v0.42.2
-    hooks:
-    -   id: protolint
-        args: [-fix]
-        exclude: ^src/main/protobuf/scalapb/
-   repo: local
-    hooks:
-    -   id: scalafmt
-        name: scalafmt
-        language: system 
-        entry: scalafmt -i -f 
-        types_or: ["scala"]
- repo: local
-  hooks:
-      - id: gazelle
-        name: gazelle
-        language: system
-        entry: ./scripts/pre-commit-gazelle.sh
-        files: '(\.go|\.proto|BUILD\.bazel|BUILD|WORKSPACE|WORKSPACE\.bazel|\.bzl)$'
-        pass_filenames: false
-   repo: local
-    hooks:
-    -   id: update-action-result-types
-        name: update-action-result-types
-        language: system
-        entry: ./scripts/updateActionResultTypes.sh
-        files: 'src/main/protobuf/net/eagle0/eagle/common/action_result_type.proto'
@@ -1,47 +1,2 @@
-version = "3.9.9"
-runner.dialect = scala3
-rewrite.scala3.convertToNewSyntax = true
-# Keep braces, don't use significant indentation
-# rewrite.scala3.removeOptionalBraces = yes
-rewrite.scala3.insertEndMarkerMinLines = 15
-rewrite.scala3.removeEndMarkerMaxLines = 14
-
-# Strip margin settings
-assumeStandardLibraryStripMargin = false
-align.stripMargin = true
-
-# Code Style & Formatting
-align.preset = more
-align.multiline = true
-align.arrowEnumeratorGenerator = true
-spaces.inImportCurlyBraces = false
-spaces.beforeContextBoundColon = Never
-maxColumn = 120
-docstrings.style = Asterisk
-docstrings.wrap = yes
-
-# Method chaining
-newlines.beforeCurlyLambdaParams = multilineWithCaseOnly
-optIn.breakChainOnFirstMethodDot = true
-includeCurlyBraceInSelectChains = false
-
-# Advanced Scala 3 Features
-rewrite.scala3.countEndMarkerLines = all
-rewrite.redundantBraces.stringInterpolation = true
-rewrite.redundantBraces.parensForOneLineApply = true
-
-# Project-Specific Considerations
-optIn.annotationNewlines = true
-runner.optimizer.forceConfigStyleMinArgCount = 3
-
-# Import sorting configuration
-rewrite.rules = [SortImports, RedundantBraces, RedundantParens]
-rewrite.imports.sort = scalastyle
-rewrite.imports.groups = [
-  ["java\\..*"],
-  ["javax\\..*"],
-  ["scala\\..*"],
-  [".*"]
-]
-rewrite.imports.contiguousGroups = only
-rewrite.trailingCommas.style = never
+version = "3.6.1"
+runner.dialect = scala213
@@ -4,32 +4,26 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co

 ## Project Overview

-Eagle0 is a multi-language gaming system combining strategic turn-based gameplay (Eagle) with tactical hex-based
-combat (Shardok). The system integrates LLM-based narrative generation and supports both human and AI players.
+Eagle0 is a multi-language gaming system combining strategic turn-based gameplay (Eagle) with tactical hex-based combat (Shardok). The system integrates LLM-based narrative generation and supports both human and AI players.

 ## Architecture

 **Three-Tier Game System:**
-
 - **Unity Client (C#)**: Real-time strategy game client with integrated tactical combat UI
 - **Eagle (Scala)**: Strategic layer managing turn-based gameplay, diplomacy, hero progression, and province control
- **Shardok (C++)**: Tactical layer handling real-time hex-based combat simulation with performance-critical battle
-  resolution
+- **Shardok (C++)**: Tactical layer handling real-time hex-based combat simulation with performance-critical battle resolution

 **Communication Flow:**
-
 ```
 Unity Client ↔ Eagle (gRPC streaming) ↔ Shardok (internal gRPC) 
 ```

 **Key Entry Points:**
-
 - `/src/main/csharp/net/eagle0/clients/unity/eagle0/` - Unity C# game client
 - `/src/main/scala/net/eagle0/eagle/Main.scala` - Eagle strategic game server
 - `/src/main/cpp/net/eagle0/shardok/shardok_server_main.cpp` - Shardok tactical server

 **Protocol Buffer Architecture:**
-
 - Extensive use of protobuf for type-safe communication
 - Separate packages: `api/` (client-facing), `internal/` (server state), `views/` (client projections)
 - Event sourcing pattern with immutable action history
@@ -37,17 +31,13 @@ Unity Client ↔ Eagle (gRPC streaming) ↔ Shardok (internal gRPC)
 ## Essential Commands

 ### Building
-
 ```bash
 # Build Eagle server (Scala strategic layer)
 bazel build //src/main/scala/net/eagle0/eagle:eagle_server_deploy.jar

-# Build Shardok server (C++ tactical layer)
+# Build Shardok server (C++ tactical layer) 
 bazel build -c opt //src/main/cpp/net/eagle0/shardok:shardok-server

-# Shardok server includes both AI algorithms
-bazel build //src/main/cpp/net/eagle0/shardok:shardok-server
-
 # Build Unity/C# client
 ./scripts/build_protos.sh         # Protocol buffer generation for Unity
 ./scripts/build_plugins.sh        # Native plugins for all platforms  
@@ -56,7 +46,6 @@ bazel build //src/main/cpp/net/eagle0/shardok:shardok-server
 ```

 ### Running Services
-
 ```bash
 # Eagle server (port 40032)
 bazel run //src/main/scala/net/eagle0/eagle:eagle_server -- --eagle-grpc-port 40032
@@ -68,7 +57,6 @@ bazel run //src/main/cpp/net/eagle0/shardok:shardok-server --compilation_mode=op
 ```

 ### Testing
-
 ```bash
 # Run all tests
 bazel test //src/test/... //src/main/go/...
@@ -79,24 +67,12 @@ bazel test //src/test/cpp/...    # C++ Shardok tests
 ```

 ### Code Generation
-
 ```bash
 bazel run gazelle              # Update Go build files
 ./scripts/updateActionResultTypes.sh   # Update protocol buffer mappings
 ```

-### Pre-Commit Checklist
-
-**MANDATORY: Before running `git commit`, verify:**
-
-1. **If you modified any BUILD.bazel file:** Run `bazel run gazelle` and stage any changes it makes
-2. **If you modified C++ or C# files:** Run `clang-format -i` on the modified files
-3. **If you modified Scala files:** scalafmt will run automatically via pre-commit hook
-
-The pre-commit hook runs gazelle but only checks if it succeeds - it does NOT verify the BUILD files are in canonical format. The `gazelle_test` will fail if deps are not alphabetically sorted. **Always run gazelle manually after BUILD file changes.**
-
 ### Code Formatting
-
 ```bash
 # ALWAYS run clang-format after making any C++ or C# code changes
 clang-format -i <modified_files>
@@ -108,95 +84,26 @@ find . -name "*.cpp" -o -name "*.hpp" | xargs clang-format -i
 find . -name "*.cs" | xargs clang-format -i
 ```

-### Static Analysis
-
-```bash
-# Run clang-tidy static analysis on C++ files
-# Note: This may show some header include errors but will still analyze the main file
-bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,clang-analyzer-*' <file_path> -- -I/Users/dancrosby/CodingProjects/github/eagle0 -std=c++23
-
-# Example for AI files:
-bazel run @llvm_toolchain//:clang-tidy -- --checks='readability-*,bugprone-*,clang-analyzer-*' /Users/dancrosby/CodingProjects/github/eagle0/src/main/cpp/net/eagle0/shardok/ai/AIUnitScoreCalculator.cpp -- -I/Users/dancrosby/CodingProjects/github/eagle0 -std=c++23
-```
-
-## AI Algorithm Selection
-
-Eagle0 supports two AI algorithms for tactical combat decision-making:
-
-### Iterative Deepening AI (Default)
-
-The original minimax-based AI with sophisticated randomness handling:
-
- **Advantages**: Proven, sophisticated randomness evaluation, comprehensive lookahead
- **Use cases**: Production builds, scenarios requiring precise evaluation
- **Performance**: Single-threaded, thorough evaluation
-
-### Monte Carlo Tree Search AI (MCTS)
-
-Modern MCTS-based AI with multithreading support:
-
- **Advantages**: Multithreaded, better performance on modern CPUs, anytime algorithm
- **Use cases**: Performance testing, scenarios requiring fast decisions
- **Performance**: Multithreaded, adaptive depth based on time budget
-
-### Switching Between Algorithms
-
-The algorithm is selected at **runtime** via the ShardokAIClient constructor:
-
-```cpp
-// Using Iterative Deepening AI (default)
-ShardokAIClient client(playerId, isDefender, hexMap, settings);
-// OR explicitly:
-ShardokAIClient client(playerId, isDefender, hexMap, settings, AIAlgorithmType::ITERATIVE_DEEPENING);
-
-// Using MCTS AI
-ShardokAIClient client(playerId, isDefender, hexMap, settings, AIAlgorithmType::MCTS);
-```
-
-```bash
-# Build the server (includes both AI algorithms)
-bazel build //src/main/cpp/net/eagle0/shardok:shardok-server
-
-# Test both algorithms
-bazel test //src/test/cpp/net/eagle0/shardok/ai:ai_iterative_deepening_test
-bazel test //src/test/cpp/net/eagle0/shardok/ai:ai_mcts_test  # If available
-
-# Performance tests
-./scripts/ai_perf_test.sh  # Uses whatever algorithm the server is configured to use
-```
-
-Both implementations are compatible with all existing interfaces and produce the same `SearchResult` structure.
-
-**Note**: Both implementations are documented in `src/main/cpp/net/eagle0/shardok/ai/AI_SCORING_SYSTEM.md`, including
-recommendations for improving MCTS randomness handling.
-
-The AI algorithm selection is made at runtime when creating ShardokAIClient instances, allowing different AI strategies
-to be used for different players or game situations within the same server process.
-
 ## Language-Specific Patterns

 **Scala (Strategic Layer):**
-
 - Use `EngineImpl.scala` for core game logic modifications
 - Follow event sourcing pattern - all changes through immutable actions
 - gRPC streaming for real-time client updates via `EagleServiceImpl.scala`
 - LLM integration in `/common/llm_integration/` for narrative generation

 **C++ (Tactical Layer):**
-
 - Performance-critical combat in `ShardokEngine.hpp/.cpp`
 - FlatBuffers for efficient serialization in `/flatbuffer/` directory
 - AI systems in `/ai/` subdirectory with pluggable strategy selectors
 - Extensive unit testing with Google Test framework

 **Protocol Buffers:**
-
 - Three-layer structure: `api/` (client), `internal/` (server), `views/` (projections)
 - Use `shardok_internal_interface.proto` for Eagle-Shardok communication
 - Maintain backward compatibility when modifying existing messages

 **C# (Unity Client):**
-
 - Located in `/src/main/csharp/net/eagle0/clients/unity/eagle0/`
 - Uses Unity 6 (6000.0.32f1) with comprehensive protobuf integration (100+ .proto files)
 - Key components: `EagleConnection.cs` (gRPC client), `EagleGameController.cs` (main game logic)
@@ -205,7 +112,6 @@ to be used for different players or game situations within the same server proce
 - Seamless transition between strategic gameplay and hex-based tactical combat

 **Go (Build Tools):**
-
 - Build automation and code generation utilities
 - AWS S3 integration for deployment artifacts

@@ -216,31 +122,6 @@ to be used for different players or game situations within the same server proce
 - Map validation tests ensure game content integrity
 - Use `GameSettings_test_utils.cpp` and `ShardokEngineBasedTestData.cpp` for C++ test helpers

-### Scala Testing Patterns
-
-**Use `inside()` instead of `asInstanceOf` for type matching in tests:**
-
-Never use `asInstanceOf` in tests. Instead, use ScalaTest's `inside()` pattern for safe type matching:
-
-```scala
-// BAD - don't do this
-val changedHero = result.changedHeroes.head.asInstanceOf[ChangedHeroC]
-changedHero.heroId shouldBe 19
-
-// GOOD - use inside() pattern
-import org.scalatest.Inside.inside
-
-inside(result.changedHeroes.head) { case changedHero: ChangedHeroC =>
-  changedHero.heroId shouldBe 19
-  changedHero.vigorChange shouldBe StatDelta(17.2)
-}
-```
-
-The `inside()` pattern:
- Provides better error messages when the type doesn't match
- Is idiomatic ScalaTest
- Works with pattern matching for more complex assertions
-
 ## Performance Testing

 When making performance-related changes to the AI or engine:
@@ -272,38 +153,10 @@ done
 ```

 **Important notes:**
-
 - Run tests multiple times (3-5) to account for performance variance
 - Focus on commands evaluated at each depth rather than total commands
 - Commands at different depths aren't directly comparable (depth 3 is more valuable than depth 2)
- **Always test performance changes** - what seems like an optimization may sometimes have unexpected overhead or
-  behavior changes.
-
-## Troubleshooting Scala Build Errors
-
-### MissingType Errors
-
-When you see errors like:
-```
-dotty.tools.dotc.core.MissingType: Cannot resolve reference to type net.eagle0.eagle.internal.game_state.type.GameState
-```
-
-**This is NOT a Scala compiler crash.** This is a missing dependency in BUILD.bazel.
-
-**How to fix:**
-1. Identify the missing type from the error message (e.g., `game_state.GameState`)
-2. Find the Bazel target that provides this type (e.g., `//src/main/protobuf/net/eagle0/eagle/internal:game_state_scala_proto`)
-3. Add it to the `deps` of the failing target
-4. If the type appears in a public method signature, also add it to `exports` so downstream targets can see it
-
-**Common pattern:** When adding a method to a class that takes or returns a proto type, the proto dependency often needs to be added to both `deps` AND `exports`.
-
-### Bazel Clean
-
-**NEVER run `bazel clean` without asking first.** It rarely fixes actual issues and wastes significant rebuild time. The issues that seem like they need `bazel clean` are usually:
- Missing imports in Scala code
- Missing dependencies in BUILD.bazel
- Missing exports for types used in public signatures
+- **Always test performance changes** - what seems like an optimization may sometimes have unexpected overhead or behavior changes.

 ## Game Content

@@ -315,6 +168,4 @@ dotty.tools.dotc.core.MissingType: Cannot resolve reference to type net.eagle0.e

 - Bazel handles multi-language builds and dependencies
 - CI/CD via GitHub Actions with platform-specific build scripts in `/ci/github_actions/`
- Docker containerization available via `ci/eagle_run.Dockerfile`
- Always run "bazel run //:gazelle" after editing any BUILD.bazel files
- *ALWAYS ALWAYS* run "bazel run gazelle" after any change that modifies a BUILD.bazel file
+- Docker containerization available via `ci/eagle_run.Dockerfile`
@@ -1,51 +1,12 @@
-module(name = "net_eagle0")
-
-# Version constants
-SCALA_VERSION = "3.7.2"
-
-NETTY_VERSION = "4.1.110.Final"
-
-SCALAPB_VERSION = "1.0.0-alpha.1"
-
-AWS_SDK_VERSION = "2.28.1"
+bazel_dep(name = "apple_support", repo_name = "build_bazel_apple_support", version = "1.21.1")

 #
-# Core Build Tools
-#
-
-bazel_dep(name = "bazel_skylib", version = "1.8.1")
-bazel_dep(name = "rules_pkg", version = "1.1.0")
-
-#
-# Language Support - Scala
-#
-
-bazel_dep(name = "rules_scala", version = "7.1.1")
-
-scala_config = use_extension(
-    "@rules_scala//scala/extensions:config.bzl",
-    "scala_config",
-)
-
-scala_config.settings(scala_version = SCALA_VERSION)
-
-scala_deps = use_extension(
-    "@rules_scala//scala/extensions:deps.bzl",
-    "scala_deps",
-)
-
-scala_deps.scala()
-
-scala_deps.scalatest()
-
-scala_deps.scala_proto()
-
-#
-# Language Support - C++
+# bazel-toolchain
 #

 bazel_dep(name = "toolchains_llvm", version = "1.4.0")

+# Configure and register the toolchain.
 llvm = use_extension("@toolchains_llvm//toolchain/extensions:llvm.bzl", "llvm")

 llvm.toolchain(
@@ -55,10 +16,18 @@ llvm.toolchain(

 use_repo(llvm, "llvm_toolchain")

-#
-# Language Support - Go
-#
+# Set dev_dependency so we can turn this off for swift MacOS builds
+register_toolchains(
+    "@llvm_toolchain//:all",
+    dev_dependency = True,
+)

+bazel_dep(name = "rules_pkg", version = "1.1.0")
+bazel_dep(name = "bazel_skylib", version = "1.8.1")
+bazel_dep(name = "protobuf", repo_name = "com_google_protobuf", version = "29.2")
+bazel_dep(name = "grpc", version = "1.71.0")
+bazel_dep(name = "grpc-java", version = "1.71.0")
+bazel_dep(name = "googletest", version = "1.17.0")
 bazel_dep(name = "rules_go", repo_name = "io_bazel_rules_go", version = "0.56.1")
 bazel_dep(name = "gazelle", repo_name = "bazel_gazelle", version = "0.45.0")

@@ -76,99 +45,69 @@ use_repo(
    "com_github_aws_aws_sdk_go_v2_config",
    "com_github_aws_aws_sdk_go_v2_credentials",
    "com_github_aws_aws_sdk_go_v2_service_s3",
-    "org_golang_google_grpc",
    "org_golang_google_protobuf",
+    "org_golang_x_text",
+    "com_github_google_go_cmp",
 )

-#
-# Platform Support - Apple/iOS
-#
-
-bazel_dep(name = "apple_support", repo_name = "build_bazel_apple_support", version = "1.21.1")
-bazel_dep(name = "rules_apple", repo_name = "build_bazel_rules_apple", version = "3.16.1")
-bazel_dep(name = "rules_swift", repo_name = "build_bazel_rules_swift", version = "2.3.1")
+#go_sdk.nogo(
+#    nogo = "//:my_nogo",
+#)

 #
-# Protocol Buffers & RPC
+# rules_jvm_external
 #

-bazel_dep(name = "protobuf", repo_name = "com_google_protobuf", version = "29.2")
-bazel_dep(name = "grpc", version = "1.71.0")
-bazel_dep(name = "grpc-java", version = "1.71.0")
-bazel_dep(name = "flatbuffers", version = "25.2.10")
+scala_version = "2.13.14"

-#
-# Testing
-#
-
-bazel_dep(name = "googletest", version = "1.17.0")
-
-#
-# Java/Scala Dependencies
-#
-
-bazel_dep(name = "rules_jvm_external", version = "6.3")
+bazel_dep(
+    name = "rules_jvm_external",
+    version = "6.3",
+)

 maven = use_extension("@rules_jvm_external//:extensions.bzl", "maven")

 maven.install(
    artifacts = [
-        # Netty
-        "io.netty:netty-codec:%s" % NETTY_VERSION,
-        "io.netty:netty-codec-http:%s" % NETTY_VERSION,
-        "io.netty:netty-codec-socks:%s" % NETTY_VERSION,
-        "io.netty:netty-codec-http2:%s" % NETTY_VERSION,
-        "io.netty:netty-handler:%s" % NETTY_VERSION,
-        "io.netty:netty-buffer:%s" % NETTY_VERSION,
-        "io.netty:netty-transport:%s" % NETTY_VERSION,
-        "io.netty:netty-resolver:%s" % NETTY_VERSION,
-        "io.netty:netty-common:%s" % NETTY_VERSION,
-        "io.netty:netty-handler-proxy:%s" % NETTY_VERSION,
-
-        # ScalaPB
-        "com.thesamet.scalapb:lenses_3:%s" % SCALAPB_VERSION,
-        "com.thesamet.scalapb:scalapb-json4s_3:%s" % SCALAPB_VERSION,
-        "com.thesamet.scalapb:scalapb-runtime_3:%s" % SCALAPB_VERSION,
-        "com.thesamet.scalapb:scalapb-runtime-grpc_3:%s" % SCALAPB_VERSION,
-        "com.thesamet.scalapb:compilerplugin_3:%s" % SCALAPB_VERSION,
-        "com.thesamet.scalapb:protoc-bridge_3:0.9.9",
-
-        # JSON
-        "org.json4s:json4s-ast_3:4.1.0-M8",
-        "org.json4s:json4s-core_3:4.1.0-M8",
-        "org.json4s:json4s-native_3:4.1.0-M8",
-
-        # Testing
-        "org.scalamock:scalamock_3:7.4.1",
-
-        # AWS SDK
-        "software.amazon.awssdk:s3-transfer-manager:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:s3:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:regions:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:aws-core:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:sdk-core:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:utils:%s" % AWS_SDK_VERSION,
-        "software.amazon.awssdk:http-client-spi:%s" % AWS_SDK_VERSION,
-
-        # AWS Lambda
-        "com.amazonaws:aws-lambda-java-core:1.2.3",
-        "com.amazonaws:aws-lambda-java-events:3.13.0",
-
-        # Logging
+        "org.scala-lang:scala-library:%s" % scala_version,
+        "io.netty:netty-codec:4.1.110.Final",
+        "io.netty:netty-codec-http:4.1.110.Final",
+        "io.netty:netty-codec-socks:4.1.110.Final",
+        "io.netty:netty-codec-http2:4.1.110.Final",
+        "io.netty:netty-handler:4.1.110.Final",
+        "io.netty:netty-buffer:4.1.110.Final",
+        "io.netty:netty-transport:4.1.110.Final",
+        "io.netty:netty-resolver:4.1.110.Final",
+        "io.netty:netty-common:4.1.110.Final",
+        "io.netty:netty-handler-proxy:4.1.110.Final",
+        "com.thesamet.scalapb:lenses_2.13:1.0.0-alpha.1",
+        "com.thesamet.scalapb:scalapb-json4s_2.13:1.0.0-alpha.1",
+        "com.thesamet.scalapb:scalapb-runtime_2.13:1.0.0-alpha.1",
+        "com.thesamet.scalapb:scalapb-runtime-grpc_2.13:1.0.0-alpha.1",
+        "com.thesamet.scalapb:compilerplugin_2.13:1.0.0-alpha.1",
+        "com.thesamet.scalapb:protoc-bridge_2.13:0.9.8",
+        "org.json4s:json4s-ast_2.13:4.0.7",
+        "org.json4s:json4s-core_2.13:4.0.7",
+        "org.json4s:json4s-native_2.13:4.0.7",
+        "org.scalamock:scalamock_2.13:6.0.0",
+        "software.amazon.awssdk:s3-transfer-manager:2.28.1",
+        "software.amazon.awssdk:s3:2.28.1",
+        "software.amazon.awssdk:regions:2.28.1",
+        "software.amazon.awssdk:aws-core:2.28.1",
+        "software.amazon.awssdk:sdk-core:2.28.1",
        "org.slf4j:slf4j-api:2.0.16",
        "org.slf4j:slf4j-simple:2.0.16",
-
-        # Other
+        #"software.amazon.awssdk:sns:2.28.1",
+        "software.amazon.awssdk:utils:2.28.1",
+        "software.amazon.awssdk:http-client-spi:2.28.1",
        "org.reactivestreams:reactive-streams:1.0.4",
+        "com.amazonaws:aws-lambda-java-core:1.2.3",
+        "com.amazonaws:aws-lambda-java-events:3.13.0",
        "javax.xml.bind:jaxb-api:2.3.1",
-
-        # OkHttp (for SSE with read timeout support)
-        "com.squareup.okhttp3:okhttp:4.12.0",
-        "com.squareup.okhttp3:okhttp-sse:4.12.0",
    ],
    duplicate_version_warning = "error",
    fail_if_repin_required = True,
-    lock_file = "//:maven_install.json",
+    lock_file = "//:maven_install.json",  #
    repositories = [
        "https://repo1.maven.org/maven2",
    ],
@@ -177,49 +116,58 @@ maven.install(
 use_repo(maven, "maven", "unpinned_maven")

 #
-# External Libraries
+# rules_apple
 #

+bazel_dep(
+    name = "rules_apple",
+    repo_name = "build_bazel_rules_apple",
+    version = "3.16.1",
+)
+bazel_dep(
+    name = "rules_swift",
+    repo_name = "build_bazel_rules_swift",
+    version = "2.3.1",
+)
+
+#
+# Unbazelified imports
+#
 http_archive = use_repo_rule("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

-# GTL (for parallel_hashmap)
-GTL_VERSION = "1.2.0"
+#
+# flatbuffers
+#
+bazel_dep(name = "flatbuffers", version = "25.2.10")

-GTL_SHA = "1969c45dd76eac0dd87e9e2b65cffe358617f4fe1bcd203f72f427742537913a"
+#
+# gtl (for parallel_hashmap)
+#
+
+gtl_version = "1.2.0"
+
+gtl_sha = "1969c45dd76eac0dd87e9e2b65cffe358617f4fe1bcd203f72f427742537913a"

 http_archive(
    name = "gtl",
    build_file = "@//external:BUILD.gtl",
-    sha256 = GTL_SHA,
-    strip_prefix = "gtl-%s" % GTL_VERSION,
-    url = "https://github.com/greg7mdp/gtl/archive/refs/tags/v%s.zip" % GTL_VERSION,
+    sha256 = gtl_sha,
+    strip_prefix = "gtl-%s" % gtl_version,
+    url = "https://github.com/greg7mdp/gtl/archive/refs/tags/v%s.zip" % gtl_version,
 )

-# Unity GoDice Plugin
-UNITY_GODICE_COMMIT = "18d6823991592e4d45fcc0f22692db849dea9063"
+#
+# Plugins for the native code for interacting with GoDice
+#
+unity_godice_commit = "18d6823991592e4d45fcc0f22692db849dea9063"

-UNITY_GODICE_SHA = "04e6ae4155965aab3372592e04061eba1256bb6ea7ccffd0d83f27574e5b3349"
+unity_godice_sha = "04e6ae4155965aab3372592e04061eba1256bb6ea7ccffd0d83f27574e5b3349"

 http_archive(
    name = "net_eagle0_unity_godice",
-    sha256 = UNITY_GODICE_SHA,
-    strip_prefix = "godice-framework-%s" % UNITY_GODICE_COMMIT,
+    sha256 = unity_godice_sha,
+    strip_prefix = "godice-framework-%s" % unity_godice_commit,
    urls = [
-        "https://github.com/nolen777/godice-framework/archive/%s.zip" % UNITY_GODICE_COMMIT,
+        "https://github.com/nolen777/godice-framework/archive/%s.zip" % unity_godice_commit,
    ],
 )
-
-#
-# Toolchain Registration
-#
-
-register_toolchains(
-    "//tools:unused_dependency_checker_error_and_opts_toolchain",
-    "@rules_scala//testing:scalatest_toolchain",
-)
-
-# Set dev_dependency so we can turn this off for swift MacOS builds
-register_toolchains(
-    "@llvm_toolchain//:all",
-    dev_dependency = True,
-)
@@ -1,2 +1,51 @@
-# This file marks the root of the Bazel workspace.
-# See MODULE.bazel for external dependencies and setup.
+workspace(name = "net_eagle0")
+
+load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
+
+#
+# Scala support
+#
+
+scala_version = "2.13.14"
+
+#rules_scala_version = "6.6.0"
+
+#rules_scala_sha = "e734eef95cf26c0171566bdc24d83bd82bdaf8ca7873bec6ce9b0d524bdaf05d"
+
+#http_archive(
+#    name = "io_bazel_rules_scala",
+#    sha256 = rules_scala_sha,
+#    strip_prefix = "rules_scala-%s" % rules_scala_version,
+#    url = "https://github.com/bazelbuild/rules_scala/releases/download/v%s/rules_scala-v%s.tar.gz" % (rules_scala_version, rules_scala_version),
+#)
+
+# Using a commit from master to get 2.13.14 support. Restore the commented-out lines above with a new
+# release version when one is cut.
+rules_scala_commit = "e53a43bf48f10a5906b3e91c21798281cec1b334"
+
+rules_scala_sha = "b4fd903724d084d9d9f45e17fc22391bda745bf0574f8934d38a9c1c2fc18834"
+
+http_archive(
+    name = "io_bazel_rules_scala",
+    sha256 = rules_scala_sha,
+    strip_prefix = "rules_scala-%s" % rules_scala_commit,
+    url = "https://github.com/bazelbuild/rules_scala/archive/%s.zip" % rules_scala_commit,
+)
+
+load("@io_bazel_rules_scala//:scala_config.bzl", "scala_config")
+
+scala_config(scala_version = scala_version)
+
+load("//tools:toolchains.bzl", "scala_register_toolchains")
+
+scala_register_toolchains()
+
+load("@io_bazel_rules_scala//scala:scala.bzl", "scala_repositories")
+
+scala_repositories()
+
+load("@io_bazel_rules_scala//testing:scalatest.bzl", "scalatest_repositories", "scalatest_toolchain")
+
+scalatest_repositories()
+
+scalatest_toolchain()
@@ -1 +1,2 @@
-UNITY_VERSION='6000.3.0f1'
+
+UNITY_VERSION='6000.1.11f1'
@@ -1,280 +0,0 @@
-# CommandProto Usage Analysis in shardok/ai
-
-This document analyzes all remaining usages of `CommandProto` (protocol buffer representation) in the AI code and identifies opportunities to eliminate proto conversion by using `ShardokCommand` directly.
-
-## Summary
-
-**Total CommandProto usages found:** 42 locations across 9 files
-
-**Eliminated:** 6 usages (14%) - ✅ **Phase 1 Complete**
-**Can be eliminated:** ~14 usages (33%)
-**Must keep (for now):** ~22 usages (53%)
-
---
-
-## Files with CommandProto Usage
-
-### 1. AICommandFilter.cpp (6 usages) - ✅ **COMPLETED** (PR #4505)
-**Location:** Lines 146, 189, 252, 356, 387, 428
-
-**Original usage:**
-```cpp
-const auto cmdProto = cmd.GetCommandProto();
-if (!cmdProto.has_target()) { ... }
-const auto& targetCoords = cmdProto.target();
-if (!cmdProto.has_actor()) { ... }
-const auto unitId = cmdProto.actor().value();
-```
-
-**Replaced with:**
-```cpp
-const int targetRow = cmd.GetTargetRow();
-const int targetCol = cmd.GetTargetColumn();
-if (targetRow < 0 || targetCol < 0) {
-    throw ShardokInternalErrorException("Command missing required target");
-}
-const Coords targetCoords(targetRow, targetCol);
-
-const int actorId = cmd.GetActorUnitId();
-if (actorId < 0) {
-    throw ShardokInternalErrorException("Command missing required actor");
-}
-```
-
-**Status:** ✅ **ELIMINATED** - Replaced with direct accessors + exception handling
-**Impact:** Eliminated 6 proto conversions in hot path (command filtering)
-**Completed:** Phase 1, PR #4505
-
---
-
-### 2. ShardokAIClient.cpp (8 usages)
-**Location:** Lines 83, 86, 87, 102, 105, 237, 261, 311, 356
-
-**Usage breakdown:**
-
-#### a) Command validation (lines 83-87)
-```cpp
-void CheckCommand(const CommandProto &realDescriptor, const CommandProto &guessedDescriptor) {
-    differencer.IgnoreField(CommandProto::descriptor()->FindFieldByNumber(
-            CommandProto::kFollowUpCommandTypesFieldNumber));
-```
-**Status:** ❌ **MUST KEEP** - Uses protobuf reflection for comparison
-**Reason:** Comparing proto messages for correctness checking requires proto API
-
-#### b) GetAvailableCommandProtos calls (lines 105, 356)
-```cpp
-const auto guessedCommands = guessedEngine.GetAvailableCommandProtos(playerId, false);
-if (const auto &availableCommands = engine.GetAvailableCommandProtos(playerId, false);
-```
-**Status:** ✅ **CAN REPLACE** - Should use `GetAvailableCommandsForAIPlayer()` instead
-**Impact:** This is a major conversion point - converts entire command list to protos
-**Priority:** HIGH (converts all commands to proto unnecessarily)
-
-#### c) Strategy selector methods (lines 102, 237, 261, 311)
-```cpp
-const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults
-```
-**Status:** ✅ **CAN REPLACE** - Depends on fixing strategy selector signatures
-**Priority:** MEDIUM (depends on other refactors)
-
---
-
-### 3. IterativeDeepeningAI.cpp/hpp (4 usages)
-**Location:** Lines 41, 272 (cpp), 73, 96 (hpp)
-
-**Current usage:**
-```cpp
-const std::vector<CommandProto>& commands,
-```
-
-**Status:** ✅ **CAN REPLACE** - These methods should accept `CommandListSPtr` instead
-**Impact:** Major - this is the main AI search algorithm
-**Priority:** HIGH (core AI algorithm)
-
-**Note:** IterativeDeepeningAI already receives commands as proto vectors. The conversion happens upstream at the entry point. Need to trace back to find where `GetAvailableCommandProtos` is called.
-
---
-
-### 4. AIFleeDecisionCalculator.cpp/hpp (6 usages)
-**Location:** Lines 17, 38, 39, 62, 63 (hpp), 18, 19, 137, 138 (cpp)
-
-**Current usage:**
-```cpp
-const vector<CommandProto>& availableCommands,
-const vector<CommandProto>::const_iterator& fleeCommand,
-```
-
-**Status:** ✅ **CAN REPLACE** - Should use `CommandListSPtr` and indices instead
-**Impact:** Flee decision logic could avoid proto conversion
-**Priority:** MEDIUM
-
---
-
-### 5. AIAttackerStrategySelector.cpp/hpp (2 usages)
-**Location:** Line 30 in both files
-
-**Current usage:**
-```cpp
-const vector<CommandProto>& availableCommands) -> AIStrategy
-```
-
-**Status:** ⚠️ **PARTIALLY REPLACEABLE** - Currently doesn't use the commands parameter
-**Current implementation:**
-```cpp
-const vector<CommandProto>& /*availableCommands*/) -> AIStrategy {
-    // Parameter is commented out - not used!
-    return AIStrategy::DEFAULT;
-}
-```
-**Priority:** LOW (parameter unused, but signature should be consistent)
-
---
-
-### 6. AICommandEvaluator.hpp (1 usage)
-**Location:** Line 27
-
-**Current usage:**
-```cpp
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-```
-
-**Status:** ⚠️ **CHECK USAGE** - Type alias, need to check if used
-**Priority:** LOW (just a type alias)
-
---
-
-### 7. AIScoreCalculator.hpp (1 usage)
-**Location:** Line 24
-
-**Current usage:**
-```cpp
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-```
-
-**Status:** ⚠️ **CHECK USAGE** - Type alias, need to check if used
-**Priority:** LOW (just a type alias)
-
---
-
-### 8. AIWaterCrossingCommandChooser.hpp (1 usage)
-**Location:** Line 20
-
-**Current usage:**
-```cpp
-using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
-```
-
-**Status:** ⚠️ **CHECK USAGE** - Type alias, need to check if used
-**Priority:** LOW (just a type alias)
-
---
-
-## Key Conversion Points (Entry Points)
-
-### ShardokEngine::GetAvailableCommandProtos()
-This method converts the entire command list from `CommandListSPtr` to `vector<CommandProto>`.
-
-**Current flow:**
-```
-ShardokEngine::GetAvailableCommandsForAIPlayer() → CommandListSPtr
-                ↓ (conversion)
-ShardokEngine::GetAvailableCommandProtos() → vector<CommandProto>
-                ↓
-AI algorithms (IterativeDeepeningAI, etc.)
-```
-
-**Desired flow:**
-```
-ShardokEngine::GetAvailableCommandsForAIPlayer() → CommandListSPtr
-                ↓ (no conversion!)
-AI algorithms use CommandSPtr directly
-```
-
---
-
-## Recommendations by Priority
-
-### HIGH Priority (Performance-critical hot paths)
-
-1. **AICommandFilter.cpp (6 usages)**
-   - Replace `cmd.GetCommandProto()` with direct accessor methods
-   - Use `GetActorUnitId()`, `GetTargetRow()`, `GetTargetColumn()`
-   - Impact: Eliminates 6 proto conversions per filtered command
-
-2. **ShardokAIClient.cpp - GetAvailableCommandProtos calls**
-   - Replace calls to `GetAvailableCommandProtos()` with `GetAvailableCommandsForAIPlayer()`
-   - Impact: Eliminates conversion of entire command list
-
-3. **IterativeDeepeningAI**
-   - Change signature from `vector<CommandProto>` to `CommandListSPtr`
-   - Impact: Main AI search algorithm avoids proto conversion
-
-### MEDIUM Priority
-
-4. **AIFleeDecisionCalculator**
-   - Change to use `CommandListSPtr` and indices
-   - Impact: Flee decision logic avoids proto
-
-5. **ShardokAIClient strategy methods**
-   - Update signatures to use `CommandListSPtr`
-   - Cascades to strategy selectors
-
-### LOW Priority
-
-6. **Type aliases**
-   - Remove unused `using CommandProto` declarations
-   - Clean up imports
-
---
-
-## Migration Strategy
-
-### Phase 1: Low-hanging fruit (AICommandFilter) - ✅ **COMPLETED** (PR #4505)
- ✅ Replaced 6 proto conversions with direct accessor calls
- ✅ Added exception handling for missing actor/target data
- ✅ No signature changes needed
- ✅ Immediate performance benefit
- **PR:** #4505
-
-### Phase 2: Entry point (ShardokAIClient)
- Replace `GetAvailableCommandProtos()` calls with `GetAvailableCommandsForAIPlayer()`
- Update method signatures in ShardokAIClient
-
-### Phase 3: Core AI (IterativeDeepeningAI)
- Change IterativeDeepeningAI to accept `CommandListSPtr`
- This is the biggest change but has highest impact
-
-### Phase 4: Supporting systems
- Update AIFleeDecisionCalculator
- Update strategy selectors
- Clean up type aliases
-
-### Phase 5: Validation code
- Keep proto-based validation as-is (uses reflection)
- Consider if validation is still needed in production
-
---
-
-## Notes
-
- **MCTS already converted**: The MCTS code path already uses `CommandListSPtr` directly
- **Proto still needed**: For serialization/network communication (not in AI hot path)
- **Validation**: Proto comparison in CheckCommand() should remain (uses proto reflection)
-
---
-
-## Estimated Impact
-
-**Proto conversions eliminated:** ~20-25 per command choice
-**Performance gain:** Eliminates hundreds of allocations per AI decision
-**Code simplification:** Removes proto conversion layer from AI
-
-**Before:**
-```
-Command → Proto → AI Decision
-```
-
-**After:**
-```
-Command → AI Decision (direct)
-```
@@ -1,309 +0,0 @@
-# Deproto Migration Plan
-
-## Vision
-
-**Protocol buffers should only be used at the edges** — for network serialization (gRPC) and disk persistence. Inside the Eagle game engine, all logic should operate on native Scala models.
-
-```
-┌─────────────────────────────────────────────────────────────────────┐
-│                         GRPC BOUNDARY                               │
-│  EagleServiceImpl.scala  ←→  Proto Messages  ←→  Unity Client       │
-└─────────────────────────────────────────────────────────────────────┘
-                                   ↓
-                          GameStateConverter
-                                   ↓
-┌─────────────────────────────────────────────────────────────────────┐
-│                         SCALA ENGINE                                │
-│                                                                     │
-│   GameStateC ───→ Actions ───→ ActionResultT ───→ New GameStateC   │
-│       ↑                                                   │        │
-│       │               (Pure Scala models)                 │        │
-│       └───────────────────────────────────────────────────┘        │
-│                                                                     │
-│   HeroC, FactionC, ProvinceC, BattalionC, ArmyC, etc.              │
-└─────────────────────────────────────────────────────────────────────┘
-                                   ↓
-                          GameStateConverter
-                                   ↓
-┌─────────────────────────────────────────────────────────────────────┐
-│                      PERSISTENCE BOUNDARY                           │
-│  GameHistory.scala  ←→  Proto Messages  ←→  File/Database          │
-└─────────────────────────────────────────────────────────────────────┘
-```
-
---
-
-## Current State
-
-### Completed Phases
-
-| Phase | Status | Summary |
-|-------|--------|---------|
-| Phase 1: GameStateC | **Complete** | Scala `GameState` model with 22 fields |
-| Phase 2: EngineImpl | **Complete** | Holds Scala `GameState` internally |
-| Phase 3: GameHistory | **Complete** | `stateAfter` returns Scala GameState |
-| Phase 4: ActionResultT | **Complete** | All 59 actions return `ActionResultT` |
-| Phase 5: Action Base Classes | **Complete** | All `RandomSequentialResultsAction` and `DeterministicSingleResultAction` converted to T-type base classes |
-| Phase 5b: Base Class Cleanup | **Complete** | `RandomSequentialResultsAction` and `DeterministicSingleResultAction` deleted |
-| Phase 5c: RoundPhaseAdvancer Actions | **Complete** | All actions called by RoundPhaseAdvancer accept Scala GameState |
-| Phase 5d: RoundPhaseAdvancer Itself | **Complete** | RoundPhaseAdvancer.checkForPhaseAdvancement takes Scala GameState |
-
-### Phase 5c/5d Progress (Complete)
-
-`RoundPhaseAdvancer.checkForPhaseAdvancement` now accepts Scala `GameState` and `ActionResultApplier` directly (PR #4677).
-
-| Action | PR | Status |
-|--------|-----|--------|
-| `PrisonerExchangeAction` | #4670 | ✅ Merged |
-| `PerformForcedTurnBackAction` | #4671 | ✅ Merged |
-| `PerformHeroDeparturesAction` | #4672 | ✅ Merged |
-| `RequestFreeForAllBattlesAction` | #4673 | ✅ Merged |
-| `EndPlayerCommandsPhaseAction` | #4674 | ✅ Merged |
-| `EndDiplomacyResolutionPhaseAction` | #4675 | ✅ Merged |
-| `RoundPhaseAdvancer` itself | #4677 | ✅ Merged |
-
-### EngineImpl Progress
-
-| Change | PR | Status |
-|--------|-----|--------|
-| `recursiveTransform` deleted | #4677 | ✅ Merged |
-| `recursiveTransformT` uses `RandomStateTSequencer` | #4677 | ✅ Merged |
-
-### Current Architecture
-
-**ActionResultT Production (100% Complete):**
- All actions produce `ActionResultT`
- Conversion to `ActionResultProto` happens via `ActionResultProtoConverter.toProto()`
- No direct `ActionResultProto` construction outside the converter
-
-**ActionResultProto Consumption (Next Target):**
- `ActionResultProtoApplierImpl` - applies proto results to proto GameState
- `RoundPhaseAdvancer` - calls converter, passes protos to applier
- `InMemoryHistory` / `PersistedHistory` - stores proto results
- Service layer (`GameController`, `GamesManager`, etc.) - uses proto for client communication
-
---
-
-## Phase 6: Migrate to ActionResultT Consumers
-
-### Objective
-
-Eliminate internal consumption of `ActionResultProto`. Everything inside the engine should work with `ActionResultT`.
-
-### Current Flow (Proto-Heavy)
-```
-Action.execute()
-    → ActionResultT
-    → ActionResultProtoConverter.toProto()
-    → ActionResultProto
-    → ActionResultProtoApplierImpl.applyActionResults()
-    → GameStateProto
-    → GameStateConverter.fromProto()
-    → GameStateC
-```
-
-### Target Flow (T-Types Throughout)
-```
-Action.execute()
-    → ActionResultT
-    → ActionResultApplier.applyActionResults()
-    → GameStateC
-
-    (Proto conversion only at boundaries)
-```
-
-### Key Files to Convert
-
-**Tier 1 - Core Applier:** ✅ **Complete**
-```
-src/main/scala/net/eagle0/eagle/library/actions/applier/ActionResultApplierImpl.scala
-```
-`ActionResultApplier` applies `ActionResultT` directly to Scala `GameState`. The legacy `ActionResultTApplierImpl` wraps it and converts to/from proto for callers that still need proto types.
-
-**Tier 2 - RoundPhaseAdvancer:** ✅ **Complete**
-```
-src/main/scala/net/eagle0/eagle/library/RoundPhaseAdvancer.scala
-```
-Now accepts Scala `GameState` and `ActionResultApplier`. Only converts to proto lazily for `AvailableCommandsFactory` calls.
-
-**Tier 3 - Sequencers:**
-```
-src/main/scala/net/eagle0/eagle/library/actions/impl/common/RandomStateTSequencer.scala
-src/main/scala/net/eagle0/eagle/library/actions/impl/common/RandomStateProtoSequencer.scala
-```
-Modify `RandomStateTSequencer` to thread Scala `GameState` throughout (currently converts to proto internally). Then evaluate whether `RandomStateProtoSequencer` is still needed at all.
-
-**Current State**: `RandomStateTSequencer` accepts Scala `GameState` via its `apply()` method but internally converts to proto. All callback methods (`withRandomActionResult`, `withActionResults`, etc.) pass `GameStateProto` to callers, forcing actions that use the sequencer to work with proto types internally.
-
-**Target State**: Create a fully protoless sequencer where:
-1. `lastState` returns Scala `GameState` (not `lastStateProto`)
-2. All callback methods pass Scala `GameState` to callers
-3. Actions using the sequencer can be fully protoless
-
-**Migration Path**:
-1. Add `lastState: GameState` method alongside `lastStateProto` (non-breaking)
-2. Add parallel callback methods that pass Scala GameState (e.g., `withScalaActionResult`)
-3. Migrate actions one by one to use the new Scala-based callbacks
-4. Once all actions migrated, deprecate/remove proto-based callbacks
-5. Remove `lastStateProto` once no longer used
-
-**RandomStateSequencer Migration Progress** (PR #4679 introduced protoless `RandomStateSequencer`):
-
-| Action | Status |
-|--------|--------|
-| `TruceTurnBackPhaseAction` | ✅ Migrated (PR #4680) |
-| `EndHandleRiotsPhaseAction` | ✅ Migrated (PR #4684) |
-| `PerformVassalCommandsPhaseAction` | ✅ Migrated |
-| `PerformVassalDefenseDecisionsAction` | ✅ Migrated |
-| `EndVassalCommandsPhaseAction` | ✅ Migrated |
-| `PerformReconResolutionAction` | ✅ Migrated |
-| `NewRoundAction` | ✅ Migrated (PR #4698) |
-| `EndBattleAftermathPhaseAction` | ✅ Migrated (PR #4699) |
-| `EndDiplomacyResolutionPhaseAction` | ✅ Migrated |
-| `PerformUnaffiliatedHeroesAction` | ✅ Migrated |
-| `EngineImpl.recursiveTransformT` | ✅ Migrated (PR #4704) |
-| `ProtolessSequentialResultsActionWrapper` | ✅ Migrated (PR #4705) |
-| `LegacyRandomStateTSequencer` | ✅ **Deleted** (PR #4705) |
-
-**TCommandFactory Extraction** (PR #4684):
-
-To enable lightweight mocking of command creation in tests, `TCommandFactory` trait was extracted from `CommandFactory`. This allows tests to mock just the `makeTCommand` method without pulling in all 40+ command dependencies that `CommandFactory` requires.
-
- `TCommandFactory` - lightweight trait with just `makeTCommand`
- `CommandFactory extends TCommandFactory` - maintains backward compatibility
- Actions accepting command factories now use `TCommandFactory` type for better testability
-
-**Tier 4 - History APIs:**
-```
-src/main/scala/net/eagle0/eagle/service/InMemoryHistory.scala
-src/main/scala/net/eagle0/eagle/service/PersistedHistory.scala
-```
-Change APIs to vend Scala `GameState` and `ActionResultT` instead of proto versions. `PersistedHistory` converts to proto internally for disk persistence; `InMemoryHistory` doesn't need proto at all.
-
-### ActionResultProto Consumer Inventory
-
-| File | Usage | Status |
-|------|-------|--------|
-| `ActionResultApplierImpl.scala` | Applies ActionResultT to Scala GameState | ✅ **Complete** |
-| `ActionResultTApplierImpl.scala` | Legacy wrapper - converts to/from proto | Keep until all callers migrated |
-| `RoundPhaseAdvancer.scala` | Uses Scala GameState | ✅ **Complete** |
-| `RandomStateSequencer.scala` | Threads Scala GameState | ✅ **Complete** |
-| `VigorXPApplier.scala` | Has both proto and Scala methods | Scala method exists, delete proto method when unused |
-| `PerformForcedTurnBackAction.scala` | Fully protoless | ✅ **Complete** |
-| `ResolveBattleAction.scala` | Heavy proto usage | Blocked by proto dependencies |
-| `InMemoryHistory.scala` | Stores proto results | Pending - vend Scala types |
-| `PersistedHistory.scala` | Stores proto results | Pending - vend Scala types, convert for disk |
-| `GameController.scala` | Uses proto for client communication | Keep proto (gRPC boundary) |
-
-### Remaining Proto Usage in Actions
-
-The following actions still have proto usage, blocked by utility dependencies:
-
-| Action | Proto Usage | Blocker |
-|--------|-------------|---------|
-| `EndBattleAftermathPhaseAction` | 1 `toProto` call | `ProvinceViewFilter` needs Scala types |
-| `NewRoundAction` | 1 `fromProto` call | `ChronicleEventGenerator` returns proto |
-| `EndHandleRiotsPhaseAction` | 1 `toProto` call | `CommandChoiceHelpers` takes proto GameState |
-| `PerformVassalCommandsPhaseAction` | 1 `toProto` call | `CommandChoiceHelpers` takes proto GameState |
-| `PerformVassalDefenseDecisionsAction` | 1 `toProto` call | `CommandChoiceHelpers` takes proto GameState |
-| `EndVassalCommandsPhaseAction` | 1 `toProto` call | `CommandChoiceHelpers` takes proto GameState |
-| `PerformReconResolutionAction` | Uses `ProvinceViewFilter` | `ProvinceViewFilter` needs Scala types |
-| `ResolveBattleAction` | Heavy proto usage | Large refactor needed |
-
-### Estimated Effort (Remaining)
-
-| Component | Lines | Complexity |
-|-----------|-------|------------|
-| `ProvinceViewFilter` to Scala | ~150 | Medium |
-| `CommandChoiceHelpers` to Scala | ~2000 | High |
-| `ChronicleEventGenerator` to Scala | ~400 | Medium |
-| History API updates | ~100 | Low |
-| **Total Remaining** | **~2650** | |
-
-### Validation
- [x] `ActionResultApplier` created and tested
- [x] `RandomStateSequencer` threads Scala GameState throughout
- [x] `RoundPhaseAdvancer` uses T-types internally
- [ ] `ProvinceViewFilter` uses Scala types
- [ ] `CommandChoiceHelpers` uses Scala types
- [ ] History APIs vend Scala types
- [ ] No `ActionResultProtoConverter.toProto()` calls except at persistence/gRPC boundaries
- [ ] All tests pass
-
---
-
-## Phase 7: Clean Up Legacy Utilities
-
-### Objective
-Remove remaining direct proto imports from utility classes.
-
-### Files to Modify
-
-| File | Status |
-|------|--------|
-| `CommandChoiceHelpers.scala` | Accepts proto `GameState`; blocks full deproto of `PerformVassalCommandsPhaseAction` and `PerformVassalDefenseDecisionsAction` |
-| `LegacyProvinceUtils.scala` | Replace with `ProvinceUtils.scala` - `hasImminentRiot` added (PR #4683) |
-| `LegacyFactionUtils.scala` | Replace proto imports with `FactionT` |
-| `LegacyUnaffiliatedHeroUtils.scala` | Replace proto imports with Scala models |
-| `BattalionTypeLoader.scala` | Keep proto for file loading, convert immediately after |
-| `BeastUtils.scala` | **Complete** - now uses Scala `BeastInfo` only |
-
-### View Filters (Blocking Full Deproto)
-
-The `ProvinceViewFilter` utility currently works entirely with proto types, blocking full deproto of actions that generate province views:
-
-| File | Issue | Needed |
-|------|-------|--------|
-| `ProvinceViewFilter.scala` | Takes proto `Province`/`GameState`, returns proto `ProvinceView` | Scala `ProvinceViewT` model |
-| `GameStateViewFilter.scala` | Uses proto types throughout | Depends on `ProvinceViewT` |
-| `GameStateViewDiffer.scala` | Works with view protos | Depends on `ProvinceViewT` |
-
-**Blocked Actions**:
- `EndBattleAftermathPhaseAction` - uses `ProvinceViewFilter` for `revelationChange`, requires lazy proto conversion
- `PerformReconResolutionAction` - uses `ProvinceViewFilter` for reconned provinces
- `GameStateFactionExtensions` - uses `ProvinceViewFilter` for `updatedReconnedProvinces`
-
-**Solution**: Create Scala `ProvinceViewT` (and possibly `ProvinceViewC`) that mirrors the proto `ProvinceView`. Then create a protoless `ProvinceViewFilter` that operates on Scala types. The proto version can delegate to the Scala version + convert, or we maintain both during transition.
-
---
-
-## Phase 8: Verify Boundaries
-
-### Objective
-Confirm protos are used correctly at boundaries — and ONLY there.
-
-### Expected Proto Usage (Keep)
- `EagleServiceImpl.scala` - gRPC boundary
- `InMemoryHistory.scala` / `PersistedHistory.scala` - Persistence boundary
- `*Converter.scala` - Explicit conversion utilities
- `*Loader.scala` - File loading utilities
-
-### Expected No Proto Usage (Verify)
- `/library/actions/impl/` - Pure Scala models
- `/library/util/` - Pure Scala models (except loaders)
- `/model/state/` - Pure Scala models
-
---
-
-## Open Questions
-
-1. **Persistence Format**: Currently game state is persisted as proto. Should we keep proto for persistence (good for schema evolution) or switch to a different format?
-
-2. **Shardok Integration**: `ResolveBattleAction` communicates with Shardok. Should the Shardok interface use protos (external service) or Scala models?
-
-3. **View Generation**: `GameStateViewDiffer` works with view protos for client updates. Views need Scala models (`ProvinceViewT`, etc.) to allow actions like `EndBattleAftermathPhaseAction` to be fully protoless. The Scala views would be converted to proto only at the gRPC boundary when sending updates to clients.
-
---
-
-## Success Criteria
-
-### Code Quality
- [ ] Zero proto imports in `/library/actions/` (except boundaries)
- [ ] Zero proto imports in `/library/` utilities (except loaders)
- [ ] `GameStateT` used throughout engine internals
- [ ] Proto usage limited to: `EagleServiceImpl`, loaders, converters, persistence
-
-### Architecture
- [ ] Clear separation: Scala models (internal) vs Proto (boundaries)
- [ ] Converters as the only bridge between domains
- [ ] No "proto creep" into business logic
@@ -1,205 +0,0 @@
-# Scala 3 Modernization Guide
-
-## Overview
-This document outlines opportunities to modernize the Eagle0 codebase to use Scala 3 best practices and features. The migration to Scala 3 is complete, but the code still uses many Scala 2 patterns that can be improved.
-
-## Modernization Opportunities
-
-### 1. **Convert Sealed Traits to Enums** 🎯 HIGH IMPACT
-**Benefits**: Better performance, more concise syntax, improved exhaustiveness checking
-
-**Current pattern** (`ExternalTextGenerationCaller.scala:23-31`):
-```scala
-sealed trait ExternalTextGenerationError extends Error {
-  def message: String
-}
-case class ExternalTextGenerationRateLimitError(code: Int, message: String)
-    extends ExternalTextGenerationError
-case class ExternalTextGenerationHttpError(code: Int, message: String)
-    extends ExternalTextGenerationError
-case class ExternalTextGenerationTimeoutError(message: String)
-    extends ExternalTextGenerationError
-```
-
-**Scala 3 improvement**:
-```scala
-enum ExternalTextGenerationError extends Error:
-  case RateLimit(code: Int, message: String)
-  case Http(code: Int, message: String) 
-  case Timeout(message: String)
-  
-  def message: String = this match
-    case RateLimit(_, msg) => msg
-    case Http(_, msg) => msg
-    case Timeout(msg) => msg
-```
-
-**Files to check**:
- `/src/main/scala/net/eagle0/common/llm_integration/ExternalTextGenerationCaller.scala`
- `/src/main/scala/net/eagle0/eagle/model/action_result/generated_text_request/GeneratedTextRequestT.scala`
- `/src/main/scala/net/eagle0/eagle/model/state/quest/concrete/QuestC.scala`
-
-### 2. **Convert Implicit Classes to Extension Methods** 🎯 HIGH IMPACT
-**Benefits**: Modern syntax, better IDE support, cleaner imports
-
-**Current pattern** (`MoreSeq.scala:23-26`):
-```scala
-implicit def SeqCollect[A, Repr[_]](coll: Repr[A])(implicit
-    itr: IsIterable[Repr[A]]
-): SeqCollect[A, Repr, itr.type] =
-  new SeqCollect[A, Repr, itr.type](coll, itr)
-```
-
-**Scala 3 improvement**:
-```scala
-extension [A, Repr[_]](coll: Repr[A])(using itr: IsIterable[Repr[A]])
-  def flatCollect[B](pf: PartialFunction[itr.A, Option[B]])(using Factory[B, Repr[B]]): Repr[B] =
-    Factory[B, Repr[B]].fromSpecific(itr(coll).collect(pf).flatten)
-    
-  def flatCollectFirst[B](pf: PartialFunction[itr.A, Option[B]]): Option[B] =
-    itr(coll).collect(pf).flatten.headOption
-```
-
-**Files to check**:
- `/src/main/scala/net/eagle0/common/MoreSeq.scala`
- `/src/main/scala/net/eagle0/eagle/library/util/command_choice_helpers/CommandChooser.scala`
- `/src/main/scala/net/eagle0/eagle/service/new_game_creation/NewGameCreation.scala`
- `/src/main/scala/net/eagle0/eagle/library/actions/applier/ActionResultProtoApplierImpl.scala`
- `/src/main/scala/net/eagle0/eagle/service/new_game_creation/StartGameActionResultUtils.scala`
- `/src/main/scala/net/eagle0/eagle/model/state/date/Date.scala`
-
-### 3. **Convert Implicit Parameters to Using Clauses** 🎯 MEDIUM IMPACT
-**Benefits**: Cleaner syntax, better tooling support, clearer intent
-
-**Current pattern**:
-```scala
-def method[T](value: T)(implicit ec: ExecutionContext): Future[T]
-def process[A](items: Seq[A])(implicit ord: Ordering[A]): Seq[A]
-```
-
-**Scala 3 improvement**:
-```scala
-def method[T](value: T)(using ExecutionContext): Future[T]
-def process[A](items: Seq[A])(using Ordering[A]): Seq[A]
-```
-
-**Files to check**:
- `/src/main/scala/net/eagle0/common/MoreSeq.scala`
- `/src/main/scala/net/eagle0/eagle/library/util/hero_name_fetcher/HeroNameFetcher.scala`
- `/src/main/scala/net/eagle0/eagle/library/util/ShardokMapInfo.scala`
- `/src/main/scala/net/eagle0/common/llm_integration/OpenAIChatCompletionsServiceImpl.scala`
- `/src/main/scala/net/eagle0/common/llm_integration/ClaudeServiceImpl.scala`
-
-### 4. **Opaque Types for Type Safety** 🎯 MEDIUM IMPACT
-**Benefits**: Zero runtime cost, compile-time type safety, prevents mixing up similar types
-
-**Pattern to look for**: Type aliases that represent distinct concepts
-```scala
-// Instead of: type UserId = String, type GameId = String
-opaque type UserId = String
-object UserId:
-  def apply(s: String): UserId = s
-  extension (id: UserId) 
-    def value: String = id
-    def isValid: Boolean = id.nonEmpty && id.length > 3
-
-opaque type GameId = Long  
-object GameId:
-  def apply(l: Long): GameId = l
-  extension (id: GameId) def value: Long = id
-```
-
-**Candidates**: Look for simple type aliases and ID types throughout the codebase.
-
-### 5. **Inline Methods for Performance** 🎯 LOW IMPACT
-**Benefits**: Compile-time optimization, better performance for hot paths
-
-**Pattern**: Mark small, frequently-called methods as `inline`
-```scala
-inline def isValidId(id: String): Boolean = 
-  id.nonEmpty && id.length > 3
-
-inline def calculateScore(base: Int, multiplier: Double): Double = 
-  base * multiplier
-```
-
-**Candidates**: Small utility methods in performance-critical paths (AI calculations, game state updates).
-
-### 6. **Union Types Instead of Complex Hierarchies** 🎯 LOW IMPACT  
-**Benefits**: Simpler type definitions for either/or scenarios
-
-**Pattern**: Simple sealed traits with only case classes
-```scala
-// Instead of:
-sealed trait Result
-case class Success(value: String) extends Result  
-case class Error(message: String) extends Result
-
-// Consider:
-type Result = Success | Error
-case class Success(value: String)
-case class Error(message: String)
-```
-
-### 7. **Context Functions for Cleaner APIs** 🎯 LOW IMPACT
-**Benefits**: Cleaner API design, implicit context passing
-
-**Pattern**: Replace implicit function parameters
-```scala
-// Old
-type Handler = GameState => Unit
-def withGameState(gs: GameState)(handler: Handler): Unit = handler(gs)
-
-// New  
-type Handler = GameState ?=> Unit
-def withGameState(gs: GameState)(handler: Handler): Unit = 
-  given GameState = gs
-  handler
-```
-
-## Implementation Priority
-
-### Phase 1: Quick Wins (High Impact, Low Risk)
-1. **Convert Extension Methods** in `MoreSeq.scala` - immediate readability improvement
-2. **Update Using Clauses** - simple find/replace operation  
-3. **Convert Simple Sealed Traits to Enums** - start with error types
-
-### Phase 2: Type Safety Improvements  
-4. **Add Opaque Types** for IDs and measurements - improves type safety
-5. **Inline Performance-Critical Methods** - measure before/after impact
-
-### Phase 3: Advanced Features (Lower Priority)
-6. **Union Types** where appropriate - only for simple either/or cases
-7. **Context Functions** for complex API improvements
-
-## Implementation Guidelines
-
-### Style Consistency
- **Keep curly braces**: Continue using Scala 2 style `{}` instead of indentation-based syntax
- **Gradual adoption**: Modernize files as they're touched for other reasons
- **Test thoroughly**: Each modernization should include verification that behavior is unchanged
-
-### Performance Considerations  
- **Measure enum performance**: Verify that enum conversion actually improves performance in hot paths
- **Benchmark inline methods**: Use profiling to confirm performance gains
- **Consider compilation time**: Some features may increase compile time
-
-### Migration Strategy
- **File-by-file approach**: Complete modernization of one file at a time
- **Separate PRs**: Each modernization type should be its own PR for easier review
- **Documentation**: Update this document as patterns are modernized
-
-## Success Criteria
- [ ] All extension methods converted from implicit classes
- [ ] All implicit parameters converted to using clauses  
- [ ] Key sealed traits converted to enums where appropriate
- [ ] Opaque types introduced for important ID types
- [ ] Performance-critical methods marked as inline (with benchmarks)
- [ ] No regression in functionality or performance
- [ ] Code remains readable and maintainable
-
-## Notes
- Focus on high-impact, low-risk improvements first
- Each change should be driven by clear benefits (performance, readability, type safety)
- Maintain backward compatibility where possible
- Document any breaking changes clearly
@@ -1,305 +0,0 @@
-# Actions and Commands Model Usage Analysis
-
-This document analyzes all actions and commands in `src/main/scala/net/eagle0/eagle/library/actions/impl` to determine which use Scala models vs protobuf models, based on BUILD.bazel dependencies.
-
-**Legend:**
- ✅ **Scala Models Only** - Uses only `//src/main/scala/net/eagle0/eagle/model` dependencies
- ❌ **Uses Protobuf** - Has dependencies on `//src/main/protobuf` targets
- 🔄 **Partial Conversion** - Conversion attempted but blocked by dependencies
-
-## Summary
-
-Based on BUILD.bazel dependency analysis (2025-09-16, updated 2025-09-17):
- **Total Commands Analyzed:** 41
- **Commands Fully Migrated (No Protobuf):** 41 (100%) ✅
- **Commands Still Using Protobuf:** 0 (0%) ✅
- **Total Actions Analyzed:** 48
- **Actions Fully Migrated (No Protobuf):** 5 (10.4%)
- **Actions Partially Migrated:** 19 (39.6%)
- **Actions Still Using Protobuf:** 24 (50%)
- **Base Classes:** 8 protoless variants available, 6 still use protobuf
- **Shared Components:** `ResolvedEagleUnit` migrated to use `Option[BattalionT]` for proper null handling
-
-## Conversion Insights
-
-Based on conversion attempt of `ResolveTruceOfferCommand` (see [PR #4379](https://github.com/nolen777/eagle0/pull/4379)):
-
-### Key Challenges Discovered
-
-1. **LLM Integration Dependencies**: Commands that use `DiplomacyResolutionLlmRequestGenerator` face challenges because the LLM system still expects protobuf enum types, not Scala model enums.
-
-2. **Inconsistent Package Naming**: Some files have inconsistent package declarations vs BUILD file locations (e.g., `generated_text_request_generators` in package vs `llm_request_generators` in BUILD).
-
-3. **Model Constructor Differences**: Scala model constructors (e.g., `TruceOffer`) have different required parameters than their protobuf counterparts, requiring more complex data mapping.
-
-4. **Type System Complexity**: Union types and type constraints become more complex when mixing protobuf and Scala model types during transition.
-
-5. **Cascading Dependency Issues**: Converting to `ActionResultC` requires extensive trait dependencies (`ChangedBattalionT`, `ChangedHeroT`, `GeneratedTextRequestT`, etc.) that create complex BUILD dependency graphs, unlike simple protobuf `ActionResult`.
-
-6. **BUILD Complexity**: Each Scala model conversion requires significantly more BUILD dependencies than protobuf equivalents, making incremental conversion difficult.
-
-7. **Build Verification Critical**: Any conversion must maintain working build state - even simple commands like `DefendCommand` can break main server build due to dependency cascades.
-### Successful Conversion Elements
-
- ✅ Base class conversion (`SimpleAction` → `ProtolessSimpleAction`)
- ✅ Import updates for most Scala model types
- ✅ BUILD.bazel dependency updates for core action result types
- ✅ Basic type conversions for simple cases
-
-### Recommended Conversion Strategy
-
-1. **Architecture-First Approach**: Convert base infrastructure (LLM generators, action result builders) before individual commands
-2. **Wrapper Pattern**: Use existing `Protoless*ActionWrapper` classes as templates for gradual transition
-3. **Dependency Analysis**: Map full dependency trees before attempting conversions to avoid cascading build failures
-4. **Batch Conversions**: Convert related commands together to minimize dependency conflicts
-5. **Build Verification**: **ALWAYS** verify `//src/main/scala/net/eagle0/eagle:eagle_server` and test suite build before creating PRs
-
-### Conversion Requirements
-
-**Before creating any PR:**
- ✅ `bazel build //src/main/scala/net/eagle0/eagle:eagle_server` succeeds
- ✅ `bazel test //src/test/scala/... --keep_going` passes (or doesn't introduce new failures)
- ✅ All BUILD dependencies are correctly specified
- ✅ Scalafmt and other linters pass
-
---
-
-## Common Base Classes
-
-| File | Type | Model Usage | Notes |
-|------|------|-------------|-------|
-| Action.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| ActionWithResultingState.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| DeterministicSingleResultAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| DeterministicSequentialResultsAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| ProtolessRandomSequentialResultsAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| ProtolessRandomSimpleAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| ProtolessSequentialResultsAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| ProtolessSimpleAction.scala | Base Class | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model/action_result` |
-| RandomSequentialResultsAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto`, `game_state_scala_proto` |
-| RandomSimpleAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto` |
-| RandomStateProtoSequencer.scala | Sequencer | ❌ Uses Protobuf | Bridge class, depends on both protobuf and Scala models |
-| RandomStateTSequencer.scala | Sequencer | ❌ Uses Protobuf | Bridge class, depends on both protobuf and Scala models |
-| SimpleAction.scala | Base Class | ❌ Uses Protobuf | Depends on `action_result_scala_proto` |
-| VigorXPApplier.scala | Utility | ❌ Uses Protobuf | Depends on `action_result_scala_proto` |
-
---
-
-## Actions
-
-### ✅ Fully Migrated Actions (No Protobuf Dependencies)
-
-These actions have been successfully migrated to use Scala models only:
-
-| File | Base Class | Notes |
-|------|------------|-------|
-| HeroBackstoryUpdateAction.scala | ProtolessSequentialResultsAction | Processes hero backstory updates with LLM integration |
-| ProvinceConqueredAction.scala | ProtolessSimpleAction | Uses component-based design (gameId, currentRoundId, currentDate, Scala models) |
-| ProvinceHeldAction.scala | ProtolessSimpleAction | Uses specific components (gameId, currentRoundId, defendingProvince, etc.) instead of full GameState |
-| UnaffiliatedHeroAppearedAction.scala | ProtolessSimpleAction | Handles unaffiliated hero appearance with name generation |
-| WithdrawnArmiesReturnHomeAction.scala | ProtolessSequentialResultsAction | Manages army withdrawal and return mechanics |
-
-### 🔄 Actions Partially Migrated (Using Protoless Base Classes)
-
-These actions use protoless base classes but still have some protobuf dependencies:
-
-| File | Model Usage | Notes |
-|------|-------------|-------|
-| CheckForFactionChangesAction.scala | ProtolessSequentialResultsAction | Still has some protobuf dependencies |
-| CheckForFailedQuestsAction.scala | ProtolessSequentialResultsAction | Depends on `unaffiliated_hero_quest_scala_proto` |
-| CheckForFulfilledQuestsAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndAttackDecisionPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndBattleAftermathPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndFreeForAllDecisionPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndPlayerCommandsPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndUnaffiliatedHeroActionsPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| EndVassalCommandsPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| FreeForAllDrawAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| FriendlyMoveAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| PerformUncontestedConquestAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| ProvinceConqueredAction.scala | ProtolessSimpleAction | **CONVERTED** - Uses specific components (gameId, currentRoundId, currentDate, Scala models) |
-| SafePassageArmiesProceedAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| ShipmentArrivedAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| TruceTurnBackPhaseAction.scala | ProtolessSequentialResultsAction | Depends on multiple protobuf targets |
-| UnaffiliatedHeroRejoinedAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-| WonFreeForAllAction.scala | ProtolessSimpleAction | Depends on multiple protobuf targets |
-
-### ❌ Actions Still Using Protobuf (Not Yet Using Protoless Base Classes)
-
-| File | Notes |
-|------|-------|
-| ChronicleEventGenerator.scala | Depends on multiple protobuf targets |
-| EndBattleRequestPhaseAction.scala | Depends on `diplomacy_offer_status_scala_proto` |
-| EndBattleResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndDefenseDecisionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndDiplomacyResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndFreeForAllBattleRequestPhaseAction.scala | Depends on multiple protobuf targets |
-| EndFreeForAllBattleResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| EndHandleRiotsPhaseAction.scala | Depends on multiple protobuf targets |
-| EndPleaseRecruitMePhaseAction.scala | Depends on multiple protobuf targets |
-| EndProvinceMoveResolutionPhaseAction.scala | Depends on multiple protobuf targets |
-| NewRoundAction.scala | Depends on multiple protobuf targets |
-| NewYearAction.scala | Depends on multiple protobuf targets |
-| PerformFoodConsumptionPhaseAction.scala | Depends on multiple protobuf targets |
-| PerformForcedTurnBackAction.scala | Depends on multiple protobuf targets |
-| PerformHeroDeparturesAction.scala | Depends on multiple protobuf targets |
-| PerformHostileArmySetupAction.scala | Depends on multiple protobuf targets |
-| PerformProvinceEventsAction.scala | Depends on `province_event_scala_proto` |
-| PerformProvinceMoveResolutionAction.scala | Depends on multiple protobuf targets |
-| PerformReconResolutionAction.scala | Depends on multiple protobuf targets |
-| PerformUnaffiliatedHeroesAction.scala | Depends on `unaffiliated_hero_quest_scala_proto` |
-| PerformVassalCommandsPhaseAction.scala | Depends on multiple protobuf targets |
-| PerformVassalDefenseDecisionsAction.scala | Depends on multiple protobuf targets |
-| PrisonerEscapeAction.scala | Depends on `game_state_scala_proto` |
-| PrisonerExchangeAction.scala | Depends on multiple protobuf targets |
-| RequestBattlesAction.scala | Depends on multiple protobuf targets |
-| RequestFreeForAllBattlesAction.scala | Depends on multiple protobuf targets |
-| ResolveBattleAction.scala | Depends on `shardok_internal_interface_scala_grpc` |
-| UnaffiliatedHeroMovedAction.scala | Depends on multiple protobuf targets |
-| UnaffiliatedHeroesChangedAction.scala | Depends on multiple protobuf targets |
-
---
-
-## Commands
-
-✅ **ALL COMMANDS FULLY MIGRATED** (100% - 41/41 commands)
-
-All 41 commands in the codebase have been successfully migrated to use Scala models only, with no protobuf dependencies. This includes:
-
- **Simple Actions**: Use `ProtolessSimpleAction` base class
- **Random Actions**: Use `ProtolessRandomSimpleAction` base class
- **Complex Domain Models**: Successfully integrated with LLM systems, diplomacy, quest fulfillment, and state management
- **Complete Type Safety**: All commands now use type-safe Scala domain models
-
-**Key Migration Achievements:**
- ✅ All military commands (ArmTroops, Train, Organize, etc.)
- ✅ All diplomacy commands (Resolve Alliance/Truce/Ransom offers, etc.)
- ✅ All LLM-integrated commands (backstory generation, diplomacy resolution)
- ✅ All quest and event commands
- ✅ Final remaining command (FreeForAllDecisionCommand) migrated
-
---
-
-## Diplomacy Helpers
-
-All diplomacy helpers use **Scala models only**:
-
-| File | Model Usage | Notes |
-|------|-------------|-------|
-| AllianceResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| BreakAllianceResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| InvitationResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| RansomResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-| TruceResolutionHelpers.scala | ✅ Scala Models Only | Uses `//src/main/scala/net/eagle0/eagle/model` only |
-
---
-
-## Migration Priority Analysis
-
-Based on the BUILD.bazel dependency analysis, here are the key findings and recommendations:
-
-### 🎯 High Impact Migration Targets
-
-**Core Dependencies Blocking Multiple Commands:**
-
-1. **`action_result_scala_proto`** - Used by 12+ commands
-   - Blocks: `DefendCommand`, `FreeForAllDecisionCommand`, diplomacy resolvers
-   - Impact: Would unlock many command migrations
-
-2. **`available_command_scala_proto` / `selected_command_scala_proto`** - Used by 10+ commands
-   - Blocks: All UI-interactive commands
-   - Impact: Would enable client-server interaction model migration
-
-3. **`game_state_scala_proto`** - Used by 8+ commands
-   - Blocks: Complex state-dependent commands
-   - Impact: Core state representation migration
-
-### 📊 Migration Tiers by Complexity
-
-**Tier 1 - Quick Wins (2 commands):**
- `ArmTroopsCommand` - Only `battalion_type` dependency
- `TrainCommand` - Only `battalion_type` dependency
- **Effort:** Low, **Impact:** Demonstrates battalion model usage
-
-**Tier 2 - API Layer (5 commands):**
- Commands blocked by `available_command`/`selected_command`
- **Effort:** Medium, **Impact:** High (enables UI interaction models)
-
-**Tier 3 - Diplomacy Suite (6 commands):**
- All `Resolve*Command` diplomacy commands
- **Effort:** High, **Impact:** High (complete diplomacy model migration)
- **Strategy:** Migrate as a group after diplomacy models are ready
-
-### 🏆 Success Metrics
-
-**Current Status:**
- ✅ **100% of commands fully migrated** (41/41) 🎉
- ✅ **All diplomacy helpers use Scala models**
- ✅ **All protoless base classes available**
- ✅ **ALL command migration completed**
-
-**Completed Milestones:**
- ✅ **70% target:** Migrate Tier 1 + some Tier 2 commands **COMPLETED**
- ✅ **80% target:** Continue with remaining non-diplomacy commands **COMPLETED**
- ✅ **85% target:** Complete API layer migration **COMPLETED**
- ✅ **95% target:** Complete diplomacy migration **COMPLETED**
- ✅ **100% target:** Migrate final remaining command (FreeForAllDecisionCommand) **COMPLETED**
-
-### 🎯 Action Migration Progress
-
-**Migration Statistics:**
- 5/48 Actions fully migrated (10.4%)
- 20/48 Actions using protoless base classes but with protobuf dependencies (41.7%)
- 24/48 Actions still fully on protobuf (50%)
-
-**Successfully Migrated Actions:**
-1. **HeroBackstoryUpdateAction** - LLM integration for hero backstories
-2. **ProvinceConqueredAction** - Component-based design with prisoner handling and province conquest
-3. **ProvinceHeldAction** - Component-based design pattern (gameId, currentRoundId, specific models)
-4. **UnaffiliatedHeroAppearedAction** - Hero appearance with name generation
-5. **WithdrawnArmiesReturnHomeAction** - Army withdrawal mechanics
-
-**Recent Migration Updates (2025-09-17):**
- **ResolvedEagleUnit** - Changed `battalion: BattalionT` to `battalion: Option[BattalionT]`
-  - Properly handles units without battalions (battalion ID -1)
-  - Updated `ShardokInterfaceGrpcClient` to check for `defaultBattalionId` and use `None`
-  - Updated `ResolveBattleAction`, `ProvinceConqueredAction`, `RequestBattlesAction`
-  - All tests updated to handle optional battalions
-
-**Key Migration Patterns:**
- ✅ Use specific components instead of full GameState (see ProvinceHeldAction, ProvinceConqueredAction)
- ✅ Convert protobuf models to Scala models at Action boundaries
- ✅ Update BUILD.bazel to remove protobuf dependencies
- ✅ Update all call sites and tests
- ✅ Use `Option[T]` for optional fields instead of special sentinel values (e.g., battalion ID -1)
-
-**Next Migration Candidates (Simple Actions with Protoless Base):**
-1. **FreeForAllDrawAction** - Already uses ProtolessSimpleAction
-2. **FriendlyMoveAction** - Already uses ProtolessSimpleAction
-3. **ShipmentArrivedAction** - Already uses ProtolessSimpleAction
-4. **WonFreeForAllAction** - Already uses ProtolessSimpleAction
-5. **ProvinceConqueredAction** - Already uses ProtolessSimpleAction, only needs `common_unit` migration
-
-### 🔄 Conversion Strategy Updates
-
-**Revised Approach Based on Analysis:**
-
-1. **Focus on Core Dependencies First**
-   - Migrate `battalion_type` model (unlocks 2 commands immediately)
-   - Migrate `action_result` model (unlocks 12+ commands)
-   - Migrate `available_command`/`selected_command` (unlocks UI layer)
-
-2. **Leverage Existing Success**
-   - 77.5% of commands already fully migrated
-   - Use migrated commands as reference implementations
-   - Diplomacy helpers prove complex business logic can work with Scala models
-
-3. **Group Related Migrations**
-   - Military commands: `ArmTroopsCommand`, `TrainCommand`, `OrganizeTroopsCommand`
-   - UI commands: All using `available_command`/`selected_command`
-   - Diplomacy commands: All `Resolve*Command` variants
-
---
-
-*Updated on 2025-09-17 - Analysis based on BUILD.bazel dependencies and code review*
-*Latest update: ResolvedEagleUnit migrated to use Option[BattalionT] for proper battalion handling*
@@ -1,310 +0,0 @@
-# Scala 3 Migration: Reflection Issues Found
-
-This document catalogs all reflection-related problems discovered during the Scala 2.13.16 → Scala 3.7.2 migration of the Eagle0 codebase.
-
-## Summary
-
-The migration revealed several categories of reflection issues that needed to be addressed for Scala 3 compatibility:
-
-1. **Scala 2 Runtime Reflection API** - No longer available in Scala 3
-2. **Settings System Reflection** - Custom reflection for loading settings singletons 
-3. **json4s Automatic Case Class Extraction** - Uses reflection that fails with Scala 3 metaprogramming classes
-4. **ScalaTest Exception Handling** - Syntax changes affecting exception variable binding
-
-## 1. Scala 2 Runtime Reflection (FIXED)
-
-### Issue
-Tests using `scala.reflect.runtime.universe` fail because this reflection API doesn't exist in Scala 3.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/test/scala/net/eagle0/eagle/library/actions/types/ActionResultTypesTest.scala`
-
-### Error
-```scala
-import scala.reflect.runtime.universe  // Not available in Scala 3
-```
-
-### Solution Applied
-**Deleted the test entirely** as it was redundant. The test was verifying that auto-generated Scala objects (created by Bazel from proto enum values) matched their source proto values - something already guaranteed by the build system. Since the objects are generated directly from the proto definitions, this test provided no value.
-
-**Files deleted:**
- `src/test/scala/net/eagle0/eagle/library/actions/types/ActionResultTypesTest.scala`
-
-## 2. Settings System Reflection (FIXED)
-
-### Issue
-Custom `SettingsLoader` class used reflection to access Scala object singletons, but the reflection pattern changed between Scala 2 and Scala 3.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/library/settings/loaders/SettingsLoader.scala`
-
-### Error
-```
-java.lang.NoSuchMethodException: net.eagle0.eagle.library.settings.ApprehendOutlawVigorCost$.MODULE$
-```
-
-### Root Cause
-In Scala 2, singleton objects are accessed via `ClassName$.MODULE$()`, but in Scala 3, they're accessed directly via `ClassName$` field. Additionally, `scala.reflect.runtime.universe` is not available in Scala 3.
-
-### Solution Applied
-**Completely eliminated reflection** by auto-generating the entire `SettingsLoader.scala` file from BUILD.bazel definitions:
-
-1. **Created generator**: `src/main/go/net/eagle0/build/settings_loader_generator/settings_loader_generator.go` - parses BUILD.bazel and generates complete SettingsLoader.scala with pattern matching for all 272 settings
-
-2. **Added genrule**: In `src/main/scala/net/eagle0/eagle/library/settings/loaders/BUILD.bazel`:
-```python
-genrule(
-    name = "settings_loader_src",
-    srcs = ["//src/main/scala/net/eagle0/eagle/library/settings:BUILD.bazel"],
-    outs = ["SettingsLoader.scala"],
-    cmd = "$(location //src/main/go/net/eagle0/build/settings_loader_generator) $(location //src/main/scala/net/eagle0/eagle/library/settings:BUILD.bazel) > $@",
-    tools = ["//src/main/go/net/eagle0/build/settings_loader_generator"],
-)
-```
-
-3. **Result**: SettingsLoader now uses compile-time pattern matching instead of reflection:
-```scala
-private def settingObjectForKey(key: String): Any = key match {
-  case "ActionVigorCost" => ActionVigorCost
-  case "BaseFoodBuyPrice" => BaseFoodBuyPrice
-  // ... all 272 settings auto-generated
-  case _ => throw NoSuchSettingException(key)
-}
-```
-
-### Benefits
- **No reflection** - Completely Scala 3 compatible
- **Maintainable** - New settings automatically included when added to BUILD.bazel
- **Performance** - Pattern matching is faster than reflection
- **Type-safe** - Compile-time checking of all settings
-
-## 3. json4s Reflection Issues (MULTIPLE LOCATIONS)
-
-### 3.1 EagleServiceImpl JSON Serialization (FIXED)
-
-#### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/service/EagleServiceImpl.scala`
-
-#### Error
-```
-java.lang.NoClassDefFoundError: scala/quoted/staging/package$
-```
-
-#### Root Cause
-json4s automatic case class serialization uses reflection that tries to access Scala 3 metaprogramming classes (`scala.quoted.staging.package$`) which aren't available at runtime.
-
-#### Solution Applied
-Replaced automatic json4s serialization with ScalaPB's built-in JSON support:
-
-```scala
-// Old (reflection-based):
-// implicit val formats: DefaultFormats.type = DefaultFormats
-// write(actionResultView)
-
-// New (ScalaPB JSON support):
-import scalapb.json4s.JsonFormat
-JsonFormat.toJsonString(actionResultView.toProto)
-```
-
-### 3.2 ShardokMapInfo JSON Parsing (FIXED)
-
-#### Files Affected  
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/library/util/ShardokMapInfo.scala` (Line 44)
-
-#### Error
-```
-java.lang.NoClassDefFoundError: scala/quoted/staging/package$
-at org.json4s.reflect.ScalaSigReader$.readConstructor(ScalaSigReader.scala:42)
-```
-
-#### Root Cause
-The line `val extracted = parsedJson.extract[List[ShardokMapInfo]]` uses json4s automatic case class extraction which relies on reflection.
-
-#### Solution Applied
-Replaced automatic extraction with manual JSON parsing:
-
-```scala
-// OLD (reflection-based):
-val extracted = parsedJson.extract[List[ShardokMapInfo]]
-
-// NEW (manual parsing, no reflection):
-val extracted = parsedJson match {
-  case JArray(items) => items.map { item =>
-    val name = (item \ "name").extract[String]
-    val castleCount = (item \ "castleCount").extract[Int] 
-    val positions = (item \ "positions").extract[Map[Int, Int]]
-    ShardokMapInfo(name, castleCount, positions)
-  }
-  case _ => throw new Exception("Expected JSON array for map info")
-}
-```
-
-#### Testing
-The fix was verified - `attack_command_chooser_test` now passes successfully.
-
-### 3.3 HeroNameFetcher JSON Parsing (FIXED)
-
-#### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/main/scala/net/eagle0/eagle/library/util/hero_name_fetcher/HeroNameFetcher.scala`
-
-#### Issue  
-Case class extraction `parsedJson.extract[ResponseBody]` uses reflection that may fail in Scala 3.
-
-#### Solution Applied
-Replaced automatic case class extraction with manual JSON parsing:
-
-```scala
-// OLD (reflection-based):
-val parsedJson = json.parse(src.getLines().mkString)
-parsedJson.extract[ResponseBody]
-
-// NEW (manual parsing, no reflection):
-parsedJson \ "names" match {
-  case JArray(nameArray) => 
-    nameArray.map { nameObj =>
-      val id = (nameObj \ "id").extract[String]
-      val name = (nameObj \ "name").extract[String]
-      NameResponse(id, name)
-    }.toVector
-  case _ => throw new Exception("Expected 'names' array in response")
-}
-```
-
-#### Testing
-The fix was verified - HeroNameFetcher now builds successfully without reflection.
-
-### 3.4 Other json4s Usage Analysis
-
-#### Files with json4s extraction:
- **✅ SAFE**: OpenAI/Claude Services - Only extract simple types (`String`, `Int`) - no reflection
- **✅ FIXED**: `HeroNameFetcher.scala` - Replaced `extract[ResponseBody]` with manual parsing (no reflection)
- **⚠️ POTENTIAL ISSUES** (not currently causing failures but should be monitored):
-  - `JsonUtils.scala`: `extract[Map[String, Vector[String]]]` - complex type extraction
-  - `HexMapJsonUtils.scala`: `extract[List[JObject]]` - may be problematic
-
-#### Recommendation
-Apply the same manual parsing pattern to remaining case class extractions if they cause runtime failures during Scala 3 migration.
-
-## 4. ScalaTest Exception Handling Syntax (FIXED)
-
-### Issue
-Scala 3 changed how exception variables are bound in ScalaTest's `the[Exception] thrownBy {...}` construct.
-
-### Files Affected
-**70+ test files** across the codebase using exception testing patterns.
-
-### Error Pattern
-```
-Not found: ex
-```
-
-### Root Cause
-In Scala 2: `the[Exception] thrownBy { ... }` automatically creates an `ex` variable.
-In Scala 3: The exception variable must be explicitly bound.
-
-### Solution Applied
-Added explicit variable binding across all affected test files:
-
-```scala
-// Old Scala 2 syntax:
-the[EagleCommandException] thrownBy {
-  // test code
-}
-ex.getMessage shouldBe "expected message"
-
-// New Scala 3 syntax:
-val ex = the[EagleCommandException] thrownBy {
-  // test code  
-}
-ex.getMessage shouldBe "expected message"
-```
-
-### Script Used
-Created and ran a systematic fix script that processed 70+ files:
-
-```bash
-# Pattern to find and fix exception handling
-find . -name "*.scala" -exec sed -i '' 's/the\[\([^]]*\)\] thrownBy {/val ex = the[\1] thrownBy {/g' {} \;
-```
-
-## 5. ScalaTest Import Changes (FIXED)
-
-### Issue
-Scala 3 requires different imports for ScalaTest matchers.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/test/scala/net/eagle0/eagle/library/actions/impl/command/DeclineQuestCommandTest.scala`
-
-### Error
-```
-value convertToAnyShouldWrapper is not a member of object org.scalatest.matchers.should.Matchers
-```
-
-### Solution Applied
-Changed from specific imports to wildcard import:
-
-```scala
-// Old:
-import org.scalatest.matchers.should.Matchers.{convertToAnyShouldWrapper, the}
-
-// New:
-import org.scalatest.matchers.should.Matchers.*
-```
-
-## 6. Mock Framework Issues (FIXED)
-
-### Issue
-ScalaMock had type inference issues with Scala 3 for classes with constructor parameters.
-
-### Files Affected
- `/Users/dancrosby/CodingProjects/github/eagle0/src/test/scala/net/eagle0/eagle/library/EngineImplTest.scala`
-
-### Error
-```
-Found: Vector
-Required: Vector[net.eagle0.eagle.library.util.hero_generator.hero_with_name.HeroWithName]
-```
-
-### Root Cause
-Mock framework couldn't properly infer types for `mock[HeroGenerator]` where `HeroGenerator` has constructor parameters.
-
-### Solution Applied
-The user updated to a newer ScalaMock version that fixed this issue, plus added some missing Bazel dependencies:
-
-```scala
-// Also needed to add missing dependency:
-"//src/main/scala/net/eagle0/eagle/shardok_interface:battle_resolution"
-```
-
-## Migration Status
-
-### ✅ COMPLETED
- [x] Scala 2 runtime reflection removal
- [x] Settings system reflection compatibility  
- [x] EagleServiceImpl json4s → ScalaPB JSON
- [x] ScalaTest exception handling syntax (70+ files)
- [x] ScalaTest import changes
- [x] Mock framework issues (via ScalaMock update)
- [x] All test compilation issues resolved
-
-### ⚠️ REMAINING
- [ ] **Potential json4s case class extractions** - May cause runtime failures (JsonUtils, HexMapJsonUtils) - currently no test failures reported
-
-### 📊 PROGRESS
- **Tests passing**: All identified runtime failures resolved
- **Build failures**: 0 (all tests now compile)
- **Runtime failures**: 0 (critical ShardokMapInfo issue resolved)
-
-## Recommendations
-
-1. **✅ COMPLETED**: ShardokMapInfo json4s reflection issue resolved with manual parsing
-2. **Monitor remaining json4s usage**: Watch for runtime failures in HeroNameFetcher, JsonUtils, and HexMapJsonUtils during full Scala 3 migration
-3. **Consider ScalaPB for new JSON needs**: For new functionality, prefer ScalaPB's JSON support to avoid reflection entirely
-4. **Apply manual parsing pattern**: If other json4s case class extractions cause runtime failures, use the same manual parsing approach demonstrated in ShardokMapInfo
-
-## Key Learnings
-
- **Scala 3 reflection changes**: Major differences in singleton object access patterns
- **json4s compatibility**: Automatic case class extraction doesn't work well with Scala 3 metaprogramming
- **ScalaPB advantage**: Using ScalaPB's JSON support avoids reflection issues entirely
- **Systematic approach**: Many issues followed patterns that could be fixed with scripts across multiple files
@@ -9,7 +9,6 @@ require (
 	github.com/aws/aws-sdk-go-v2/config v1.28.10
 	github.com/aws/aws-sdk-go-v2/credentials v1.17.51
 	github.com/aws/aws-sdk-go-v2/service/s3 v1.72.2
-	google.golang.org/grpc v1.68.0
 	google.golang.org/protobuf v1.36.3
 )

@@ -40,8 +40,6 @@ github.com/google/go-cmp v0.5.5/go.mod h1:v8dTdLbMG2kIc/vJvl+f65V22dbkXbowE6jgT/
 golang.org/x/text v0.25.0 h1:qVyWApTSYLk/drJRO5mDlNYskwQznZmkpV2c8q9zls4=
 golang.org/x/text v0.25.0/go.mod h1:WEdwpYrmk1qmdHvhkSTNPm3app7v4rsT8F2UD6+VHIA=
 golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0=
-google.golang.org/grpc v1.68.0 h1:aHQeeJbo8zAkAa3pRzrVjZlbz6uSfeOXlJNQM0RAbz0=
-google.golang.org/grpc v1.68.0/go.mod h1:fmSPC5AsjSBCK54MyHRx48kpOti1/jRfOlwEWywNjWA=
 google.golang.org/protobuf v1.26.0-rc.1 h1:7QnIQpGRHE5RnLKnESfDoxm2dTapTZua5a0kS0A+VXQ=
 google.golang.org/protobuf v1.26.0-rc.1/go.mod h1:jlhhOSvTdKEhbULTjvd4ARK9grFBp09yW+WbY/TyQbw=
 google.golang.org/protobuf v1.36.3 h1:82DV7MYdb8anAVi3qge1wSnMDrnKK7ebr+I0hHRN1BU=
@@ -1,10 +1,9 @@
 {
  "__AUTOGENERATED_FILE_DO_NOT_MODIFY_THIS_FILE_MANUALLY": "THERE_IS_NO_DATA_ONLY_ZUUL",
-  "__INPUT_ARTIFACTS_HASH": 289080209,
-  "__RESOLVED_ARTIFACTS_HASH": -131178107,
+  "__INPUT_ARTIFACTS_HASH": 644967262,
+  "__RESOLVED_ARTIFACTS_HASH": -595552834,
  "conflict_resolution": {
    "com.google.guava:failureaccess:1.0.1": "com.google.guava:failureaccess:1.0.2",
-    "com.squareup.okio:okio:2.10.0": "com.squareup.okio:okio:3.6.0",
    "io.netty:netty-buffer:4.1.110.Final": "io.netty:netty-buffer:4.1.112.Final",
    "io.netty:netty-codec-http2:4.1.110.Final": "io.netty:netty-codec-http2:4.1.112.Final",
    "io.netty:netty-codec-http:4.1.110.Final": "io.netty:netty-codec-http:4.1.112.Final",
@@ -15,7 +14,8 @@
    "io.netty:netty-transport-native-unix-common:4.1.110.Final": "io.netty:netty-transport-native-unix-common:4.1.112.Final",
    "io.netty:netty-transport:4.1.110.Final": "io.netty:netty-transport:4.1.112.Final",
    "io.opencensus:opencensus-api:0.31.0": "io.opencensus:opencensus-api:0.31.1",
-    "org.checkerframework:checker-qual:3.12.0": "org.checkerframework:checker-qual:3.43.0"
+    "org.checkerframework:checker-qual:3.12.0": "org.checkerframework:checker-qual:3.43.0",
+    "org.scala-lang:scala-library:2.13.14": "org.scala-lang:scala-library:2.13.15"
  },
  "artifacts": {
    "com.amazonaws:aws-lambda-java-core": {
@@ -156,18 +156,6 @@
      },
      "version": "1.4.2"
    },
-    "com.squareup.okhttp3:okhttp": {
-      "shasums": {
-        "jar": "b1050081b14bb7a3a7e55a4d3ef01b5dcfabc453b4573a4fc019767191d5f4e0"
-      },
-      "version": "4.12.0"
-    },
-    "com.squareup.okhttp3:okhttp-sse": {
-      "shasums": {
-        "jar": "bff4fbcaef7aac2d910d4ff46dafaa4e6d15da127df6bac97216da46943a7d4c"
-      },
-      "version": "4.12.0"
-    },
    "com.squareup.okhttp:okhttp": {
      "shasums": {
        "jar": "88ac9fd1bb51f82bcc664cc1eb9c225c90dc4389d660231b4cc737bebfe7d0aa"
@@ -176,39 +164,27 @@
    },
    "com.squareup.okio:okio": {
      "shasums": {
-        "jar": "8e63292e5c53bb93c4a6b0c213e79f15990fed250c1340f1c343880e1c9c39b5"
+        "jar": "a27f091d34aa452e37227e2cfa85809f29012a8ef2501a9b5a125a978e4fcbc1"
      },
-      "version": "3.6.0"
+      "version": "2.10.0"
    },
-    "com.squareup.okio:okio-jvm": {
+    "com.thesamet.scalapb:compilerplugin_2.13": {
      "shasums": {
-        "jar": "67543f0736fc422ae927ed0e504b98bc5e269fda0d3500579337cb713da28412"
-      },
-      "version": "3.6.0"
-    },
-    "com.thesamet.scalapb:compilerplugin_3": {
-      "shasums": {
-        "jar": "e7d7156269fc23cbb539eea60f07c3230aa05a726434fc942b040495567f0a2d"
+        "jar": "218640423ba8156f994d6d700ef960d65025f79a5918070c0898213f4384df1f"
      },
      "version": "1.0.0-alpha.1"
    },
-    "com.thesamet.scalapb:lenses_3": {
+    "com.thesamet.scalapb:lenses_2.13": {
      "shasums": {
-        "jar": "63fdffc573947402c526c49cf6ee92990ede88d55eb56af5123dfd247b365185"
+        "jar": "46902feb0fd848fce92e234514254dc43b3cde5f6e10e88ae6eec52f4c016fbc"
      },
      "version": "1.0.0-alpha.1"
    },
    "com.thesamet.scalapb:protoc-bridge_2.13": {
      "shasums": {
-        "jar": "403f0e7223c8fd052cff0fbf977f3696c387a696a3a12d7b031d95660c7552f5"
+        "jar": "0b3827da2cd9bca867d6963c2a821e7eaff41f5ac3babf671c4c00408bd14a9b"
      },
-      "version": "0.9.7"
-    },
-    "com.thesamet.scalapb:protoc-bridge_3": {
-      "shasums": {
-        "jar": "e7e2f1862f54076b6870bd034a7c16aae7b88cfee3d00b69dbb6b1175108560c"
-      },
-      "version": "0.9.9"
+      "version": "0.9.8"
    },
    "com.thesamet.scalapb:protoc-gen_2.13": {
      "shasums": {
@@ -216,24 +192,30 @@
      },
      "version": "0.9.7"
    },
-    "com.thesamet.scalapb:scalapb-json4s_3": {
+    "com.thesamet.scalapb:scalapb-json4s_2.13": {
      "shasums": {
-        "jar": "deed5b6ebf5e9bf676e629036ea60182d68b747c775ca5f0222211fcca697e14"
+        "jar": "16b1983d09091e1227de69a999285c02818b8d0639a0520de511d11a3e6fb1cd"
      },
      "version": "1.0.0-alpha.1"
    },
-    "com.thesamet.scalapb:scalapb-runtime-grpc_3": {
+    "com.thesamet.scalapb:scalapb-runtime-grpc_2.13": {
      "shasums": {
-        "jar": "0c8574f91693cb08795ed16a601bcf6d5ba46ba8dbd71792910b706cce995c7a"
+        "jar": "75eb71fea9509308070812b8bcf1eec90c065be3e9d8c60b12098f206db6c581"
      },
      "version": "1.0.0-alpha.1"
    },
-    "com.thesamet.scalapb:scalapb-runtime_3": {
+    "com.thesamet.scalapb:scalapb-runtime_2.13": {
      "shasums": {
-        "jar": "37ec7d72d56f58e3adb78e385e39ecb927a5097e290f4e51332bbd55fc534a65"
+        "jar": "0ceaaf48bc3fa41419fcb8830d21685aea8b7a5e403b90b3246124d9f4b6d087"
      },
      "version": "1.0.0-alpha.1"
    },
+    "com.thoughtworks.paranamer:paranamer": {
+      "shasums": {
+        "jar": "688cb118a6021d819138e855208c956031688be4b47a24bb615becc63acedf07"
+      },
+      "version": "2.8"
+    },
    "commons-codec:commons-codec": {
      "shasums": {
        "jar": "f9f6cb103f2ddc3c99a9d80ada2ae7bf0685111fd6bffccb72033d1da4e6ff23"
@@ -463,27 +445,15 @@
    },
    "org.jetbrains.kotlin:kotlin-stdlib": {
      "shasums": {
-        "jar": "55e989c512b80907799f854309f3bc7782c5b3d13932442d0379d5c472711504"
+        "jar": "b8ab1da5cdc89cb084d41e1f28f20a42bd431538642a5741c52bbfae3fa3e656"
      },
-      "version": "1.9.10"
+      "version": "1.4.20"
    },
    "org.jetbrains.kotlin:kotlin-stdlib-common": {
      "shasums": {
-        "jar": "cde3341ba18a2ba262b0b7cf6c55b20c90e8d434e42c9a13e6a3f770db965a88"
+        "jar": "a7112c9b3cefee418286c9c9372f7af992bd1e6e030691d52f60cb36dbec8320"
      },
-      "version": "1.9.10"
-    },
-    "org.jetbrains.kotlin:kotlin-stdlib-jdk7": {
-      "shasums": {
-        "jar": "ac6361bf9ad1ed382c2103d9712c47cdec166232b4903ed596e8876b0681c9b7"
-      },
-      "version": "1.9.10"
-    },
-    "org.jetbrains.kotlin:kotlin-stdlib-jdk8": {
-      "shasums": {
-        "jar": "a4c74d94d64ce1abe53760fe0389dd941f6fc558d0dab35e47c085a11ec80f28"
-      },
-      "version": "1.9.10"
+      "version": "1.4.20"
    },
    "org.jetbrains:annotations": {
      "shasums": {
@@ -491,35 +461,41 @@
      },
      "version": "13.0"
    },
-    "org.json4s:json4s-ast_3": {
+    "org.json4s:json4s-ast_2.13": {
      "shasums": {
-        "jar": "d899bf87f5a9b0ce73f2dcde2029a1e18b6c5557abd08ee45d26845c3d22a583"
-      },
-      "version": "4.1.0-M8"
-    },
-    "org.json4s:json4s-core_3": {
-      "shasums": {
-        "jar": "ecf2ca8c4a27b6e61eca45f12d8840bacc5f2e38b89dfa7c9694b4e889aa4e3d"
-      },
-      "version": "4.1.0-M8"
-    },
-    "org.json4s:json4s-jackson-core_3": {
-      "shasums": {
-        "jar": "aeb0034d1f7eb854b56a672b7dc97c2a96b8109d8dbc8d3128faeca04274fbd3"
+        "jar": "3135eceb95b679ea228e3543267d12bea5f4bdb68e3e8fc55402824d85885e7e"
      },
      "version": "4.0.7"
    },
-    "org.json4s:json4s-native-core_3": {
+    "org.json4s:json4s-core_2.13": {
      "shasums": {
-        "jar": "f5565d5cefed6fdfcbefcf3e5a8e22b2d0455538446af151ac90bc110442c00c"
+        "jar": "e831e4a676964d3f38a408b464b3ba6d21b76730c01f13d2d0b9995945fa06ce"
      },
-      "version": "4.1.0-M8"
+      "version": "4.0.7"
    },
-    "org.json4s:json4s-native_3": {
+    "org.json4s:json4s-jackson-core_2.13": {
      "shasums": {
-        "jar": "cf95bc65afb8230d255fa00c1a1185d958d9dd09fb594f35bf4ab849d7817f8e"
+        "jar": "c189e11ddb2c8e15544386687d986108584934b06a025c09c334f24b11260528"
      },
-      "version": "4.1.0-M8"
+      "version": "4.0.7"
+    },
+    "org.json4s:json4s-native-core_2.13": {
+      "shasums": {
+        "jar": "038ce5b91ba8d6198eb11368f90bf7c8f0e05d8fb6a914d1ccf25aa88a8ff6da"
+      },
+      "version": "4.0.7"
+    },
+    "org.json4s:json4s-native_2.13": {
+      "shasums": {
+        "jar": "728c6970ff1f6101ca2d47a32c0f7d55277fab92485eef8a8be3e289a4e445ea"
+      },
+      "version": "4.0.7"
+    },
+    "org.json4s:json4s-scalap_2.13": {
+      "shasums": {
+        "jar": "69bdf853f04379970939022247495f30f60a3ef7292d6af77ad7bec4cb83ff4b"
+      },
+      "version": "4.0.7"
    },
    "org.ow2.asm:asm": {
      "shasums": {
@@ -533,29 +509,29 @@
      },
      "version": "1.0.4"
    },
-    "org.scala-lang.modules:scala-collection-compat_3": {
+    "org.scala-lang.modules:scala-collection-compat_2.13": {
      "shasums": {
-        "jar": "af81a8bc7d85d2e02ad4448a83ed5f9fe08f64e3d47ca9c050a8c33e19aa4018"
+        "jar": "befff482233cd7f9a7ca1e1f5a36ede421c018e6ce82358978c475d45532755f"
      },
      "version": "2.12.0"
    },
    "org.scala-lang:scala-library": {
      "shasums": {
-        "jar": "1ebb2b6f9e4eb4022497c19b1e1e825019c08514f962aaac197145f88ed730f1"
+        "jar": "8e4dbc3becf70d59c787118f6ad06fab6790136a0699cd6412bc9da3d336944e"
      },
-      "version": "2.13.16"
+      "version": "2.13.15"
    },
-    "org.scala-lang:scala3-library_3": {
+    "org.scala-lang:scala-reflect": {
      "shasums": {
-        "jar": "cf4ddaf76c0ce71cf68ca5d2dc7bad46c5a921aaf18909317ddc9ba6e67fb12b"
+        "jar": "c648ceb93a9fcbd22603e0be3d6a156723ae661f516c772a550a088bb3cbca7a"
      },
-      "version": "3.3.6"
+      "version": "2.13.12"
    },
-    "org.scalamock:scalamock_3": {
+    "org.scalamock:scalamock_2.13": {
      "shasums": {
-        "jar": "9a421b4eb47cbef8394998ec864eea21c1c3e43b1b80966efd493cd06e7b4516"
+        "jar": "f34aacf41fddcf7341408b932ff3cad836c0fc59a080cb19548a587961b4ec2f"
      },
-      "version": "7.4.1"
+      "version": "6.0.0"
    },
    "org.slf4j:slf4j-api": {
      "shasums": {
@@ -810,63 +786,48 @@
      "org.checkerframework:checker-qual",
      "org.ow2.asm:asm"
    ],
-    "com.squareup.okhttp3:okhttp": [
-      "com.squareup.okio:okio",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk8"
-    ],
-    "com.squareup.okhttp3:okhttp-sse": [
-      "com.squareup.okhttp3:okhttp",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk8"
-    ],
    "com.squareup.okhttp:okhttp": [
      "com.squareup.okio:okio"
    ],
    "com.squareup.okio:okio": [
-      "com.squareup.okio:okio-jvm"
+      "org.jetbrains.kotlin:kotlin-stdlib",
+      "org.jetbrains.kotlin:kotlin-stdlib-common"
    ],
-    "com.squareup.okio:okio-jvm": [
-      "org.jetbrains.kotlin:kotlin-stdlib-common",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk8"
-    ],
-    "com.thesamet.scalapb:compilerplugin_3": [
+    "com.thesamet.scalapb:compilerplugin_2.13": [
      "com.google.protobuf:protobuf-java",
      "com.thesamet.scalapb:protoc-gen_2.13",
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+      "org.scala-lang.modules:scala-collection-compat_2.13",
+      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:lenses_3": [
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+    "com.thesamet.scalapb:lenses_2.13": [
+      "org.scala-lang.modules:scala-collection-compat_2.13",
+      "org.scala-lang:scala-library"
    ],
    "com.thesamet.scalapb:protoc-bridge_2.13": [
      "dev.dirs:directories",
      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:protoc-bridge_3": [
-      "dev.dirs:directories",
-      "org.scala-lang:scala3-library_3"
-    ],
    "com.thesamet.scalapb:protoc-gen_2.13": [
      "com.thesamet.scalapb:protoc-bridge_2.13",
      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:scalapb-json4s_3": [
-      "com.thesamet.scalapb:scalapb-runtime_3",
-      "org.json4s:json4s-jackson-core_3",
-      "org.scala-lang:scala3-library_3"
+    "com.thesamet.scalapb:scalapb-json4s_2.13": [
+      "com.thesamet.scalapb:scalapb-runtime_2.13",
+      "org.json4s:json4s-jackson-core_2.13",
+      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:scalapb-runtime-grpc_3": [
-      "com.thesamet.scalapb:scalapb-runtime_3",
+    "com.thesamet.scalapb:scalapb-runtime-grpc_2.13": [
+      "com.thesamet.scalapb:scalapb-runtime_2.13",
      "io.grpc:grpc-protobuf",
      "io.grpc:grpc-stub",
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+      "org.scala-lang.modules:scala-collection-compat_2.13",
+      "org.scala-lang:scala-library"
    ],
-    "com.thesamet.scalapb:scalapb-runtime_3": [
+    "com.thesamet.scalapb:scalapb-runtime_2.13": [
      "com.google.protobuf:protobuf-java",
-      "com.thesamet.scalapb:lenses_3",
-      "org.scala-lang.modules:scala-collection-compat_3",
-      "org.scala-lang:scala3-library_3"
+      "com.thesamet.scalapb:lenses_2.13",
+      "org.scala-lang.modules:scala-collection-compat_2.13",
+      "org.scala-lang:scala-library"
    ],
    "io.grpc:grpc-api": [
      "com.google.code.findbugs:jsr305",
@@ -1034,42 +995,41 @@
      "org.jetbrains.kotlin:kotlin-stdlib-common",
      "org.jetbrains:annotations"
    ],
-    "org.jetbrains.kotlin:kotlin-stdlib-jdk7": [
-      "org.jetbrains.kotlin:kotlin-stdlib"
-    ],
-    "org.jetbrains.kotlin:kotlin-stdlib-jdk8": [
-      "org.jetbrains.kotlin:kotlin-stdlib",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk7"
-    ],
-    "org.json4s:json4s-ast_3": [
-      "org.scala-lang:scala3-library_3"
-    ],
-    "org.json4s:json4s-core_3": [
-      "org.json4s:json4s-ast_3",
-      "org.scala-lang:scala3-library_3"
-    ],
-    "org.json4s:json4s-jackson-core_3": [
-      "com.fasterxml.jackson.core:jackson-databind",
-      "org.json4s:json4s-ast_3",
-      "org.scala-lang:scala3-library_3"
-    ],
-    "org.json4s:json4s-native-core_3": [
-      "org.json4s:json4s-ast_3",
-      "org.scala-lang:scala3-library_3"
-    ],
-    "org.json4s:json4s-native_3": [
-      "org.json4s:json4s-core_3",
-      "org.json4s:json4s-native-core_3",
-      "org.scala-lang:scala3-library_3"
-    ],
-    "org.scala-lang.modules:scala-collection-compat_3": [
-      "org.scala-lang:scala3-library_3"
-    ],
-    "org.scala-lang:scala3-library_3": [
+    "org.json4s:json4s-ast_2.13": [
      "org.scala-lang:scala-library"
    ],
-    "org.scalamock:scalamock_3": [
-      "org.scala-lang:scala3-library_3"
+    "org.json4s:json4s-core_2.13": [
+      "com.thoughtworks.paranamer:paranamer",
+      "org.json4s:json4s-ast_2.13",
+      "org.json4s:json4s-scalap_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-jackson-core_2.13": [
+      "com.fasterxml.jackson.core:jackson-databind",
+      "org.json4s:json4s-ast_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-native-core_2.13": [
+      "org.json4s:json4s-ast_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-native_2.13": [
+      "org.json4s:json4s-core_2.13",
+      "org.json4s:json4s-native-core_2.13",
+      "org.scala-lang:scala-library"
+    ],
+    "org.json4s:json4s-scalap_2.13": [
+      "org.scala-lang:scala-library"
+    ],
+    "org.scala-lang.modules:scala-collection-compat_2.13": [
+      "org.scala-lang:scala-library"
+    ],
+    "org.scala-lang:scala-reflect": [
+      "org.scala-lang:scala-library"
+    ],
+    "org.scalamock:scalamock_2.13": [
+      "org.scala-lang:scala-library",
+      "org.scala-lang:scala-reflect"
    ],
    "org.slf4j:slf4j-simple": [
      "org.slf4j:slf4j-api"
@@ -1500,29 +1460,6 @@
    "com.google.truth:truth": [
      "com.google.common.truth"
    ],
-    "com.squareup.okhttp3:okhttp": [
-      "okhttp3",
-      "okhttp3.internal",
-      "okhttp3.internal.authenticator",
-      "okhttp3.internal.cache",
-      "okhttp3.internal.cache2",
-      "okhttp3.internal.concurrent",
-      "okhttp3.internal.connection",
-      "okhttp3.internal.http",
-      "okhttp3.internal.http1",
-      "okhttp3.internal.http2",
-      "okhttp3.internal.io",
-      "okhttp3.internal.platform",
-      "okhttp3.internal.platform.android",
-      "okhttp3.internal.proxy",
-      "okhttp3.internal.publicsuffix",
-      "okhttp3.internal.tls",
-      "okhttp3.internal.ws"
-    ],
-    "com.squareup.okhttp3:okhttp-sse": [
-      "okhttp3.internal.sse",
-      "okhttp3.sse"
-    ],
    "com.squareup.okhttp:okhttp": [
      "com.squareup.okhttp",
      "com.squareup.okhttp.internal",
@@ -1531,18 +1468,18 @@
      "com.squareup.okhttp.internal.io",
      "com.squareup.okhttp.internal.tls"
    ],
-    "com.squareup.okio:okio-jvm": [
+    "com.squareup.okio:okio": [
      "okio",
      "okio.internal"
    ],
-    "com.thesamet.scalapb:compilerplugin_3": [
+    "com.thesamet.scalapb:compilerplugin_2.13": [
      "scalapb",
      "scalapb.compiler",
      "scalapb.internal",
      "scalapb.options",
      "scalapb.options.compiler"
    ],
-    "com.thesamet.scalapb:lenses_3": [
+    "com.thesamet.scalapb:lenses_2.13": [
      "scalapb.lenses"
    ],
    "com.thesamet.scalapb:protoc-bridge_2.13": [
@@ -1550,21 +1487,16 @@
      "protocbridge.codegen",
      "protocbridge.frontend"
    ],
-    "com.thesamet.scalapb:protoc-bridge_3": [
-      "protocbridge",
-      "protocbridge.codegen",
-      "protocbridge.frontend"
-    ],
    "com.thesamet.scalapb:protoc-gen_2.13": [
      "protocgen"
    ],
-    "com.thesamet.scalapb:scalapb-json4s_3": [
+    "com.thesamet.scalapb:scalapb-json4s_2.13": [
      "scalapb.json4s"
    ],
-    "com.thesamet.scalapb:scalapb-runtime-grpc_3": [
+    "com.thesamet.scalapb:scalapb-runtime-grpc_2.13": [
      "scalapb.grpc"
    ],
-    "com.thesamet.scalapb:scalapb-runtime_3": [
+    "com.thesamet.scalapb:scalapb-runtime_2.13": [
      "com.google.protobuf.any",
      "com.google.protobuf.api",
      "com.google.protobuf.compiler.plugin",
@@ -1583,6 +1515,9 @@
      "scalapb.options",
      "scalapb.textformat"
    ],
+    "com.thoughtworks.paranamer:paranamer": [
+      "com.thoughtworks.paranamer"
+    ],
    "commons-codec:commons-codec": [
      "org.apache.commons.codec",
      "org.apache.commons.codec.binary",
@@ -1886,7 +1821,6 @@
      "kotlin.annotation",
      "kotlin.collections",
      "kotlin.collections.builders",
-      "kotlin.collections.jdk8",
      "kotlin.collections.unsigned",
      "kotlin.comparisons",
      "kotlin.concurrent",
@@ -1895,59 +1829,51 @@
      "kotlin.coroutines.cancellation",
      "kotlin.coroutines.intrinsics",
      "kotlin.coroutines.jvm.internal",
-      "kotlin.enums",
      "kotlin.experimental",
      "kotlin.internal",
-      "kotlin.internal.jdk7",
-      "kotlin.internal.jdk8",
      "kotlin.io",
-      "kotlin.io.encoding",
-      "kotlin.io.path",
-      "kotlin.jdk7",
      "kotlin.js",
      "kotlin.jvm",
      "kotlin.jvm.functions",
      "kotlin.jvm.internal",
      "kotlin.jvm.internal.markers",
      "kotlin.jvm.internal.unsafe",
-      "kotlin.jvm.jdk8",
-      "kotlin.jvm.optionals",
      "kotlin.math",
      "kotlin.properties",
      "kotlin.random",
-      "kotlin.random.jdk8",
      "kotlin.ranges",
      "kotlin.reflect",
      "kotlin.sequences",
-      "kotlin.streams.jdk8",
      "kotlin.system",
      "kotlin.text",
-      "kotlin.text.jdk8",
-      "kotlin.time",
-      "kotlin.time.jdk8"
+      "kotlin.time"
    ],
    "org.jetbrains:annotations": [
      "org.intellij.lang.annotations",
      "org.jetbrains.annotations"
    ],
-    "org.json4s:json4s-ast_3": [
+    "org.json4s:json4s-ast_2.13": [
      "org.json4s",
      "org.json4s.prefs"
    ],
-    "org.json4s:json4s-core_3": [
+    "org.json4s:json4s-core_2.13": [
      "org.json4s",
      "org.json4s.prefs",
      "org.json4s.reflect"
    ],
-    "org.json4s:json4s-jackson-core_3": [
+    "org.json4s:json4s-jackson-core_2.13": [
      "org.json4s.jackson"
    ],
-    "org.json4s:json4s-native-core_3": [
+    "org.json4s:json4s-native-core_2.13": [
      "org.json4s.native"
    ],
-    "org.json4s:json4s-native_3": [
+    "org.json4s:json4s-native_2.13": [
      "org.json4s.native"
    ],
+    "org.json4s:json4s-scalap_2.13": [
+      "org.json4s.scalap",
+      "org.json4s.scalap.scalasig"
+    ],
    "org.ow2.asm:asm": [
      "org.objectweb.asm",
      "org.objectweb.asm.signature"
@@ -1955,7 +1881,7 @@
    "org.reactivestreams:reactive-streams": [
      "org.reactivestreams"
    ],
-    "org.scala-lang.modules:scala-collection-compat_3": [
+    "org.scala-lang.modules:scala-collection-compat_2.13": [
      "scala.collection.compat",
      "scala.collection.compat.immutable",
      "scala.util.control.compat",
@@ -1994,26 +1920,22 @@
      "scala.util.hashing",
      "scala.util.matching"
    ],
-    "org.scala-lang:scala3-library_3": [
-      "scala",
-      "scala.annotation",
-      "scala.annotation.internal",
-      "scala.annotation.unchecked",
-      "scala.compiletime",
-      "scala.compiletime.ops",
-      "scala.compiletime.testing",
-      "scala.deriving",
-      "scala.quoted",
-      "scala.quoted.runtime",
-      "scala.reflect",
-      "scala.runtime",
-      "scala.runtime.coverage",
-      "scala.runtime.function",
-      "scala.runtime.stdLibPatches",
-      "scala.util",
-      "scala.util.control"
+    "org.scala-lang:scala-reflect": [
+      "scala.reflect.api",
+      "scala.reflect.internal",
+      "scala.reflect.internal.annotations",
+      "scala.reflect.internal.pickling",
+      "scala.reflect.internal.settings",
+      "scala.reflect.internal.tpe",
+      "scala.reflect.internal.transform",
+      "scala.reflect.internal.util",
+      "scala.reflect.io",
+      "scala.reflect.macros",
+      "scala.reflect.macros.blackbox",
+      "scala.reflect.macros.whitebox",
+      "scala.reflect.runtime"
    ],
-    "org.scalamock:scalamock_3": [
+    "org.scalamock:scalamock_2.13": [
      "org.scalamock",
      "org.scalamock.clazz",
      "org.scalamock.context",
@@ -2024,8 +1946,6 @@
      "org.scalamock.scalatest",
      "org.scalamock.scalatest.proxy",
      "org.scalamock.specs2",
-      "org.scalamock.stubs",
-      "org.scalamock.stubs.internal",
      "org.scalamock.util"
    ],
    "org.slf4j:slf4j-api": [
@@ -2355,19 +2275,16 @@
      "com.google.protobuf:protobuf-java",
      "com.google.re2j:re2j",
      "com.google.truth:truth",
-      "com.squareup.okhttp3:okhttp",
-      "com.squareup.okhttp3:okhttp-sse",
      "com.squareup.okhttp:okhttp",
      "com.squareup.okio:okio",
-      "com.squareup.okio:okio-jvm",
-      "com.thesamet.scalapb:compilerplugin_3",
-      "com.thesamet.scalapb:lenses_3",
+      "com.thesamet.scalapb:compilerplugin_2.13",
+      "com.thesamet.scalapb:lenses_2.13",
      "com.thesamet.scalapb:protoc-bridge_2.13",
-      "com.thesamet.scalapb:protoc-bridge_3",
      "com.thesamet.scalapb:protoc-gen_2.13",
-      "com.thesamet.scalapb:scalapb-json4s_3",
-      "com.thesamet.scalapb:scalapb-runtime-grpc_3",
-      "com.thesamet.scalapb:scalapb-runtime_3",
+      "com.thesamet.scalapb:scalapb-json4s_2.13",
+      "com.thesamet.scalapb:scalapb-runtime-grpc_2.13",
+      "com.thesamet.scalapb:scalapb-runtime_2.13",
+      "com.thoughtworks.paranamer:paranamer",
      "commons-codec:commons-codec",
      "commons-logging:commons-logging",
      "dev.dirs:directories",
@@ -2412,20 +2329,19 @@
      "org.hamcrest:hamcrest-core",
      "org.jetbrains.kotlin:kotlin-stdlib",
      "org.jetbrains.kotlin:kotlin-stdlib-common",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk7",
-      "org.jetbrains.kotlin:kotlin-stdlib-jdk8",
      "org.jetbrains:annotations",
-      "org.json4s:json4s-ast_3",
-      "org.json4s:json4s-core_3",
-      "org.json4s:json4s-jackson-core_3",
-      "org.json4s:json4s-native-core_3",
-      "org.json4s:json4s-native_3",
+      "org.json4s:json4s-ast_2.13",
+      "org.json4s:json4s-core_2.13",
+      "org.json4s:json4s-jackson-core_2.13",
+      "org.json4s:json4s-native-core_2.13",
+      "org.json4s:json4s-native_2.13",
+      "org.json4s:json4s-scalap_2.13",
      "org.ow2.asm:asm",
      "org.reactivestreams:reactive-streams",
-      "org.scala-lang.modules:scala-collection-compat_3",
+      "org.scala-lang.modules:scala-collection-compat_2.13",
      "org.scala-lang:scala-library",
-      "org.scala-lang:scala3-library_3",
-      "org.scalamock:scalamock_3",
+      "org.scala-lang:scala-reflect",
+      "org.scalamock:scalamock_2.13",
      "org.slf4j:slf4j-api",
      "org.slf4j:slf4j-simple",
      "software.amazon.awssdk:annotations",
@@ -3,8 +3,7 @@
 set -euxo pipefail

 /bin/echo "building darwin bundle"
-bazel build --config=mactools @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle
-ZIP_LOCATION=$(bazel cquery --config=mactools --output=files @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle 2>/dev/null)
-/usr/bin/unzip -o $ZIP_LOCATION -d src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/
+bazel build --noincompatible_enable_cc_toolchain_resolution @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle
+/usr/bin/unzip -o bazel-bin/external/net_eagle0_unity_godice/darwin/framework/DarwinGodiceBundle.zip -d src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/

 /usr/bin/plutil -convert xml1 src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/DarwinGodiceBundle.bundle/Contents/Info.plist
@@ -5,9 +5,8 @@ set -euxo pipefail
 /bin/echo "build plugins"

 /bin/echo "building darwin bundle"
-bazel build --config=mactools @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle
-ZIP_LOCATION=$(bazel cquery --config=mactools --output=files @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle 2>/dev/null)
-/usr/bin/unzip -o $ZIP_LOCATION -d src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/
+bazel build --noincompatible_enable_cc_toolchain_resolution @net_eagle0_unity_godice//darwin/framework:DarwinGodiceBundle
+/usr/bin/unzip -o bazel-bin/external/net_eagle0_unity_godice/darwin/framework/DarwinGodiceBundle.zip -d src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/

 /usr/bin/plutil -convert xml1 src/main/csharp/net/eagle0/clients/unity/eagle0/Assets/Plugins/DarwinGodiceBundle.bundle/Contents/Info.plist

@@ -1,10 +1,8 @@
 #!/usr/bin/env bash

-curl -L "https://docs.google.com/spreadsheets/d/1pv-WMXReccddPwev_YG9IXEGznuGHrYjNNEZ0Rb-ZhM/export?gid=0&format=tsv" | tr -d '\r' > src/main/resources/net/eagle0/shardok/settings.tsv
-curl -L "https://docs.google.com/spreadsheets/d/1p6I5nUMcoAPHIcqikVgbBCFVnqN9dpOEVClbS_wOI7M/export?gid=0&format=tsv" | tr -d '\r' > src/main/resources/net/eagle0/eagle/settings.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1pv-WMXReccddPwev_YG9IXEGznuGHrYjNNEZ0Rb-ZhM/export?gid=0&format=tsv" > src/main/resources/net/eagle0/shardok/settings.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1p6I5nUMcoAPHIcqikVgbBCFVnqN9dpOEVClbS_wOI7M/export?gid=0&format=tsv" > src/main/resources/net/eagle0/eagle/settings.tsv

 bazel run //src/main/go/net/eagle0/build/settings_generator:settings_generator -- \
    ${PWD}/src/main/resources/net/eagle0/eagle/settings.tsv \
    ${PWD}/src/main/scala/net/eagle0/eagle/library/settings/
-bazel run gazelle
-
@@ -1,11 +1,11 @@
 #!/usr/bin/env bash

-curl -L "https://docs.google.com/spreadsheets/d/1DHEsiv4cY4gE6AX3sVH82K__mpBD1aznIYCQwQxA_F0/export?gid=0&format=tsv" | tr -d '\r' > /tmp/names.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1DHEsiv4cY4gE6AX3sVH82K__mpBD1aznIYCQwQxA_F0/export?gid=0&format=tsv" > /tmp/names.tsv
 bazel run //src/main/scala/net/eagle0/util:name_list_checker -- /tmp/names.tsv > src/main/resources/net/eagle0/names.tsv
 bazel run //src/main/scala/net/eagle0/util:name_list_json_maker -- /tmp/names.tsv > src/main/resources/net/eagle0/names.json
-curl -L "https://docs.google.com/spreadsheets/d/1NhvG73HKyVE36yGpkV2oJiSIXoNqQOYTr5ArLnucYL0/export?gid=0&format=tsv" | tr -d '\r' > src/main/resources/net/eagle0/shardok/battalionTypes.tsv
-curl -L "https://docs.google.com/spreadsheets/d/1pNWiyxIks2wJ1v7jRLFD24zrKHG2AfhC-nkWmQKQGN4/export?gid=0&format=tsv" | tr -d '\r' > src/main/resources/net/eagle0/eagle/heroes.tsv
-curl -L "https://docs.google.com/spreadsheets/d/1RUguq5eAQprsZwOOqiCc-1dg4Urc_6iJ6awZsFU4MeI/export?gid=0&format=tsv" | tr -d '\r' > src/main/resources/net/eagle0/eagle/beasts.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1NhvG73HKyVE36yGpkV2oJiSIXoNqQOYTr5ArLnucYL0/export?gid=0&format=tsv" > src/main/resources/net/eagle0/shardok/battalionTypes.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1pNWiyxIks2wJ1v7jRLFD24zrKHG2AfhC-nkWmQKQGN4/export?gid=0&format=tsv" > src/main/resources/net/eagle0/eagle/heroes.tsv
+curl -L "https://docs.google.com/spreadsheets/d/1RUguq5eAQprsZwOOqiCc-1dg4Urc_6iJ6awZsFU4MeI/export?gid=0&format=tsv" > src/main/resources/net/eagle0/eagle/beasts.tsv
 #curl -L "https://docs.google.com/spreadsheets/d/1Z-60cJ_N1IasvqpVb5awKEkIYznEeR2IZSdli47oW88/export?gid=0&format=tsv" > src/main/resources/net/eagle0/eagle/province_map.tsv

 ${PWD}/scripts/dlSettings.sh
@@ -1,19 +0,0 @@
-#!/bin/bash
-# Pre-commit hook wrapper for gazelle that fails if files are modified.
-# This ensures BUILD files are in canonical format before committing.
-
-set -e
-
-# Run gazelle
-bazel run //:gazelle 2>/dev/null
-
-# Check if any BUILD files were modified
-if ! git diff --quiet -- '*.bazel' '**/BUILD' 'WORKSPACE*'; then
-    echo ""
-    echo "ERROR: gazelle modified BUILD files. Please stage the changes and retry:"
-    echo ""
-    git diff --name-only -- '*.bazel' '**/BUILD' 'WORKSPACE*'
-    echo ""
-    echo "Run: git add -u && git commit"
-    exit 1
-fi
@@ -88,11 +88,19 @@ cc_library(
    ],
 )

+cc_library(
+    name = "task_result",
+    hdrs = ["TaskResult.hpp"],
+    copts = COPTS,
+    visibility = ["//visibility:public"],
+)
+
 cc_library(
    name = "thread_pool",
    hdrs = ["ThreadPool.hpp"],
    copts = COPTS,
    visibility = ["//visibility:public"],
+    deps = [":task_result"],
 )

 cc_library(
@@ -18,31 +18,11 @@ static inline auto MixIn(uint64_t& hash, const uint8_t byte) {
 }

 // Hash an entire buffer using FNV-1a
-// Fast word-at-a-time implementation - processes 8 bytes at once for better performance
-// while maintaining good distribution properties for hash table use
 static inline auto HashBuffer(const uint8_t* data, size_t size) -> uint64_t {
-    if (data == nullptr) { return FNV_OFFSET_BASIS; }
-
    uint64_t hash = FNV_OFFSET_BASIS;
-    const uint8_t* end = data + size;
-
-    // Process 8 bytes at a time
-    while (data + 8 <= end) {
-        uint64_t word;
-        // Use memcpy to avoid alignment issues and let compiler optimize
-        __builtin_memcpy(&word, data, sizeof(word));
-        hash ^= word;
-        hash *= FNV_PRIME;
-        data += 8;
+    if (data != nullptr) {
+        for (size_t i = 0; i < size; ++i) { MixIn(hash, data[i]); }
    }
-
-    // Process remaining bytes
-    while (data < end) {
-        hash ^= static_cast<uint64_t>(*data);
-        hash *= FNV_PRIME;
-        data++;
-    }
-
    return hash;
 }

@@ -30,7 +30,7 @@ auto rloc(const string& execPath) -> string {
    const std::unique_ptr<Runfiles> runfiles(Runfiles::Create(execPath, &error));

    if (runfiles == nullptr) {
-        fprintf(stderr, "Error! %s\n", error.c_str());
+        printf("Error! %s\n", error.c_str());
        abort();
        // error handling
    }
@@ -67,9 +67,9 @@ auto FilesystemUtils::MapFilesDirectory() -> string {

 void FilesystemUtils::MakeDirectoryIfNecessary(const string& directoryPath) {
    if (fs::create_directories(directoryPath))
-        fprintf(stderr, "Directory %s created\n", directoryPath.c_str());
+        printf("Directory %s created\n", directoryPath.c_str());
    else
-        fprintf(stderr, "No new directory created for %s\n", directoryPath.c_str());
+        printf("No new directory created for %s\n", directoryPath.c_str());
 }

 auto FilesystemUtils::SaveFilesDirectory() -> string {
@@ -129,11 +129,11 @@ auto FilesystemUtils::AtomicallySaveToPath(const string& path, const byte_vector
    if (ostr.good()) {
        const int err = rename(tempPath.c_str(), path.c_str());
        if (err == -1) {
-            fprintf(stderr, "Failed to move file to %s! Errno %d\n", path.c_str(), errno);
+            printf("Failed to move file to %s! Errno %d\n", path.c_str(), errno);
            return false;
        }
    } else {
-        fprintf(stderr, "Failed writing to %s!\n", tempPath.c_str());
+        printf("Failed writing to %s!\n", tempPath.c_str());
        return false;
    }

@@ -14,14 +14,6 @@

 #include "src/main/cpp/net/eagle0/common/RandomGenerator.hpp"

-// A deterministic random generator that returns values from a fixed sequence.
-// Used for testing and MCTS simulation where we want specific, predictable outcomes.
-//
-// Values in the sequence are treated as [0, 1] probabilities that are returned
-// by DoubleZeroToOne(). The normal percentile methods (including open-ended
-// variants) work as usual, so callers must provide appropriate sequences.
-// For example, to get an open-ended low result of -50, provide [0.02, 0.52]
-// which produces: initial=2 (triggers open-ended), accumulated=52, final=2-52=-50
 class SequenceRandomGenerator : public ::RandomGenerator {
 private:
    const std::vector<double> sequence;
@@ -0,0 +1,39 @@
+//
+// TaskResult.hpp - Result wrapper for task execution with status information
+//
+
+#ifndef EAGLE0_TASK_RESULT_HPP
+#define EAGLE0_TASK_RESULT_HPP
+
+namespace eagle0::common {
+
+enum class TaskStatus { SUCCESS = 0, DEADLINE_EXCEEDED = 1, CANCELLED = 2 };
+
+template<typename T>
+struct TaskResult {
+    T value;
+    TaskStatus status;
+
+    TaskResult() : value{}, status(TaskStatus::SUCCESS) {}
+    TaskResult(T val) : value(std::move(val)), status(TaskStatus::SUCCESS) {}
+    TaskResult(T val, TaskStatus stat) : value(std::move(val)), status(stat) {}
+
+    // Convenience methods for checking status
+    T get() const { return value; }
+    bool succeeded() const { return status == TaskStatus::SUCCESS; }
+    bool deadlineExceeded() const { return status == TaskStatus::DEADLINE_EXCEEDED; }
+    bool cancelled() const { return status == TaskStatus::CANCELLED; }
+
+    // Factory methods for cleaner construction
+    static TaskResult Success(T val) { return TaskResult(std::move(val), TaskStatus::SUCCESS); }
+    static TaskResult DeadlineExceeded(T val = T{}) {
+        return TaskResult(std::move(val), TaskStatus::DEADLINE_EXCEEDED);
+    }
+    static TaskResult Cancelled(T val = T{}) {
+        return TaskResult(std::move(val), TaskStatus::CANCELLED);
+    }
+};
+
+}  // namespace eagle0::common
+
+#endif  // EAGLE0_TASK_RESULT_HPP
@@ -8,33 +8,26 @@
 #include <atomic>
 #include <chrono>
 #include <condition_variable>
+#include <deque>
 #include <functional>
 #include <future>
 #include <memory>
 #include <mutex>
-#include <queue>
 #include <thread>
 #include <vector>

+#include "TaskResult.hpp"
+
 namespace eagle0::common {

-enum class TaskStatus { SUCCESS = 0, DEADLINE_EXCEEDED = 1, CANCELLED = 2 };
-
-template<typename T>
-struct TaskResult {
-    T value;
-    TaskStatus status;
-
-    TaskResult() : value{}, status(TaskStatus::SUCCESS) {}
-    TaskResult(T val) : value(std::move(val)), status(TaskStatus::SUCCESS) {}
-    TaskResult(T val, TaskStatus stat) : value(std::move(val)), status(stat) {}
-
-    // NO implicit conversion - this was causing infinite recursion
-    // Use .value or .get() instead
-    T get() const { return value; }
-
-    bool succeeded() const { return status == TaskStatus::SUCCESS; }
-    bool deadlineExceeded() const { return status == TaskStatus::DEADLINE_EXCEEDED; }
+// Metrics structure for ThreadPool session statistics
+struct ThreadPoolMetrics {
+    size_t tasks_enqueued = 0;
+    size_t tasks_succeeded = 0;
+    size_t tasks_deadline_exceeded = 0;
+    size_t tasks_cancelled = 0;
+    double average_thread_load = 0.0;  // Average percentage of threads busy over time
+    std::chrono::milliseconds session_duration{0};
 };

 class ThreadPool {
@@ -45,47 +38,40 @@ public:
 private:
    struct Task {
        std::function<void()> function;
-        int priority;
        TimePoint deadline;
        bool has_deadline;

-        Task(std::function<void()> f, int p, TimePoint d, bool has_d)
+        Task(std::function<void()> f, TimePoint d, bool has_d)
            : function(std::move(f)),
-              priority(p),
              deadline(d),
              has_deadline(has_d) {}
-
-        // Higher priority values and earlier deadlines have higher priority
-        bool operator<(const Task& other) const {
-            if (priority != other.priority) {
-                return priority < other.priority;  // Lower priority values have lower priority in
-                                                   // priority_queue
-            }
-            if (has_deadline && other.has_deadline) {
-                return deadline > other.deadline;  // Later deadlines have lower priority
-            }
-            if (has_deadline && !other.has_deadline) {
-                return false;  // Tasks with deadlines have higher priority
-            }
-            if (!has_deadline && other.has_deadline) {
-                return true;  // Tasks without deadlines have lower priority
-            }
-            return false;  // Equal priority, no preference
-        }
    };

    std::vector<std::thread> workers;
-    std::priority_queue<Task> tasks;
-    std::mutex queue_mutex;
+    std::deque<Task> tasks;          // Simple FIFO queue instead of priority queue
+    mutable std::mutex queue_mutex;  // mutable for const methods like queue_size()
    std::condition_variable condition;
    std::atomic<bool> stop{false};

+    // Metrics tracking
+    mutable std::mutex metrics_mutex;  // mutable for const methods like isSessionActive()
+    bool session_active = false;
+    TimePoint session_start;
+    std::atomic<size_t> tasks_enqueued{0};
+    std::atomic<size_t> tasks_succeeded{0};
+    std::atomic<size_t> tasks_deadline_exceeded{0};
+    std::atomic<size_t> tasks_cancelled{0};
+    std::atomic<size_t> active_threads{0};
+
+    // Thread load tracking
+    std::vector<std::pair<TimePoint, size_t>> thread_load_samples;  // (timestamp, active_count)
+
 public:
    explicit ThreadPool(size_t num_threads = std::thread::hardware_concurrency()) {
        for (size_t i = 0; i < num_threads; ++i) {
            workers.emplace_back([this] {
                while (true) {
-                    Task task{nullptr, 0, TimePoint{}, false};
+                    Task task{nullptr, TimePoint{}, false};
                    {
                        std::unique_lock<std::mutex> lock(queue_mutex);
                        condition.wait(lock, [this] { return stop.load() || !tasks.empty(); });
@@ -93,23 +79,42 @@ public:
                        if (stop.load() && tasks.empty()) { return; }

                        if (!tasks.empty()) {
-                            task = std::move(const_cast<Task&>(tasks.top()));
-                            tasks.pop();
+                            task = std::move(tasks.front());
+                            tasks.pop_front();
                        } else {
                            continue;
                        }
                    }

                    // Execute the task (deadline checking is now handled inside the task)
-                    if (task.function) { task.function(); }
+                    if (task.function) {
+                        // Track thread activity
+                        active_threads++;
+                        recordThreadLoadSample();
+
+                        task.function();
+
+                        active_threads--;
+                        recordThreadLoadSample();
+                    }
                }
            });
        }
    }

-    // Enqueue a task with priority only
+private:
+    // Helper to record thread load samples
+    void recordThreadLoadSample() {
+        if (session_active) {
+            std::lock_guard<std::mutex> lock(metrics_mutex);
+            thread_load_samples.emplace_back(Clock::now(), active_threads.load());
+        }
+    }
+
+public:
+    // Enqueue a task without deadline
    template<class F, class... Args>
-    auto enqueue(F&& f, Args&&... args, int priority = 0)
+    auto enqueue(F&& f, Args&&... args)
            -> std::future<TaskResult<std::invoke_result_t<F, Args...>>> {
        using return_type = std::invoke_result_t<F, Args...>;
        using result_type = TaskResult<return_type>;
@@ -117,8 +122,19 @@ public:
        auto actualTask = std::bind(std::forward<F>(f), std::forward<Args>(args)...);

        auto task = std::make_shared<std::packaged_task<result_type()>>(
-                [actualTask = std::move(actualTask)]() mutable -> result_type {
-                    return result_type(actualTask());
+                [this, actualTask = std::move(actualTask)]() mutable -> result_type {
+                    result_type res = result_type(actualTask());
+
+                    // Track completion status
+                    if (session_active) {
+                        switch (res.status) {
+                            case TaskStatus::SUCCESS: tasks_succeeded++; break;
+                            case TaskStatus::DEADLINE_EXCEEDED: tasks_deadline_exceeded++; break;
+                            case TaskStatus::CANCELLED: tasks_cancelled++; break;
+                        }
+                    }
+
+                    return res;
                });

        std::future<result_type> result = task->get_future();
@@ -126,28 +142,43 @@ public:
        {
            std::unique_lock<std::mutex> lock(queue_mutex);
            if (stop.load()) { throw std::runtime_error("enqueue on stopped ThreadPool"); }
-            tasks.emplace([task]() { (*task)(); }, priority, TimePoint{}, false);
+            tasks.emplace_back([task]() { (*task)(); }, TimePoint{}, false);
+
+            if (session_active) { tasks_enqueued++; }
        }

        condition.notify_one();
        return result;
    }

-    // Enqueue a task with priority and deadline
-    template<class F, class... Args>
-    auto enqueue_with_deadline(F&& f, Args&&... args, int priority, TimePoint deadline)
-            -> std::future<TaskResult<std::invoke_result_t<F, Args...>>> {
-        using return_type = std::invoke_result_t<F, Args...>;
+    // Enqueue a task with deadline
+    template<class F>
+    auto enqueue_with_deadline(F&& f, TimePoint deadline)
+            -> std::future<TaskResult<std::invoke_result_t<F>>> {
+        using return_type = std::invoke_result_t<F>;
        using result_type = TaskResult<return_type>;

-        auto actualTask = std::bind(std::forward<F>(f), std::forward<Args>(args)...);
+        auto actualTask = std::forward<F>(f);

        auto task = std::make_shared<std::packaged_task<result_type()>>(
-                [actualTask = std::move(actualTask), deadline]() mutable -> result_type {
+                [this, actualTask = std::move(actualTask), deadline]() mutable -> result_type {
+                    result_type res;
                    if (Clock::now() > deadline) {
-                        return result_type(return_type{}, TaskStatus::DEADLINE_EXCEEDED);
+                        res = result_type(return_type{}, TaskStatus::DEADLINE_EXCEEDED);
+                    } else {
+                        res = result_type(actualTask());
                    }
-                    return result_type(actualTask());
+
+                    // Track completion status
+                    if (session_active) {
+                        switch (res.status) {
+                            case TaskStatus::SUCCESS: tasks_succeeded++; break;
+                            case TaskStatus::DEADLINE_EXCEEDED: tasks_deadline_exceeded++; break;
+                            case TaskStatus::CANCELLED: tasks_cancelled++; break;
+                        }
+                    }
+
+                    return res;
                });

        std::future<result_type> result = task->get_future();
@@ -155,7 +186,9 @@ public:
        {
            std::unique_lock<std::mutex> lock(queue_mutex);
            if (stop.load()) { throw std::runtime_error("enqueue on stopped ThreadPool"); }
-            tasks.emplace([task]() { (*task)(); }, priority, deadline, true);
+            tasks.emplace_back([task]() { (*task)(); }, deadline, true);
+
+            if (session_active) { tasks_enqueued++; }
        }

        condition.notify_one();
@@ -164,28 +197,102 @@ public:

    // Get current queue size (approximate, for monitoring)
    size_t queue_size() const {
-        std::unique_lock<std::mutex> lock(const_cast<std::mutex&>(queue_mutex));
+        std::unique_lock<std::mutex> lock(queue_mutex);
        return tasks.size();
    }

    // Get detailed queue information for debugging
    void debug_queue_state() const {
-        std::unique_lock<std::mutex> lock(const_cast<std::mutex&>(queue_mutex));
+        std::unique_lock<std::mutex> lock(queue_mutex);
        printf("ThreadPool: Queue size: %zu\n", tasks.size());
        if (!tasks.empty()) {
-            // Create a copy to inspect priorities without modifying queue
-            auto queue_copy = tasks;
-            std::vector<int> priorities;
-            while (!queue_copy.empty()) {
-                priorities.push_back(queue_copy.top().priority);
-                queue_copy.pop();
+            int with_deadline = 0;
+            int without_deadline = 0;
+            for (const auto& task : tasks) {
+                if (task.has_deadline) {
+                    with_deadline++;
+                } else {
+                    without_deadline++;
+                }
            }
-            printf("ThreadPool: Priorities in queue: ");
-            for (int p : priorities) { printf("%d ", p); }
-            printf("\n");
+            printf("ThreadPool: Tasks with deadline: %d, without deadline: %d\n",
+                   with_deadline,
+                   without_deadline);
        }
    }

+    // Start a new metrics session
+    void beginSession() {
+        std::lock_guard<std::mutex> lock(metrics_mutex);
+        session_active = true;
+        session_start = Clock::now();
+
+        // Reset all metrics
+        tasks_enqueued = 0;
+        tasks_succeeded = 0;
+        tasks_deadline_exceeded = 0;
+        tasks_cancelled = 0;
+        thread_load_samples.clear();
+
+        // Record initial thread load
+        thread_load_samples.emplace_back(session_start, active_threads.load());
+    }
+
+    // End the current session and return metrics
+    ThreadPoolMetrics endSession() {
+        std::lock_guard<std::mutex> lock(metrics_mutex);
+
+        if (!session_active) {
+            return ThreadPoolMetrics{};  // Return empty metrics if no session active
+        }
+
+        auto session_end = Clock::now();
+        session_active = false;
+
+        // Record final thread load
+        thread_load_samples.emplace_back(session_end, active_threads.load());
+
+        // Calculate metrics
+        ThreadPoolMetrics metrics;
+        metrics.tasks_enqueued = tasks_enqueued.load();
+        metrics.tasks_succeeded = tasks_succeeded.load();
+        metrics.tasks_deadline_exceeded = tasks_deadline_exceeded.load();
+        metrics.tasks_cancelled = tasks_cancelled.load();
+        metrics.session_duration =
+                std::chrono::duration_cast<std::chrono::milliseconds>(session_end - session_start);
+
+        // Calculate average thread load
+        if (thread_load_samples.size() >= 2 && workers.size() > 0) {
+            double total_load_time = 0.0;
+            auto total_duration =
+                    std::chrono::duration<double>(
+                            thread_load_samples.back().first - thread_load_samples.front().first)
+                            .count();
+
+            for (size_t i = 1; i < thread_load_samples.size(); ++i) {
+                auto duration =
+                        std::chrono::duration<double>(
+                                thread_load_samples[i].first - thread_load_samples[i - 1].first)
+                                .count();
+                auto load = static_cast<double>(thread_load_samples[i - 1].second) / workers.size();
+                total_load_time += load * duration;
+            }
+
+            metrics.average_thread_load =
+                    (total_duration > 0) ? (total_load_time / total_duration) : 0.0;
+        } else {
+            metrics.average_thread_load = 0.0;
+        }
+
+        return metrics;
+    }
+
+    // Check if a session is currently active
+    bool isSessionActive() const {
+        std::lock_guard<std::mutex> lock(metrics_mutex);
+        return session_active;
+    }
+
    ~ThreadPool() {
        stop.store(true);
        condition.notify_all();
@@ -1,139 +0,0 @@
-# MCTS (Monte Carlo Tree Search) Framework
-
-This directory contains a game-agnostic Monte Carlo Tree Search implementation that can be used with any turn-based game. The framework separates the MCTS algorithm from game-specific logic through abstract interfaces.
-
-## Core Abstract Classes
-
-### `MCTSAction` (abstract/MCTSAction.hpp)
-Abstract interface for representing game actions/moves.
-
-**Key Methods:**
- `getIndex()` - Returns the action's unique identifier
- `getDescription()` - Human-readable description for debugging/logging
- `clone()` - Creates a deep copy of the action
- `equals()` - Compares actions for equality
-
-### `MCTSGameState` (abstract/MCTSGameState.hpp)
-Abstract interface for representing game states.
-
-**Key Methods:**
- `hash()` - Returns a hash for transposition table lookups
- `score(playerId)` - Evaluates the state's value for a given player
- `currentPlayerId()` - Returns whose turn it is
- `isTerminal()` - Checks if the game has ended
- `getWinner()` - Returns the winning player (if terminal)
- `clone()` - Creates a deep copy of the state
- `equals()` - Compares states for equality
-
-### `MCTSGameEngine` (abstract/MCTSGameEngine.hpp)
-Abstract interface for game rule enforcement and state transitions. Many methods have efficient default implementations.
-
-**Must Override (Pure Virtual):**
- `applyAction(state, action)` - Applies an action to create a new state
- `getLegalActions(state)` - Returns all valid moves from a state
- `isTerminal(state)` - Checks if a state is game-ending
- `evaluateState(state, playerId)` - Scores a state for a player
-
-**Optional Overrides (Have Default Implementations):**
- `applyActionMutable(state, action)` - Apply action in-place for efficiency (default: calls applyAction)
- `filterActions(actions, state)` - Applies heuristic filtering (default: no filtering)
- `simulateRandomPlayout(state, playerId, maxDepth, policy)` - Runs simulation (default: efficient mutable implementation)
- `getActionScore(state, action, playerId)` - Scores an action (default: apply and evaluate)
- `shouldStopSearch(state, iterations, startTime)` - Early termination (default: no early stop)
-
-**Performance Features:**
- The default `simulateRandomPlayout` clones the state once and mutates it throughout simulation for efficiency
- Games can override `applyActionMutable` to provide even more efficient in-place updates
- Games can override `simulateRandomPlayout` for custom optimizations (e.g., using internal engine state)
-
-## MCTS Algorithm Implementation
-
-### `AbstractMCTSAI` (abstract/AbstractMCTSAI.hpp)
-The main MCTS algorithm implementation that works with any game implementing the abstract interfaces.
-
-**Key Features:**
- **Selection**: Uses UCB1 (Upper Confidence Bound) for node selection
- **Expansion**: Adds new nodes to the search tree
- **Simulation**: Runs random playouts to estimate node values
- **Backpropagation**: Updates node statistics with simulation results
- **Multithreading**: Supports parallel MCTS with configurable thread count
- **Path Compression**: Optimizes move sequences for better performance
-
-**Configuration Options:**
- `explorationConstant` - UCB1 exploration parameter (default: √2)
- `maxSimulationDepth` - Maximum depth for random playouts
- `maxTreeDepth` - Maximum tree depth to prevent stack overflow
- `useMultithreading` - Enable parallel search
- `numThreads` - Number of worker threads
- `simulationPolicy` - Strategy for action selection during simulation
-
-### `MCTSNode` (abstract/MCTSNode.hpp)
-Represents nodes in the MCTS search tree.
-
-**Core Data:**
- `action` - The action that led to this node
- `actionIndex` - Index in the original actions array
- `gameState` - The game state at this node
- `visitCount` - Number of times this node was visited
- `totalReward` - Sum of simulation rewards
- `averageReward` - Average reward (totalReward / visitCount)
- `children` - Child nodes in the search tree
- `parent` - Parent node reference
-
-**Key Methods:**
- `CanExpand()` - Checks if node has untried actions
- `GetBestChild(explorationConstant)` - UCB1-based child selection
- `GetBestFinalChild()` - Most-visited child (for final move selection)
- `CalculateUCB1(explorationConstant)` - Computes UCB1 value
-
-## Simulation Policies
-
-The framework supports multiple strategies for action selection during random playouts:
-
- **RANDOM** - Uniform random selection
- **FILTERED_RANDOM** - Random selection from filtered action set
- **BEST_IMMEDIATE** - Always choose the highest-scoring immediate action
- **WEIGHTED_BEST_IMMEDIATE** - Weighted random selection based on action scores
-
-## Type Definitions
-
-### `MCTSTypes` (abstract/MCTSTypes.hpp)
- `MCTSPlayerId` - Player identifier type (int)
- `MCTSSimulationPolicy` - Enumeration of simulation strategies
- `MCTSConfig` - Configuration structure for MCTS parameters
-
-## Usage Pattern
-
-To use this framework with your game:
-
-1. **Implement the abstract interfaces** for your game:
-   ```cpp
-   class MyGameAction : public MCTSAction { /* ... */ };
-   class MyGameState : public MCTSGameState { /* ... */ };
-   class MyGameEngine : public MCTSGameEngine { /* ... */ };
-   ```
-
-2. **Create and configure the AI**:
-   ```cpp
-   MCTSConfig config;
-   config.explorationConstant = 1.414;
-   config.maxSimulationDepth = 100;
-   AbstractMCTSAI ai(playerId, config);
-   ```
-
-3. **Run the search**:
-   ```cpp
-   auto actions = engine.getLegalActions(currentState);
-   auto result = ai.Search(engine, currentState, actions, timeLimit);
-   auto bestAction = actions[result.bestActionIndex];
-   ```
-
-## Testing
-
-The framework includes comprehensive tests using a Tic-Tac-Toe implementation:
- `MockTicTacToe.hpp` - Example implementation of all abstract interfaces
- `AbstractMCTSAI_test.cpp` - Unit tests for the core algorithm
- `MCTSIntegration_test.cpp` - Integration tests with complete games
- `MCTSNode_test.cpp` - Tests for the node data structure
-
-This demonstrates how to implement the interfaces and validates that the MCTS algorithm works correctly with any turn-based game.
@@ -1,106 +0,0 @@
-//
-// Abstract MCTS AI implementation - game agnostic
-//
-
-#ifndef EAGLE0_ABSTRACT_MCTSAI_HPP
-#define EAGLE0_ABSTRACT_MCTSAI_HPP
-
-#include <chrono>
-#include <memory>
-#include <unordered_map>
-#include <vector>
-
-#include "MCTSAction.hpp"
-#include "MCTSGameEngine.hpp"
-#include "MCTSGameState.hpp"
-#include "MCTSNode.hpp"
-#include "MCTSTypes.hpp"
-
-namespace shardok {
-namespace mcts {
-
-class AbstractMCTSAI {
-public:
-    // Search result structure
-    struct SearchResult {
-        size_t bestActionIndex = 0;
-        double bestScore = 0.0;
-        int searchDepth = 0;
-        int nodesEvaluated = 0;
-        std::chrono::milliseconds searchTime{0};
-        bool foundWinningMove = false;
-    };
-
-    explicit AbstractMCTSAI(MCTSPlayerId playerId, MCTSConfig config = MCTSConfig{});
-
-    // Main search interface
-    [[nodiscard]] auto Search(
-            const MCTSGameEngine& engine,
-            const MCTSGameState& initialState,
-            std::chrono::milliseconds timeLimit) const -> SearchResult;
-
-    // Configuration
-    [[nodiscard]] auto GetConfig() const -> const MCTSConfig& { return config_; }
-    void SetConfig(const MCTSConfig& newConfig) { config_ = newConfig; }
-
-    [[nodiscard]] auto FindNodeAtDepthWithHash(
-            const MCTSNode* root,
-            int maxDepth,
-            uint64_t targetHash) -> const MCTSNode*;
-
-private:
-    MCTSPlayerId playerId_;
-    MCTSConfig config_;
-
-    // Transposition table: maps state hash -> minimum depth at which state was reached
-    // Used to detect and penalize longer paths to the same game state
-    // Cleared at the start of each Search() call
-    mutable std::unordered_map<uint64_t, int> transpositionTable_;
-
-    // Core MCTS algorithm
-    [[nodiscard]] auto BuildMCTSTree(
-            const MCTSGameEngine& engine,
-            const MCTSGameState& initialState,
-            std::chrono::steady_clock::time_point deadline) const -> std::unique_ptr<MCTSNode>;
-
-    // MCTS phases
-    [[nodiscard]] auto MCTSSelection(MCTSNode* root) const -> MCTSNode*;
-
-    [[nodiscard]] auto MCTSExpansion(MCTSNode* node, const MCTSGameEngine& engine) const
-            -> MCTSNode*;
-
-    [[nodiscard]] auto MCTSSimulation(
-            const MCTSGameEngine& engine,
-            const MCTSGameState& state,
-            MCTSPlayerId startingPlayer,
-            int startingPlayerFlips = 0) const -> double;
-
-    auto MCTSBackpropagation(MCTSNode* node, double reward, MCTSBackpropagationPolicy policy) const
-            -> void;
-
-    // Helper functions
-    [[nodiscard]] auto SelectSimulationAction(
-            const MCTSGameEngine& engine,
-            const MCTSGameState& state,
-            const std::vector<std::unique_ptr<MCTSAction>>& actions,
-            bool isMaximizing) const -> size_t;
-
-    // Logging
-    static auto LogSearchResults(
-            const MCTSNode* rootNode,
-            const MCTSNode* bestChild,
-            const SearchResult& result) -> void;
-
-    // Debug tree dumping
-    static auto DumpTreeToFile(const MCTSNode* root, const std::string& filepath) -> void;
-
-private:
-    static auto
-    DumpNodeRecursive(const MCTSNode* node, std::ostream& out, int indentLevel, bool isLastChild)
-            -> void;
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_ABSTRACT_MCTSAI_HPP
@@ -1,94 +0,0 @@
-load("//tools:copts.bzl", "COPTS")
-
-cc_library(
-    name = "mcts_types",
-    hdrs = ["MCTSTypes.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-)
-
-cc_library(
-    name = "mcts_action",
-    hdrs = ["MCTSAction.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-)
-
-cc_library(
-    name = "mcts_game_state",
-    hdrs = ["MCTSGameState.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-    deps = [
-        ":mcts_types",
-    ],
-)
-
-cc_library(
-    name = "mcts_game_engine",
-    srcs = ["MCTSGameEngine.cpp"],
-    hdrs = ["MCTSGameEngine.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-    deps = [
-        ":mcts_action",
-        ":mcts_game_state",
-        ":mcts_types",
-    ],
-)
-
-cc_library(
-    name = "mcts_node",
-    hdrs = ["MCTSNode.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__pkg__",
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-    deps = [
-        ":mcts_action",
-        ":mcts_game_state",
-        ":mcts_types",
-    ],
-)
-
-cc_library(
-    name = "abstract_mcts_ai",
-    srcs = ["AbstractMCTSAI.cpp"],
-    hdrs = ["AbstractMCTSAI.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__subpackages__",
-    ],
-    deps = [
-        ":mcts_action",
-        ":mcts_game_engine",
-        ":mcts_game_state",
-        ":mcts_node",
-        ":mcts_types",
-        "//src/main/cpp/net/eagle0/common/mcts/util:tree_indent_util",
-    ],
-)
-
-# Individual targets are exposed above - no need for a catch-all target
-# Each component should be imported explicitly by its consumers
@@ -1,40 +0,0 @@
-//
-// Abstract action interface for MCTS
-//
-
-#ifndef EAGLE0_MCTS_ACTION_HPP
-#define EAGLE0_MCTS_ACTION_HPP
-
-#include <memory>
-#include <string>
-
-namespace shardok {
-namespace mcts {
-
-// Abstract interface for game actions
-class MCTSAction {
-public:
-    virtual ~MCTSAction() = default;
-
-    // Get a unique index for this action (used for command indexing)
-    [[nodiscard]] virtual size_t getIndex() const = 0;
-
-    // Get a human-readable description for debugging/logging
-    [[nodiscard]] virtual std::string getDescription() const = 0;
-
-    // Create a deep copy of this action
-    [[nodiscard]] virtual std::unique_ptr<MCTSAction> clone() const = 0;
-
-    // Check if two actions are equivalent
-    [[nodiscard]] virtual bool equals(const MCTSAction& other) const = 0;
-
-    // Check if this action requires a chance node (binary success/failure outcome)
-    // Examples: START_FIRE, RAISE_DEAD, EXTINGUISH_FIRE
-    // If true, the game engine should provide outcome probabilities
-    [[nodiscard]] virtual bool requiresChanceNode() const = 0;
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_ACTION_HPP
@@ -1,148 +0,0 @@
-//
-// Default implementations for MCTSGameEngine
-//
-
-#include "MCTSGameEngine.hpp"
-
-#include <algorithm>
-#include <limits>
-#include <random>
-#include <vector>
-
-#include "MCTSTypes.hpp"  // For MCTSInternalError
-
-namespace shardok {
-namespace mcts {
-
-double MCTSGameEngine::simulateRandomPlayout(
-        const MCTSGameState& state,
-        MCTSPlayerId playerId,
-        int maxDepth,
-        MCTSSimulationPolicy policy) const {
-    // Clone state once and mutate it throughout simulation for efficiency
-    auto currentState = state.clone();
-    int depth = 0;
-
-    // Use thread-local random generator for thread safety
-    static thread_local std::mt19937 gen(std::random_device{}());
-
-    // Simulate until terminal or max depth
-    while (!currentState->isTerminal() && depth < maxDepth) {
-        auto actions = getLegalActions(*currentState, playerId, 0, 0);
-        if (actions.empty()) { break; }
-
-        size_t selectedIndex = 0;
-
-        // Select action based on policy
-        switch (policy) {
-            case MCTSSimulationPolicy::RANDOM: {
-                std::uniform_int_distribution<> dis(0, actions.size() - 1);
-                selectedIndex = dis(gen);
-                break;
-            }
-
-            case MCTSSimulationPolicy::FILTERED_RANDOM: {
-                auto filteredIndices = filterActions(actions, *currentState);
-                if (!filteredIndices.empty()) {
-                    std::uniform_int_distribution<> dis(0, filteredIndices.size() - 1);
-                    selectedIndex = filteredIndices[dis(gen)];
-                } else {
-                    // Fall back to random if no actions pass filter
-                    std::uniform_int_distribution<> dis(0, actions.size() - 1);
-                    selectedIndex = dis(gen);
-                }
-                break;
-            }
-
-            case MCTSSimulationPolicy::BEST_IMMEDIATE: {
-                double bestScore = -std::numeric_limits<double>::infinity();
-                for (size_t i = 0; i < actions.size(); ++i) {
-                    double score = getActionScore(
-                            *currentState,
-                            *actions[i],
-                            currentState->currentPlayerId());
-                    if (score > bestScore) {
-                        bestScore = score;
-                        selectedIndex = i;
-                    }
-                }
-                break;
-            }
-
-            case MCTSSimulationPolicy::WEIGHTED_BEST_IMMEDIATE: {
-                // Score all actions and weight by ranking
-                std::vector<std::pair<size_t, double>> scores;
-                scores.reserve(actions.size());
-
-                for (size_t i = 0; i < actions.size(); ++i) {
-                    double score = getActionScore(
-                            *currentState,
-                            *actions[i],
-                            currentState->currentPlayerId());
-                    scores.emplace_back(i, score);
-                }
-
-                // Sort by score (descending)
-                std::sort(scores.begin(), scores.end(), [](const auto& a, const auto& b) {
-                    return a.second > b.second;
-                });
-
-                // Create weights based on ranking (1/rank)
-                std::vector<double> weights;
-                weights.reserve(scores.size());
-                for (size_t i = 0; i < scores.size(); ++i) { weights.push_back(1.0 / (i + 1.0)); }
-
-                // Select based on weights
-                std::discrete_distribution<> dis(weights.begin(), weights.end());
-                selectedIndex = scores[dis(gen)].first;
-                break;
-            }
-
-            case MCTSSimulationPolicy::WEIGHTED_HEURISTIC: {
-                // Get heuristic weights (fast O(1) per action)
-                const auto weights = getActionWeights(actions, *currentState);
-
-                // Filter out zero-weight actions
-                std::vector<size_t> validIndices;
-                std::vector<double> validWeights;
-                validIndices.reserve(actions.size());
-                validWeights.reserve(actions.size());
-
-                for (size_t i = 0; i < weights.size() && i < actions.size(); ++i) {
-                    if (weights[i] > 0.0) {
-                        validIndices.push_back(i);
-                        validWeights.push_back(weights[i]);
-                    }
-                }
-
-                // If all actions filtered out, this is a bug in the weighting logic
-                if (validWeights.empty()) {
-                    throw MCTSInternalError(
-                            "MCTS simulation (playout): All actions have zero weight in "
-                            "WEIGHTED_HEURISTIC policy (action count: " +
-                            std::to_string(actions.size()) +
-                            ") - this indicates incorrect weighting");
-                }
-
-                // Select based on heuristic weights
-                std::discrete_distribution<> dis(validWeights.begin(), validWeights.end());
-                selectedIndex = validIndices[dis(gen)];
-                break;
-            }
-        }
-
-        // Apply selected action using mutable version for efficiency
-        applyActionMutable(currentState, *actions[selectedIndex]);
-        if (!currentState) {
-            break;  // Failed to apply action
-        }
-
-        depth++;
-    }
-
-    // Return evaluation from original player's perspective
-    return evaluateState(*currentState, playerId);
-}
-
-}  // namespace mcts
-}  // namespace shardok
@@ -1,161 +0,0 @@
-//
-// Abstract game engine interface for MCTS
-//
-
-#ifndef EAGLE0_MCTS_GAME_ENGINE_HPP
-#define EAGLE0_MCTS_GAME_ENGINE_HPP
-
-#include <chrono>
-#include <memory>
-#include <vector>
-
-#include "MCTSAction.hpp"
-#include "MCTSGameState.hpp"
-#include "MCTSTypes.hpp"
-
-namespace shardok {
-namespace mcts {
-
-// Information about chance outcomes (supports both binary and multi-outcome)
-struct ChanceOutcomeInfo {
-    std::vector<double> probabilities;  // Probability of each outcome (must sum to 1.0)
-    std::vector<double> rolls;          // Roll values for each outcome
-
-    // Factory for binary success/failure outcomes (e.g., START_FIRE)
-    [[nodiscard]] static ChanceOutcomeInfo binary(double successProbability) {
-        // -100: triggers open-ended low sequence, succeeds against any threshold
-        // 150: triggers open-ended high sequence, fails against any threshold
-        return {{successProbability, 1.0 - successProbability}, {-100.0, 150.0}};
-    }
-
-    // Factory for multi-outcome with fixed seeds (e.g., END_TURN)
-    // Uses uniformly distributed roll values to sample different random outcomes
-    [[nodiscard]] static ChanceOutcomeInfo multiOutcome(int numOutcomes) {
-        std::vector<double> probs(numOutcomes, 1.0 / numOutcomes);
-        std::vector<double> rollValues;
-        rollValues.reserve(numOutcomes);
-        // Spread rolls across the percentile range: 10, 30, 50, 70, 90 for 5 outcomes
-        for (int i = 0; i < numOutcomes; ++i) {
-            rollValues.push_back(10.0 + (80.0 * i) / (numOutcomes - 1));
-        }
-        return {probs, rollValues};
-    }
-
-    [[nodiscard]] const std::vector<double>& getRepresentativeRolls() const { return rolls; }
-
-    [[nodiscard]] const std::vector<double>& getProbabilities() const { return probabilities; }
-};
-
-// Backward compatibility alias
-using BinaryOutcomeInfo = ChanceOutcomeInfo;
-
-// Abstract interface for game engines
-class MCTSGameEngine {
-public:
-    virtual ~MCTSGameEngine() = default;
-
-    // Apply an action to a state and return the resulting state
-    // If deterministicRoll is provided (0.0-100.0), use that for any random outcomes
-    [[nodiscard]] virtual std::unique_ptr<MCTSGameState> applyAction(
-            const MCTSGameState& state,
-            const MCTSAction& action,
-            double deterministicRoll = -1.0) const = 0;
-
-    // Apply an action to a mutable state in-place (for efficient simulation)
-    // Default: clone, apply, and move the result back
-    // Override this for better performance
-    virtual void applyActionMutable(std::unique_ptr<MCTSGameState>& state, const MCTSAction& action)
-            const {
-        state = applyAction(*state, action);
-    }
-
-    // Get all legal actions for the current state with player flip tracking
-    // Default implementation ignores flip tracking and calls base version
-    [[nodiscard]] virtual std::vector<std::unique_ptr<MCTSAction>> getLegalActions(
-            const MCTSGameState& state,
-            MCTSPlayerId /*rootPlayerId*/,
-            int /*currentPlayerFlips*/,
-            int /*maxPlayerFlips*/) const = 0;
-
-    // Check if a state is terminal
-    [[nodiscard]] virtual bool isTerminal(const MCTSGameState& state) const = 0;
-
-    // Evaluate a state from the perspective of a player
-    [[nodiscard]] virtual double evaluateState(const MCTSGameState& state, MCTSPlayerId playerId)
-            const = 0;
-
-    // Filter actions based on game-specific heuristics
-    // Returns indices of actions to keep
-    // Default: no filtering (return all indices)
-    [[nodiscard]] virtual std::vector<size_t> filterActions(
-            const std::vector<std::unique_ptr<MCTSAction>>& actions,
-            const MCTSGameState& /*state*/) const {
-        std::vector<size_t> indices;
-        indices.reserve(actions.size());
-        for (size_t i = 0; i < actions.size(); ++i) { indices.push_back(i); }
-        return indices;
-    }
-
-    // Get heuristic weights for actions (used by WEIGHTED_HEURISTIC simulation policy)
-    // Returns weights corresponding to each action (same size as actions vector)
-    // Weight of 0.0 = never select, higher = more likely to select
-    // Default: uniform weights (all actions equally likely)
-    [[nodiscard]] virtual std::vector<double> getActionWeights(
-            const std::vector<std::unique_ptr<MCTSAction>>& actions,
-            const MCTSGameState& /*state*/) const {
-        // Default: uniform weights
-        return std::vector<double>(actions.size(), 1.0);
-    }
-
-    // Simulate a random playout from the given state
-    // Default implementation uses policy to select actions
-    [[nodiscard]] virtual double simulateRandomPlayout(
-            const MCTSGameState& state,
-            MCTSPlayerId playerId,
-            int maxDepth,
-            MCTSSimulationPolicy policy) const;
-
-    // Get the immediate score of applying an action
-    // Default: apply the action and evaluate the resulting state
-    [[nodiscard]] virtual double getActionScore(
-            const MCTSGameState& state,
-            const MCTSAction& action,
-            MCTSPlayerId playerId) const {
-        auto newState = applyAction(state, action);
-        if (!newState) { return 0.0; }
-        return evaluateState(*newState, playerId);
-    }
-
-    // Check if we should stop searching (e.g., time limit, found winning move)
-    [[nodiscard]] virtual bool shouldStopSearch(
-            const MCTSGameState& /*state*/,
-            int /*iterations*/,
-            std::chrono::steady_clock::time_point /*startTime*/) const {
-        // Default: no early stopping
-        return false;
-    }
-
-    // Map a filtered action index back to the original unfiltered index
-    // This is needed when getLegalActions() applies filtering - the returned actions
-    // may be a subset of all available actions, and this maps back to the original index.
-    // Default implementation: no filtering, so filtered index = original index
-    [[nodiscard]] virtual size_t mapFilteredIndexToOriginal(
-            size_t filteredIndex,
-            const MCTSGameState& state) const {
-        // Default: no filtering, index stays the same
-        (void)state;  // Suppress unused parameter warning
-        return filteredIndex;
-    }
-
-    // Get binary outcome information for an action that requires a chance node
-    // Only called for actions where action.requiresChanceNode() returns true
-    // Returns success probability for binary success/failure actions
-    [[nodiscard]] virtual BinaryOutcomeInfo getBinaryOutcomeInfo(
-            const MCTSGameState& state,
-            const MCTSAction& action) const = 0;
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_GAME_ENGINE_HPP
@@ -1,50 +0,0 @@
-//
-// Abstract game state interface for MCTS
-//
-
-#ifndef EAGLE0_MCTS_GAME_STATE_HPP
-#define EAGLE0_MCTS_GAME_STATE_HPP
-
-#include <cstdint>
-#include <memory>
-#include <string>
-
-#include "MCTSTypes.hpp"
-
-namespace shardok {
-namespace mcts {
-
-// Abstract interface for game states
-class MCTSGameState {
-public:
-    virtual ~MCTSGameState() = default;
-
-    // Compute hash for transposition table
-    [[nodiscard]] virtual uint64_t hash() const = 0;
-
-    // Evaluate the state from the perspective of the given player
-    [[nodiscard]] virtual double score(MCTSPlayerId playerId) const = 0;
-
-    // Get the player whose turn it is
-    [[nodiscard]] virtual MCTSPlayerId currentPlayerId() const = 0;
-
-    // Check if the game has ended
-    [[nodiscard]] virtual bool isTerminal() const = 0;
-
-    // Create a deep copy of the state
-    [[nodiscard]] virtual std::unique_ptr<MCTSGameState> clone() const = 0;
-
-    // Check if two states are equivalent
-    [[nodiscard]] virtual bool equals(const MCTSGameState& other) const = 0;
-
-    // Get winner if terminal, or -1 if not terminal or draw
-    [[nodiscard]] virtual MCTSPlayerId getWinner() const = 0;
-
-    // Optional: Get a string representation for debugging
-    [[nodiscard]] virtual std::string toString() const { return "MCTSGameState"; }
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_GAME_STATE_HPP
@@ -1,277 +0,0 @@
-//
-// Abstract MCTS Node structure for game-agnostic implementation
-//
-
-#ifndef EAGLE0_ABSTRACT_MCTSNODE_HPP
-#define EAGLE0_ABSTRACT_MCTSNODE_HPP
-
-#include <cmath>
-#include <limits>
-#include <memory>
-#include <vector>
-
-#include "MCTSAction.hpp"
-#include "MCTSGameState.hpp"
-#include "MCTSTypes.hpp"
-
-namespace shardok {
-namespace mcts {
-
-// Node type for MCTS tree
-enum class NodeType {
-    DECISION,  // Player chooses an action (standard MCTS node)
-    CHANCE     // Nature determines outcome (for probabilistic actions)
-};
-
-// Abstract MCTS Node structure
-struct MCTSNode {
-    // Node type
-    NodeType nodeType = NodeType::DECISION;
-    // Action information
-    std::unique_ptr<MCTSAction> action;  // The action that led to this node (null for root)
-    size_t actionIndex = SIZE_MAX;       // Index in the original actions array (SIZE_MAX for root)
-
-    // Score information
-    double immediateScore = 0.0;
-    double lookaheadScore = 0.0;
-
-    // Game state after this action
-    std::unique_ptr<MCTSGameState> gameState;
-
-    // MCTS statistics
-    int visitCount = 0;
-    double totalReward = 0.0;
-    double averageReward = 0.0;
-    mutable double ucb1Value = 0.0;
-    double actionWeight = 1.0;  // Prior probability/weight for this action (from heuristics)
-
-    // Tree structure
-    std::vector<std::unique_ptr<MCTSNode>> children;
-    size_t nextUntriedActionIndex = 0;  // Next action to expand
-    size_t totalActions = 0;            // Total number of available actions
-    MCTSNode* parent = nullptr;
-
-    // Chance node specific fields (only used when nodeType == CHANCE)
-    std::vector<double> outcomeProbabilities;  // Probability of each outcome
-    std::vector<double> outcomeRolls;          // Representative roll for each outcome
-
-    // Game context
-    MCTSPlayerId playerId;
-    int depth = 0;
-    bool isTerminal = false;
-    int playerFlips = 0;  // Number of times the active player has changed from root player
-    bool isMaximizingPlayer = true;  // True if this node is maximizing for root player
-
-    // Transposition detection
-    uint64_t stateHash = 0;
-    bool isRedundant = false;  // True if this node represents a duplicate state
-
-    // Constructor for root node
-    MCTSNode(std::unique_ptr<MCTSGameState> state, MCTSPlayerId pid, int d)
-        : gameState(std::move(state)),
-          playerId(pid),
-          depth(d),
-          playerFlips(0),
-          isMaximizingPlayer(true) {
-        if (gameState) {
-            stateHash = gameState->hash();
-            isTerminal = gameState->isTerminal();
-        }
-    }
-
-    // Constructor for child node
-    MCTSNode(
-            std::unique_ptr<MCTSAction> act,
-            std::unique_ptr<MCTSGameState> state,
-            MCTSPlayerId pid,
-            int d,
-            size_t actIdx = SIZE_MAX,
-            int flips = 0,
-            bool isMaximizing = true,
-            double weight = 1.0)
-        : action(std::move(act)),
-          actionIndex(actIdx),
-          gameState(std::move(state)),
-          actionWeight(weight),
-          playerId(pid),
-          depth(d),
-          playerFlips(flips),
-          isMaximizingPlayer(isMaximizing) {
-        if (gameState) {
-            stateHash = gameState->hash();
-            isTerminal = gameState->isTerminal();
-        }
-    }
-
-    // Iterative destructor to avoid stack overflow with deep trees
-    ~MCTSNode() {
-        std::vector<std::unique_ptr<MCTSNode>> nodesToDestroy;
-        nodesToDestroy.swap(children);
-
-        while (!nodesToDestroy.empty()) {
-            std::vector<std::unique_ptr<MCTSNode>> currentBatch;
-            currentBatch.swap(nodesToDestroy);
-
-            for (const auto& node : currentBatch) {
-                if (node && !node->children.empty()) {
-                    for (auto& child : node->children) {
-                        nodesToDestroy.push_back(std::move(child));
-                    }
-                    node->children.clear();
-                }
-            }
-        }
-    }
-
-    // Calculate UCB1 value for this node from parent's perspective
-    // Uses prior-weighted formula similar to AlphaGo:
-    //   UCB = Q + c * P * sqrt(N_parent) / (1 + N_child)
-    // Where P is the action weight (prior probability from heuristics)
-    [[nodiscard]] double CalculateUCB1(
-            const double explorationConstant,
-            const int parentVisitCount,
-            const bool parentIsMaximizing) const {
-        // Exploitation: use lookahead score (minimax value)
-        // For minimizing nodes, negate the score to prefer low child values
-        const double exploitationValue = parentIsMaximizing ? lookaheadScore : -lookaheadScore;
-
-        // Exploration: prior-weighted formula (AlphaGo-style)
-        // Actions with weight 0.0 (like FLEE_COMMAND) get no exploration bonus
-        // Unvisited nodes get: c * weight * sqrt(N_parent)
-        // This prevents bad actions from dominating exploration due to infinite UCB
-        const double explorationValue = explorationConstant * actionWeight *
-                                        std::sqrt(parentVisitCount) / (1.0 + visitCount);
-
-        return exploitationValue + explorationValue;
-    }
-
-    // Check if this node can be expanded
-    [[nodiscard]] bool CanExpand() const { return nextUntriedActionIndex < totalActions; }
-
-    // Check if this is a chance node
-    [[nodiscard]] bool IsChanceNode() const { return nodeType == NodeType::CHANCE; }
-
-    // Check if this is a decision node
-    [[nodiscard]] bool IsDecisionNode() const { return nodeType == NodeType::DECISION; }
-
-    // Get best child from chance node (probability-weighted selection)
-    // For chance nodes, we want to explore outcomes proportionally to their probability
-    [[nodiscard]] MCTSNode* GetBestChanceChild() const {
-        if (children.empty() || !IsChanceNode()) return nullptr;
-
-        // Find the outcome that is most under-explored relative to its probability
-        // Expected visits for outcome i: total_visits * probability[i]
-        // Actual visits: child[i]->visitCount
-        // Deficit: expected - actual
-        size_t bestIndex = 0;
-        double bestDeficit = -std::numeric_limits<double>::max();
-
-        for (size_t i = 0; i < children.size(); i++) {
-            if (!children[i] || children[i]->isRedundant) continue;
-
-            const double expectedVisits = visitCount * outcomeProbabilities[i];
-            const double actualVisits = static_cast<double>(children[i]->visitCount);
-            const double deficit = expectedVisits - actualVisits;
-
-            if (deficit > bestDeficit) {
-                bestDeficit = deficit;
-                bestIndex = i;
-            }
-        }
-
-        return children[bestIndex].get();
-    }
-
-    // Get best child based on UCB1
-    [[nodiscard]] MCTSNode* GetBestChild(const double explorationConstant) const {
-        if (children.empty()) return nullptr;
-
-        MCTSNode* bestChild = nullptr;
-        double bestValue = -std::numeric_limits<double>::max();
-
-        for (auto& child : children) {
-            // Skip redundant nodes
-            if (child->isRedundant) continue;
-
-            // Calculate UCB1 value using the helper function
-            const double value =
-                    child->CalculateUCB1(explorationConstant, visitCount, isMaximizingPlayer);
-
-            // Debug logging for UCB selection
-            static bool enableUCBDebug = false;
-            if (enableUCBDebug && child->visitCount > 0) {
-                const double exploitationValue =
-                        isMaximizingPlayer ? child->lookaheadScore : -child->lookaheadScore;
-                const double explorationValue =
-                        explorationConstant * std::sqrt(std::log(visitCount) / child->visitCount);
-                printf("    UCB: %s lookahead=%.2f expl=%.2f (+%.2f) = %.2f [%s]\n",
-                       isMaximizingPlayer ? "MAX" : "MIN",
-                       child->lookaheadScore,
-                       exploitationValue,
-                       explorationValue,
-                       value,
-                       child->action ? child->action->getDescription().c_str() : "root");
-            }
-
-            if (value > bestValue) {
-                bestValue = value;
-                bestChild = child.get();
-            }
-        }
-
-        return bestChild;
-    }
-
-    // Get best child based on visit count (for final selection)
-    [[nodiscard]] MCTSNode* GetBestFinalChild() const {
-        if (children.empty()) return nullptr;
-
-        MCTSNode* bestChild = nullptr;
-        int bestVisits = 0;
-        double bestScore = isMaximizingPlayer ? -std::numeric_limits<double>::max()
-                                              : std::numeric_limits<double>::max();
-
-        for (const auto& child : children) {
-            // Skip redundant nodes
-            if (child->isRedundant) continue;
-
-            // Prefer most-visited node (robust child selection)
-            if (child->visitCount > bestVisits) {
-                bestVisits = child->visitCount;
-                bestScore = child->lookaheadScore;
-                bestChild = child.get();
-            } else if (child->visitCount == bestVisits) {
-                // Tie-break on lookahead score (minimax value, not poisoned average)
-                // Maximizing: prefer higher score (better for root player)
-                // Minimizing: prefer lower score (worse for root player)
-                const bool shouldReplace = isMaximizingPlayer ? (child->lookaheadScore > bestScore)
-                                                              : (child->lookaheadScore < bestScore);
-                if (shouldReplace) {
-                    bestScore = child->lookaheadScore;
-                    bestChild = child.get();
-                }
-            }
-        }
-
-        // If no child was visited, fall back to lookahead score
-        if (!bestChild && !children.empty()) {
-            for (const auto& child : children) {
-                if (child->isRedundant) continue;
-
-                const bool shouldReplace = isMaximizingPlayer ? (child->lookaheadScore > bestScore)
-                                                              : (child->lookaheadScore < bestScore);
-                if (shouldReplace) {
-                    bestScore = child->lookaheadScore;
-                    bestChild = child.get();
-                }
-            }
-        }
-
-        return bestChild;
-    }
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_ABSTRACT_MCTSNODE_HPP
@@ -1,60 +0,0 @@
-//
-// Core types for abstract MCTS implementation
-//
-
-#ifndef EAGLE0_MCTS_TYPES_HPP
-#define EAGLE0_MCTS_TYPES_HPP
-
-#include <stdexcept>
-#include <string>
-
-namespace shardok {
-namespace mcts {
-
-// Exception thrown when MCTS encounters an internal error that indicates a bug
-class MCTSInternalError : public std::logic_error {
-public:
-    explicit MCTSInternalError(const std::string& message) : std::logic_error(message) {}
-};
-
-// Abstract player identifier type
-using MCTSPlayerId = int;
-
-// Simulation policy for MCTS rollouts
-enum class MCTSSimulationPolicy {
-    RANDOM,                   // Pure random selection
-    FILTERED_RANDOM,          // Random from filtered actions
-    BEST_IMMEDIATE,           // Choose best immediate score
-    WEIGHTED_BEST_IMMEDIATE,  // Random weighted by score ranking
-    WEIGHTED_HEURISTIC        // Random weighted by fast heuristics (no score evaluation)
-};
-
-// Backpropagation policy for MCTS tree updates
-enum class MCTSBackpropagationPolicy {
-    AVERAGING,  // Traditional MCTS averaging (for stochastic/single-player games)
-    MINIMAX     // Minimax backup (for deterministic adversarial games)
-};
-
-// Configuration for MCTS algorithm
-struct MCTSConfig {
-    double explorationConstant = 1.414;  // UCB1 constant (sqrt(2) by default)
-    int maxSimulationDepth = 1000;       // Maximum depth for rollout
-    int maxTreeDepth = 2000;             // Maximum tree depth to prevent stack overflow
-    bool useMultithreading = true;       // Enable parallel MCTS
-    int numThreads = 16;                 // Number of threads for parallel MCTS
-    MCTSSimulationPolicy simulationPolicy = MCTSSimulationPolicy::BEST_IMMEDIATE;
-    MCTSBackpropagationPolicy backpropagationPolicy = MCTSBackpropagationPolicy::AVERAGING;
-    int maxPlayerFlips = 0;          // Maximum number of player changes for tree expansion
-                                     // (0 = expand through current player's turn only,
-                                     //  1 = expand through opponent's first response, etc.)
-    int maxSimulationFlips = 0;      // Maximum player flips for leaf evaluation
-                                     // When evaluating a leaf at playerFlips < maxSimulationFlips,
-                                     // simulate forward to this phase for fair comparison
-                                     // (default 0 = evaluate leaves as-is, backward compatible)
-    std::string debugDumpPath = "";  // If non-empty, dump MCTS tree to this file path
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_MCTS_TYPES_HPP
@@ -1,8 +0,0 @@
-load("@rules_cc//cc:defs.bzl", "cc_library")
-
-cc_library(
-    name = "tree_indent_util",
-    srcs = ["TreeIndentUtil.cpp"],
-    hdrs = ["TreeIndentUtil.hpp"],
-    visibility = ["//visibility:public"],
-)
@@ -1,53 +0,0 @@
-//
-// Utility functions for processing tree indentation with UTF-8 box drawing characters
-//
-
-#include "TreeIndentUtil.hpp"
-
-namespace mcts::util {
-
-namespace {
-// Box drawing characters for tree visualization
-constexpr const char* kBranch = "\xE2\x94\x9C";      // ├
-constexpr const char* kCorner = "\xE2\x94\x94";      // └
-constexpr const char* kVertical = "\xE2\x94\x82";    // │
-constexpr const char* kHorizontal = "\xE2\x94\x80";  // ─
-}  // namespace
-
-std::string BuildTreeIndent(int indentLevel, bool isLastChild) {
-    std::string indent;
-
-    for (int i = 0; i < indentLevel; ++i) {
-        if (i == indentLevel - 1) {
-            indent += isLastChild ? kCorner : kBranch;
-            indent += kHorizontal;
-            indent += " ";
-        } else {
-            indent += "   ";
-        }
-    }
-
-    return indent;
-}
-
-std::string ConvertBranchToContinuation(const std::string& indent) {
-    std::string result = indent;
-
-    const std::string replacement = std::string(kVertical) + "  ";
-
-    // Replace ├ and └ with │
-    size_t pos = 0;
-    while ((pos = result.find(kBranch, pos)) != std::string::npos) {
-        result.replace(pos, 3, replacement);  // UTF-8 chars are 3 bytes
-        pos += replacement.size();
-    }
-    pos = 0;
-    while ((pos = result.find(kCorner, pos)) != std::string::npos) {
-        result.replace(pos, 3, replacement);
-        pos += replacement.size();
-    }
-
-    return result;
-}
-
-}  // namespace mcts::util
@@ -1,22 +0,0 @@
-//
-// Utility functions for processing tree indentation with UTF-8 box drawing characters
-//
-
-#ifndef EAGLE0_TREE_INDENT_UTIL_HPP
-#define EAGLE0_TREE_INDENT_UTIL_HPP
-
-#include <string>
-
-namespace mcts::util {
-
-// Builds tree indentation string for a node at a given depth
-// Returns string like "   ├─ " or "   └─ " with proper spacing
-std::string BuildTreeIndent(int indentLevel, bool isLastChild);
-
-// Converts tree branch characters (├ and └) to continuation lines (│) for sub-content
-// This preserves the tree structure when displaying additional info below a node
-std::string ConvertBranchToContinuation(const std::string& indent);
-
-}  // namespace mcts::util
-
-#endif  // EAGLE0_TREE_INDENT_UTIL_HPP
@@ -4,11 +4,11 @@

 #include "AIAttackGroups.hpp"

-#include <cstdlib>
 #include <iterator>
 #include <ranges>
 #include <unordered_map>

+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"

 namespace shardok {
@@ -75,28 +75,30 @@ auto MinDistanceIncludingBraving(
 auto EffectiveDistance(
        const Unit* unit,
        const HexMap* map,
-        const AttackLocations& attackLocations,
+        const MapId& mapId,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> DIST_T {
+        const AttackLocations& attackLocations,
+        const SettingsGetter& settings,
+        const int braveWaterCost) -> DIST_T {
    return EffectiveDistance(
            unit,
            map,
-            attackLocations.LocationsWithEnemyInRange(unit),
+            mapId,
            apdCache,
-            battalionTypeGetter,
+            attackLocations.LocationsWithEnemyInRange(unit),
+            settings,
            braveWaterCost);
 }

 auto EffectiveDistance(
        const Unit* unit,
        const HexMap* map,
-        const CoordsSet& locations,
+        const MapId& mapId,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> DIST_T {
-    const auto mapId = ActionPointDistancesCache::GetMapId(map);
-    const auto& battType = battalionTypeGetter(unit->battalion().type());
+        const CoordsSet& locations,
+        const SettingsGetter& settings,
+        const int braveWaterCost) -> DIST_T {
+    const auto& battType = settings.GetBattalionType(unit->battalion().type());
    const auto* notBravingApd = apdCache->GetRaw(map, mapId, battType, false);
    const ActionPointDistances* bravingApd = nullptr;
    if (battType->allowsBraveWater) {
@@ -129,12 +131,12 @@ auto GenerateTargetPriorities(
        const vector<const Unit*>& remainingUnits,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const MapId& mapId,
+        const SettingsGetter& settings,
        const bool isLateGame) -> vector<TargetPriorityList> {
    auto cc = map->column_count();

-    const auto mapId = ActionPointDistancesCache::GetMapId(map);
+    const auto braveWaterCost = settings.Backing().brave_water_action_point_cost();

    vector<TargetPriorityList> allTargetsUnitsAndDistances{};
    allTargetsUnitsAndDistances.reserve(remainingUnits.size());
@@ -158,7 +160,7 @@ auto GenerateTargetPriorities(
        vector<TargetAndDistance> targetsWithDistance;

        // Get APDs directly from cache (now with built-in thread-local optimization)
-        const auto& battType = battalionTypeGetter(unit->battalion().type());
+        const auto& battType = settings.GetBattalionType(unit->battalion().type());
        const auto* notBravingApd = apdCache->GetRaw(map, mapId, battType, false);
        const ActionPointDistances* bravingApd = nullptr;
        if (battType->allowsBraveWater) {
@@ -5,12 +5,12 @@
 #ifndef EAGLE0_AIATTACKGROUPS_HPP
 #define EAGLE0_AIATTACKGROUPS_HPP

-#include <functional>
 #include <vector>

 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/player_info.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/unit.hpp"
@@ -22,8 +22,6 @@ using Unit = net::eagle0::shardok::storage::fb::Unit;
 using net::eagle0::shardok::storage::fb::PlayerInfo;
 using std::vector;

-using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
-
 struct TargetAndAttackLocations {
    Coords target;
    CoordsSet attackLocations;
@@ -43,18 +41,20 @@ struct TargetPriorityList {
 auto EffectiveDistance(
        const Unit* unit,
        const HexMap* map,
-        const AttackLocations& attackLocations,
+        const MapId& mapId,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> DIST_T;
+        const AttackLocations& attackLocations,
+        const SettingsGetter& settings,
+        int braveWaterCost) -> DIST_T;

 auto EffectiveDistance(
        const Unit* unit,
        const HexMap* map,
-        const CoordsSet& locations,
+        const MapId& mapId,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> DIST_T;
+        const CoordsSet& locations,
+        const SettingsGetter& settings,
+        int braveWaterCost) -> DIST_T;

 auto EffectiveDistance(
        const Unit* unit,
@@ -71,8 +71,8 @@ auto GenerateTargetPriorities(
        const vector<const Unit*>& remainingUnits,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const MapId& mapId,
+        const SettingsGetter& settings,
        bool isLateGame = false) -> vector<TargetPriorityList>;

 }  // namespace shardok
@@ -4,7 +4,6 @@

 #include "AIAttackerStrategySelector.hpp"

-#include "AIAttackGroups.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIFleeDecisionCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
@@ -21,13 +20,11 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
        const PlayerId attackerPid,
        const GameStateW& gameState,
        const CoordsSet& criticalTileCoords,
-        int maxRounds,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter& settings,
        const AIWaterCrossingCommandChooser& waterCrossingCommandChooser,
-        const CommandListSPtr& /*availableCommands*/) -> AIStrategy {
+        const vector<CommandProto>& /*availableCommands*/) -> AIStrategy {
    uint32_t attackerUnitCount = 0;
    int defenderOccupiedCriticalTileCount = 0;
    bool canFlee = false;
@@ -66,14 +63,12 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
    if (canFlee && AIFleeDecisionCalculator::ShouldConsiderFleeing(
                           attackerPid,
                           gameState,
-                           maxRounds,
+                           settings,
                           FLEE_CONSIDERATION_THRESHOLD)) {
        chosenStrategy = FleeStrategy;
    } else if (const CoordsSet startCrossingLocations =
-                       waterCrossingCommandChooser.StartCrossingFrom(
-                               battalionTypeGetter,
-                               gameState,
-                               criticalTileCoords);
+                       waterCrossingCommandChooser
+                               .StartCrossingFrom(settings, gameState, criticalTileCoords);
               !startCrossingLocations.empty()) {
        chosenStrategy = CrossRiversStrategy(startCrossingLocations);
    } else if (attackerUnitCount < criticalTileCoords.size()) {
@@ -88,8 +83,8 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
                attackerUnits,
                apdCache,
                alCache,
-                battalionTypeGetter,
-                braveWaterCost));
+                ActionPointDistancesCache::GetMapId(gameState->hex_map()),
+                settings));
    }
    // If any critical tile is occupied by the defender, attack the castles.
    // Otherwise, try to hold the castles.
@@ -105,8 +100,8 @@ auto AIAttackerStrategySelector::BestAttackerStrategy(
                attackerUnits,
                apdCache,
                alCache,
-                battalionTypeGetter,
-                braveWaterCost));
+                ActionPointDistancesCache::GetMapId(gameState->hex_map()),
+                settings));
    } else {
        chosenStrategy = HoldCastlesStrategy;
    }
@@ -6,12 +6,9 @@
 #define EAGLE0_AIATTACKERSTRATEGYSELECTOR_HPP

 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCommandChooser.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"

 namespace shardok {
@@ -22,13 +19,11 @@ public:
            PlayerId attackerPid,
            const GameStateW& gameState,
            const CoordsSet& criticalTileCoords,
-            int maxRounds,
            const APDCache& apdCache,
            const ALCache& alCache,
-            const BattalionTypeGetter& battalionTypeGetter,
-            ActionPoints braveWaterCost,
+            const SettingsGetter& settings,
            const AIWaterCrossingCommandChooser& waterCrossingCommandChooser,
-            const CommandListSPtr& availableCommands) -> AIStrategy;
+            const vector<CommandProto>& availableCommands) -> AIStrategy;
 };

 }  // namespace shardok
@@ -1,560 +0,0 @@
-//
-// Command evaluator for AI lookahead search.
-// Extracted from AIScoreCalculator to separate concerns.
-//
-
-#include "AICommandEvaluator.hpp"
-
-#include <chrono>
-#include <cmath>
-#include <future>
-#include <limits>
-
-#include "AICommandFilter.hpp"
-#include "TranspositionTable.hpp"
-#include "src/main/cpp/net/eagle0/common/SequenceRandomGenerator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/util/HexCubeUtils.hpp"
-
-namespace shardok {
-
-// No need to forward declare internal functions - use the public interface instead
-
-// Helper constants and static variables
-static const std::vector<double> _averageSequence = {0.5};
-static const auto _averageGenerator = std::make_shared<SequenceRandomGenerator>(_averageSequence);
-
-#define MULTITHREAD true
-#define LOGGING_ 0
-
-// Helper function to determine if a command type is deterministic
-static auto IsDeterministic(const CommandType type) -> bool {
-    switch (type) {
-        case net::eagle0::shardok::common::MOVE_COMMAND:
-        case net::eagle0::shardok::common::CONTROL_COMMAND:
-        case net::eagle0::shardok::common::METEOR_START_COMMAND:
-        case net::eagle0::shardok::common::METEOR_TARGET_COMMAND:
-        case net::eagle0::shardok::common::METEOR_CANCEL_COMMAND:
-        case net::eagle0::shardok::common::END_TURN_COMMAND:
-        case net::eagle0::shardok::common::PLACE_UNIT_COMMAND:
-        case net::eagle0::shardok::common::PLACE_HIDDEN_UNIT_COMMAND:
-        case net::eagle0::shardok::common::UNIT_STOP_COMMAND:
-        case net::eagle0::shardok::common::UNIT_REST_COMMAND:
-        case net::eagle0::shardok::common::FLEE_COMMAND:
-        case net::eagle0::shardok::common::REINFORCE_COMMAND:
-        case net::eagle0::shardok::common::RETREAT_COMMAND:
-        case net::eagle0::shardok::common::END_PLAYER_SETUP_COMMAND:
-        case net::eagle0::shardok::common::HIDE_COMMAND:
-        case net::eagle0::shardok::common::FORTIFY_COMMAND:
-        case net::eagle0::shardok::common::BECOME_OUTLAW_COMMAND:
-        case net::eagle0::shardok::common::HOLY_WAVE_COMMAND:
-        case net::eagle0::shardok::common::REPAIR_COMMAND: return true;
-        default: return false;
-    }
-}
-
-// Helper function to sort commands by score
-static auto CommandSorter(
-        const AICommandEvaluator::IndexAndScore& l,
-        const AICommandEvaluator::IndexAndScore& r) -> bool {
-    if (l.lookaheadScore < r.lookaheadScore) return true;
-    if (l.lookaheadScore > r.lookaheadScore) return false;
-
-    // At this point the scores are tied
-    if (l.immediateScore < r.immediateScore) return true;
-    if (l.immediateScore > r.immediateScore) return false;
-
-    return false;
-}
-
-AICommandEvaluator::AICommandEvaluator(
-        const AIScoreCalculator& scorer,
-        const APDCache& apdCache,
-        BattalionTypeGetter battalionTypeGetter)
-    : scorer_(scorer),
-      apdCache_(apdCache),
-      battalionTypeGetter_(std::move(battalionTypeGetter)) {}  // Move the function object
-
-auto AICommandEvaluator::PerformLookahead(
-        const PlayerId pid,
-        const bool isDefender,
-        const int remainingLookahead,
-        const int maxRepeatCount,
-        const std::shared_ptr<ShardokEngine>& innerEngine,
-        const ScoreValue currentUtility,
-        const AIStrategy& attackerStrategy,
-        const CoordsSet& allCastleCoords,
-        std::chrono::steady_clock::time_point deadline) const -> std::future<ScoreValue> {
-    // Check transposition table before expensive computation
-    auto cachedScore =
-            g_transpositionTable.probe(innerEngine->GetCurrentGameState(), remainingLookahead, pid);
-
-    if (cachedScore.has_value()) {
-        // Return cached result immediately
-        std::promise<ScoreValue> p;
-        p.set_value(*cachedScore);
-        return p.get_future();
-    }
-    const auto nextUtility = currentUtility;
-
-    // Check if we've reached the depth limit before making recursive calls
-    if (remainingLookahead <= 0) {
-        // Store the current utility in the transposition table and return it
-        // Note: Store with depth 1 since depth 0 indicates an empty entry in the transposition
-        // table
-        g_transpositionTable.store(innerEngine->GetCurrentGameState(), 1, pid, nextUtility);
-
-        std::promise<ScoreValue> p;
-        p.set_value(nextUtility);
-        return p.get_future();
-    }
-
-    if (const CommandListSPtr nextCommands = innerEngine->GetAvailableCommandsForAIPlayer(pid);
-        nextCommands && !nextCommands->empty()) {
-        // Get the future from FindBestCommand without calling .get()
-        auto bestCommandFuture = FindBestCommand(
-                pid,
-                isDefender,
-                remainingLookahead - 1,
-                maxRepeatCount,
-                *innerEngine,
-                attackerStrategy,
-                nextUtility,
-                allCastleCoords,
-                deadline);
-
-        // Return a future that chains the best command evaluation
-        return std::async(
-                std::launch::deferred,
-                [bestCommandFuture = std::move(bestCommandFuture),
-                 innerEngine,
-                 pid,
-                 nextUtility,
-                 remainingLookahead]() mutable -> ScoreValue {
-                    const auto [index, type, lookaheadScore, immediateScore] =
-                            bestCommandFuture.get();
-
-                    ScoreValue resultScore;
-                    if (auto& nextCommand =
-                                innerEngine->GetAvailableCommandsForAIPlayer(pid)->at(index);
-                        nextCommand->GetCommandType() !=
-                        net::eagle0::shardok::common::END_TURN_COMMAND) {
-                        resultScore = immediateScore;
-                    } else {
-                        resultScore = nextUtility;
-                    }
-
-                    // Store in transposition table before returning
-                    g_transpositionTable.store(
-                            innerEngine->GetCurrentGameState(),
-                            remainingLookahead,
-                            pid,
-                            resultScore);
-
-                    return resultScore;
-                });
-    }
-
-    // No commands available, store and return the current utility as a future
-    g_transpositionTable
-            .store(innerEngine->GetCurrentGameState(), remainingLookahead, pid, nextUtility);
-
-    std::promise<ScoreValue> p;
-    p.set_value(nextUtility);
-    return p.get_future();
-}
-
-auto AICommandEvaluator::EvaluateWithRandomness(
-        const PlayerId pid,
-        const bool isDefender,
-        const uint32_t commandIndex,
-        const int remainingLookahead,
-        const int maxRepeatCount,
-        const std::shared_ptr<RandomGenerator>& randomGenerator,
-        const ShardokEngine& guessedEngine,
-        const AIStrategy& attackerStrategy,
-        const CoordsSet& allCastleCoords,
-        std::chrono::steady_clock::time_point deadline) const -> ImmediateAndLookaheadScore {
-    ImmediateAndLookaheadScore returnValue{};
-
-    // Check if we've exceeded the deadline
-    if (std::chrono::steady_clock::now() > deadline) {
-        // Return with a default score and an empty future that resolves immediately
-        std::promise<ScoreValue> p;
-        p.set_value(0.0);  // Default timeout score
-        returnValue.immediateScore = 0.0;
-        returnValue.lookaheadScore = p.get_future();
-        return returnValue;
-    }
-
-    auto innerEngine = std::make_shared<ShardokEngine>(guessedEngine, false);
-    innerEngine->PostCommand(pid, commandIndex, randomGenerator);
-
-    auto innerUtility = scorer_.GuessedStateScore(
-            isDefender,
-            innerEngine->GetCurrentGameState(),
-            attackerStrategy,
-            allCastleCoords);
-
-    returnValue.immediateScore = innerUtility;
-
-    if (remainingLookahead <= 0) {
-        std::promise<ScoreValue> p;
-        returnValue.lookaheadScore = p.get_future();
-        p.set_value(innerUtility);
-    } else {
-        auto lookaheadLambda = [this,
-                                pid,
-                                isDefender,
-                                remainingLookahead,
-                                maxRepeatCount,
-                                innerEngine,
-                                attackerStrategy,
-                                innerUtility,
-                                &allCastleCoords,
-                                deadline]() -> ScoreValue {
-            auto lookaheadFuture = PerformLookahead(
-                    pid,
-                    isDefender,
-                    remainingLookahead,
-                    maxRepeatCount,
-                    innerEngine,
-                    innerUtility,
-                    attackerStrategy,
-                    allCastleCoords,
-                    deadline);
-            return lookaheadFuture.get();
-        };
-
-#if MULTITHREAD
-        auto launchPolicy = remainingLookahead == 1 ? std::launch::async : std::launch::deferred;
-        returnValue.lookaheadScore = std::async(launchPolicy, lookaheadLambda);
-#else
-        std::promise<ScoreValue> p;
-        returnValue.lookaheadScore = p.get_future();
-        auto lambdaResult = lookaheadLambda();
-        p.set_value(lambdaResult);
-#endif
-    }
-
-    return returnValue;
-}
-
-auto AICommandEvaluator::FindBestCommand(
-        const PlayerId pid,
-        const bool isDefender,
-        const int remainingLookahead,
-        const int maxRepeatCount,
-        const ShardokEngine& guessedEngine,
-        const AIStrategy& attackerStrategy,
-        const ScoreValue currentUtility,
-        const CoordsSet& allCastleCoords,
-        std::chrono::steady_clock::time_point deadline) const -> std::future<IndexAndScore> {
-    const CommandListSPtr guessedDescriptors = guessedEngine.GetAvailableCommandsForAIPlayer(pid);
-
-    // Filter out obviously bad commands to reduce search space
-    const std::vector<size_t> filteredIndices = AICommandFilter::FilterCommands(
-            guessedDescriptors,
-            pid,
-            isDefender,
-            guessedEngine.GetCurrentGameState(),
-            apdCache_,
-            battalionTypeGetter_);
-
-    const auto& gameState = guessedEngine.GetCurrentGameState();
-    // Calculate minimum hex distance to enemies for this player
-    double minDistToEnemies = std::numeric_limits<double>::max();
-    const auto* units = gameState->units();
-
-    for (size_t i = 0; i < units->size(); ++i) {
-        if (const auto* playerUnit = units->Get(static_cast<unsigned int>(i));
-            playerUnit->player_id() == pid) {
-            const auto& playerCoords = playerUnit->location();
-
-            for (size_t j = 0; j < units->size(); ++j) {
-                if (const auto* enemyUnit = units->Get(static_cast<unsigned int>(j));
-                    enemyUnit->player_id() != pid) {
-                    const auto& enemyCoords = enemyUnit->location();
-
-                    // Proper hex distance calculation using cube coordinates
-                    const Cube playerCube = OffsetToCube(playerCoords);
-                    const Cube enemyCube = OffsetToCube(enemyCoords);
-                    const int hexDistance = CubeDistance(playerCube, enemyCube);
-
-                    minDistToEnemies = std::min(minDistToEnemies, static_cast<double>(hexDistance));
-                }
-            }
-        }
-    }
-
-    if (minDistToEnemies == std::numeric_limits<double>::max()) {
-        minDistToEnemies = 0.0;  // No enemies found
-    }
-
-#if LOGGING_
-    // Log command count and distance metrics for performance analysis
-    const auto allCommandCount = guessedDescriptors->size();
-    const auto filteredCommandCount = filteredIndices.size();
-    const int currentRound = gameState->current_round();
-
-    printf("AI_COMMAND_COUNT: Round %d, Player %d, Defender %d, MinDist %.1f, Commands %zu -> %zu "
-           "(%.1f%% filtered)\n",
-           currentRound,
-           static_cast<int>(pid),
-           isDefender ? 1 : 0,
-           minDistToEnemies,
-           allCommandCount,
-           filteredCommandCount,
-           100.0 * (allCommandCount - filteredCommandCount) / allCommandCount);
-#endif
-
-    const auto commandCount = filteredIndices.size();
-
-    // Structure to hold all command evaluation data
-    struct CommandEvaluation {
-        size_t index;
-        CommandType type;
-        ScoreValue immediateScore;
-        std::vector<std::future<ScoreValue>> lookaheadFutures;
-    };
-
-    std::vector<CommandEvaluation> commandEvaluations(commandCount);
-
-    for (uint32_t index = 0; index < commandCount; index++) {
-        const auto originalIndex = filteredIndices[index];
-        const auto& guessedDescriptor = guessedDescriptors->at(originalIndex);
-        const auto guessedCommandType = guessedDescriptor->GetCommandType();
-
-        commandEvaluations[index].index = originalIndex;
-        commandEvaluations[index].type = guessedCommandType;
-
-        if (guessedCommandType == net::eagle0::shardok::common::END_TURN_COMMAND) {
-            std::promise<ScoreValue> p;
-            commandEvaluations[index].lookaheadFutures.push_back(p.get_future());
-            p.set_value(currentUtility);
-            commandEvaluations[index].immediateScore = currentUtility;
-        } else if (IsDeterministic(guessedCommandType)) {
-            auto [immediateScore, lookaheadScore] = EvaluateWithRandomness(
-                    pid,
-                    isDefender,
-                    originalIndex,
-                    remainingLookahead,
-                    maxRepeatCount,
-                    _averageGenerator,
-                    guessedEngine,
-                    attackerStrategy,
-                    allCastleCoords,
-                    deadline);
-
-            commandEvaluations[index].immediateScore = immediateScore;
-            commandEvaluations[index].lookaheadFutures.push_back(std::move(lookaheadScore));
-        } else if (guessedDescriptor->HasOdds()) {
-            const auto successChancePercentile = guessedDescriptor->GetOddsPercentile();
-            const double successChance = static_cast<double>(successChancePercentile) / 100.0;
-
-            // Success attempt uses 1.0 - (successChance / 2) as the roll
-            auto [successImmediateScore, successLookaheadScore] = EvaluateWithRandomness(
-                    pid,
-                    isDefender,
-                    originalIndex,
-                    remainingLookahead,
-                    maxRepeatCount,
-                    std::make_shared<SequenceRandomGenerator>(
-                            std::vector{1.0 - successChance / 2.0}),
-                    guessedEngine,
-                    attackerStrategy,
-                    allCastleCoords,
-                    deadline);
-
-            // Failure attempt uses the average of (1 - successChance) and 0 as the roll
-            auto [failureImmediateScore, failureLookaheadScore] = EvaluateWithRandomness(
-                    pid,
-                    isDefender,
-                    originalIndex,
-                    remainingLookahead,
-                    maxRepeatCount,
-                    std::make_shared<SequenceRandomGenerator>(
-                            std::vector{(1.0 - successChance) / 2.0}),
-                    guessedEngine,
-                    attackerStrategy,
-                    allCastleCoords,
-                    deadline);
-
-            commandEvaluations[index].immediateScore =
-                    std::lerp(failureImmediateScore, successImmediateScore, successChance);
-
-            auto successSF = successLookaheadScore.share();
-            auto failureSF = failureLookaheadScore.share();
-            commandEvaluations[index].lookaheadFutures.push_back(std::async(
-                    std::launch::deferred,
-                    [successSF, failureSF, successChance]() -> double {
-                        return std::lerp(failureSF.get(), successSF.get(), successChance);
-                    }));
-        } else {
-            ScoreValue sum = 0.0;
-            for (int repeatIteration = 0; repeatIteration < maxRepeatCount; repeatIteration++) {
-                // In each iteration, use a double from [0, 1] as the random roll
-                auto sequence = std::vector{
-                        static_cast<double>(repeatIteration) /
-                        static_cast<double>(maxRepeatCount - 1)};
-                auto [immediateScore, lookaheadScore] = EvaluateWithRandomness(
-                        pid,
-                        isDefender,
-                        originalIndex,
-                        remainingLookahead,
-                        maxRepeatCount,
-                        std::make_shared<SequenceRandomGenerator>(sequence),
-                        guessedEngine,
-                        attackerStrategy,
-                        allCastleCoords,
-                        deadline);
-
-                sum += immediateScore;
-                commandEvaluations[index].lookaheadFutures.push_back(std::move(lookaheadScore));
-            }
-            commandEvaluations[index].immediateScore = sum / maxRepeatCount;
-        }
-    }
-
-    // Return a future that will wait for all evaluations and find the best one
-    return std::async(
-            std::launch::deferred,
-            [evals = std::move(commandEvaluations)]() mutable -> IndexAndScore {
-                std::vector<IndexAndScore> allResults;
-                allResults.reserve(evals.size());
-
-                // Wait for all futures and compute final scores
-                for (auto& eval : evals) {
-                    ScoreValue totalLookaheadScore = 0.0;
-                    for (auto& future : eval.lookaheadFutures) {
-                        totalLookaheadScore += future.get();
-                    }
-                    ScoreValue avgLookaheadScore =
-                            eval.lookaheadFutures.empty()
-                                    ? eval.immediateScore
-                                    : totalLookaheadScore / eval.lookaheadFutures.size();
-
-                    allResults.push_back(IndexAndScore{
-                            .index = eval.index,
-                            .type = eval.type,
-                            .lookaheadScore = avgLookaheadScore,
-                            .immediateScore = eval.immediateScore});
-                }
-                // Find the best command using the existing sorter
-                auto bestIt = std::ranges::max_element(allResults, CommandSorter);
-                return *bestIt;
-            });
-}
-
-auto AICommandEvaluator::EvaluateCommand(
-        const PlayerId pid,
-        const bool isDefender,
-        const int remainingLookahead,
-        const int maxRepeatCount,
-        const ShardokEngine& guessedEngine,
-        const AIStrategy& attackerStrategy,
-        const ScoreValue currentUtility,
-        const CoordsSet& allCastleCoords,
-        const size_t commandIndex,
-        std::chrono::steady_clock::time_point deadline) const -> std::future<ScoreValue> {
-    const CommandListSPtr guessedDescriptors = guessedEngine.GetAvailableCommandsForAIPlayer(pid);
-
-    if (commandIndex >= guessedDescriptors->size()) {
-        std::promise<ScoreValue> p;
-        p.set_value(currentUtility);
-        return p.get_future();
-    }
-
-    const auto& guessedDescriptor = guessedDescriptors->at(commandIndex);
-
-    if (const auto guessedCommandType = guessedDescriptor->GetCommandType();
-        guessedCommandType == net::eagle0::shardok::common::END_TURN_COMMAND) {
-        std::promise<ScoreValue> p;
-        p.set_value(currentUtility);
-        return p.get_future();
-    } else if (IsDeterministic(guessedCommandType)) {
-        auto [immediateScore, lookaheadScore] = EvaluateWithRandomness(
-                pid,
-                isDefender,
-                commandIndex,
-                remainingLookahead,
-                maxRepeatCount,
-                _averageGenerator,
-                guessedEngine,
-                attackerStrategy,
-                allCastleCoords,
-                deadline);
-        return std::move(lookaheadScore);
-    } else if (guessedDescriptor->HasOdds()) {
-        const auto successChancePercentile = guessedDescriptor->GetOddsPercentile();
-        const double successChance = static_cast<double>(successChancePercentile) / 100.0;
-
-        // Success attempt
-        auto [successImmediateScore, successLookaheadScore] = EvaluateWithRandomness(
-                pid,
-                isDefender,
-                commandIndex,
-                remainingLookahead,
-                maxRepeatCount,
-                std::make_shared<SequenceRandomGenerator>(std::vector{1.0 - successChance / 2.0}),
-                guessedEngine,
-                attackerStrategy,
-                allCastleCoords,
-                deadline);
-
-        // Failure attempt
-        auto [failureImmediateScore, failureLookaheadScore] = EvaluateWithRandomness(
-                pid,
-                isDefender,
-                commandIndex,
-                remainingLookahead,
-                maxRepeatCount,
-                std::make_shared<SequenceRandomGenerator>(std::vector{(1.0 - successChance) / 2.0}),
-                guessedEngine,
-                attackerStrategy,
-                allCastleCoords,
-                deadline);
-
-        // Return weighted average of success and failure
-        auto successSF = successLookaheadScore.share();
-        auto failureSF = failureLookaheadScore.share();
-        return std::async(std::launch::deferred, [successSF, failureSF, successChance]() -> double {
-            return std::lerp(failureSF.get(), successSF.get(), successChance);
-        });
-    } else {
-        // For non-deterministic commands without odds, use multiple attempts
-        std::vector<std::future<ScoreValue>> lookaheadFutures;
-        lookaheadFutures.reserve(maxRepeatCount);
-
-        for (int repeatIteration = 0; repeatIteration < maxRepeatCount; repeatIteration++) {
-            auto sequence = std::vector{
-                    static_cast<double>(repeatIteration) / static_cast<double>(maxRepeatCount - 1)};
-            auto [immediateScore, lookaheadScore] = EvaluateWithRandomness(
-                    pid,
-                    isDefender,
-                    commandIndex,
-                    remainingLookahead,
-                    maxRepeatCount,
-                    std::make_shared<SequenceRandomGenerator>(sequence),
-                    guessedEngine,
-                    attackerStrategy,
-                    allCastleCoords,
-                    deadline);
-
-            lookaheadFutures.push_back(std::move(lookaheadScore));
-        }
-
-        // Return a future that computes the average when needed
-        return std::async(
-                std::launch::deferred,
-                [lookaheadFutures = std::move(lookaheadFutures),
-                 maxRepeatCount]() mutable -> double {
-                    ScoreValue total = 0.0;
-                    for (auto& future : lookaheadFutures) { total += future.get(); }
-                    return total / maxRepeatCount;
-                });
-    }
-}
-
-}  // namespace shardok
@@ -1,110 +0,0 @@
-//
-// Command evaluator for AI lookahead search.
-// Separated from AIScoreCalculator to isolate pure state scoring from lookahead logic.
-//
-
-#ifndef EAGLE0_AICOMMANDEVALUATOR_HPP
-#define EAGLE0_AICOMMANDEVALUATOR_HPP
-
-#include <chrono>
-#include <future>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-
-namespace shardok {
-
-// Forward declarations
-class AIScoreCalculator;
-class ShardokEngine;
-
-using ScoreValue = double;
-using CommandType = net::eagle0::shardok::common::CommandType;
-using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
-
-/// Evaluates commands with lookahead using minimax-style search.
-/// Uses AIScoreCalculator for pure state evaluation, adds recursive lookahead logic.
-class AICommandEvaluator {
-public:
-    /// Construct evaluator with a scorer for state evaluation and dependencies for command
-    /// filtering
-    AICommandEvaluator(
-            const AIScoreCalculator& scorer,
-            const APDCache& apdCache,
-            BattalionTypeGetter battalionTypeGetter);  // Pass by value
-
-    /// Evaluates the score for a particular command index with lookahead.
-    [[nodiscard]] auto EvaluateCommand(
-            PlayerId pid,
-            bool isDefender,
-            int remainingLookahead,
-            int maxRepeatCount,
-            const ShardokEngine& guessedEngine,
-            const AIStrategy& attackerStrategy,
-            ScoreValue currentUtility,
-            const CoordsSet& allCastleCoords,
-            size_t commandIndex,
-            std::chrono::steady_clock::time_point deadline) const -> std::future<ScoreValue>;
-
-    /// Find the best command among all available commands at the given depth.
-    struct IndexAndScore {
-        size_t index;
-        CommandType type;
-        ScoreValue lookaheadScore;
-        ScoreValue immediateScore;
-    };
-
-    [[nodiscard]] auto FindBestCommand(
-            PlayerId pid,
-            bool isDefender,
-            int remainingLookahead,
-            int maxRepeatCount,
-            const ShardokEngine& guessedEngine,
-            const AIStrategy& attackerStrategy,
-            ScoreValue currentUtility,
-            const CoordsSet& allCastleCoords,
-            std::chrono::steady_clock::time_point deadline) const -> std::future<IndexAndScore>;
-
-private:
-    const AIScoreCalculator& scorer_;
-    const APDCache& apdCache_;
-    BattalionTypeGetter battalionTypeGetter_;  // Store by value
-
-    struct ImmediateAndLookaheadScore {
-        ScoreValue immediateScore;
-        std::future<ScoreValue> lookaheadScore;
-    };
-
-    /// Recursive lookahead calculator
-    [[nodiscard]] auto PerformLookahead(
-            PlayerId pid,
-            bool isDefender,
-            int remainingLookahead,
-            int maxRepeatCount,
-            const std::shared_ptr<ShardokEngine>& innerEngine,
-            ScoreValue currentUtility,
-            const AIStrategy& attackerStrategy,
-            const CoordsSet& allCastleCoords,
-            std::chrono::steady_clock::time_point deadline) const -> std::future<ScoreValue>;
-
-    /// Evaluate single command execution with randomness handling
-    [[nodiscard]] auto EvaluateWithRandomness(
-            PlayerId pid,
-            bool isDefender,
-            uint32_t commandIndex,
-            int remainingLookahead,
-            int maxRepeatCount,
-            const std::shared_ptr<class RandomGenerator>& randomGenerator,
-            const ShardokEngine& guessedEngine,
-            const AIStrategy& attackerStrategy,
-            const CoordsSet& allCastleCoords,
-            std::chrono::steady_clock::time_point deadline) const -> ImmediateAndLookaheadScore;
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AICOMMANDEVALUATOR_HPP
@@ -7,7 +7,6 @@
 #include <algorithm>

 #include "src/main/cpp/net/eagle0/shardok/library/BattalionType.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokException.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexCubeUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
@@ -37,8 +36,8 @@ std::vector<size_t> AICommandFilter::FilterCommands(
        PlayerId pid,
        bool isDefender,
        const GameStateW& gameState,
-        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter) {
+        const SettingsGetter& settings,
+        const APDCache& apdCache) {
    std::vector<size_t> filteredIndices;
    filteredIndices.reserve(commands->size());

@@ -67,8 +66,8 @@ std::vector<size_t> AICommandFilter::FilterCommands(
                    pid,
                    isDefender,
                    gameState,
+                    settings,
                    apdCache,
-                    battalionTypeGetter,
                    enemyLocations,
                    castleLocations,
                    minDistToEnemies)) {
@@ -81,22 +80,16 @@ std::vector<size_t> AICommandFilter::FilterCommands(
                                     pid,
                                     isDefender,
                                     gameState,
+                                     settings,
                                     apdCache,
-                                     battalionTypeGetter,
                                     enemyLocations,
                                     minDistToEnemies)) {
            shouldFilter = true;
        }

        // Check strategic blunders
-        if (!shouldFilter && IsStrategicBlunder(
-                                     *cmd,
-                                     pid,
-                                     isDefender,
-                                     gameState,
-                                     apdCache,
-                                     battalionTypeGetter,
-                                     minDistToEnemies)) {
+        if (!shouldFilter &&
+            IsStrategicBlunder(*cmd, pid, isDefender, gameState, settings, minDistToEnemies)) {
            shouldFilter = true;
        }

@@ -111,8 +104,8 @@ bool AICommandFilter::IsWastefulAction(
        PlayerId pid,
        bool isDefender,
        const GameStateW& gameState,
+        const SettingsGetter& settings,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
        const CoordsSet& enemyLocations,
        const CoordsSet& castleLocations,
        double minDistToEnemies) {
@@ -144,16 +137,15 @@ bool AICommandFilter::IsWastefulAction(

            if (!isDefender) {
                // Attackers: Only allow fire if the target location is on or adjacent to an enemy
-                const int targetRow = cmd.GetTargetRow();
-                const int targetCol = cmd.GetTargetColumn();
-                if (targetRow < 0 || targetCol < 0) {
-                    throw ShardokInternalErrorException(
-                            "START_FIRE_COMMAND missing required target information");
+                const auto cmdProto = cmd.GetCommandProto();
+                if (!cmdProto.has_target()) {
+                    return true;  // Can't analyze without target info
                }

-                const Coords fireLocation(
-                        static_cast<int8_t>(targetRow),
-                        static_cast<int8_t>(targetCol));
+                const auto& targetCoords = cmdProto.target();
+                const Coords fireLocation{
+                        static_cast<int8_t>(targetCoords.row()),
+                        static_cast<int8_t>(targetCoords.column())};

                // Check if any enemy is on the fire location or adjacent to it
                bool enemyNearFireLocation = false;
@@ -188,12 +180,13 @@ bool AICommandFilter::IsWastefulAction(

            if (!isDefender) {
                // Attackers: Only allow fortify if within 3 hexes of enemies or castles
-                const int unitId = cmd.GetActorUnitId();
-                if (unitId < 0) {
-                    throw ShardokInternalErrorException(
-                            "FORTIFY_COMMAND missing required actor information");
+                const auto cmdProto = cmd.GetCommandProto();
+                if (!cmdProto.has_actor()) {
+                    return true;  // Can't analyze without actor info
                }

+                const auto unitId = cmdProto.actor().value();
+
                // Get the acting unit directly by ID
                const Unit* actingUnit = gameState->units()->Get(unitId);
                // verify the unit is still active
@@ -250,18 +243,16 @@ bool AICommandFilter::IsWastefulAction(
            // These actions can fail, so we need high confidence of benefit (8+ action points
            // saved)

-            const int unitId = cmd.GetActorUnitId();
-            const int targetRow = cmd.GetTargetRow();
-            const int targetCol = cmd.GetTargetColumn();
-            if (unitId < 0 || targetRow < 0 || targetCol < 0) {
-                throw ShardokInternalErrorException(
-                        "BUILD_BRIDGE/FREEZE_WATER_COMMAND missing required actor or target "
-                        "information");
+            const auto cmdProto = cmd.GetCommandProto();
+            if (!cmdProto.has_actor() || !cmdProto.has_target()) {
+                return true;  // Can't analyze without full command info
            }

-            const Coords waterLocation(
-                    static_cast<int8_t>(targetRow),
-                    static_cast<int8_t>(targetCol));
+            const auto unitId = cmdProto.actor().value();
+            const auto& targetCoords = cmdProto.target();
+            const Coords waterLocation{
+                    static_cast<int8_t>(targetCoords.row()),
+                    static_cast<int8_t>(targetCoords.column())};

            // Get the acting unit directly by ID
            const Unit* actingUnit = gameState->units()->Get(unitId);
@@ -278,7 +269,7 @@ bool AICommandFilter::IsWastefulAction(
            }

            // Get action point distances for this unit's battalion type
-            const auto& battType = battalionTypeGetter(actingUnit->battalion().type());
+            const auto& battType = settings.GetBattalionType(actingUnit->battalion().type());
            const auto* apd = apdCache->GetRaw(
                    gameState->hex_map(),
                    ActionPointDistancesCache::GetMapId(gameState->hex_map()),
@@ -356,16 +347,15 @@ bool AICommandFilter::IsWastefulAction(
        case CommandType::REPAIR_COMMAND: {
            // Repair filtering - filter repairs with high integrity targets
            // Note: RepairCommandFactory already filters enemy-occupied targets
-            const int targetRow = cmd.GetTargetRow();
-            const int targetCol = cmd.GetTargetColumn();
-            if (targetRow < 0 || targetCol < 0) {
-                throw ShardokInternalErrorException(
-                        "REPAIR_COMMAND missing required target information");
+            const auto cmdProto = cmd.GetCommandProto();
+            if (!cmdProto.has_target()) {
+                return true;  // Can't analyze without target info
            }

-            const Coords repairLocation(
-                    static_cast<int8_t>(targetRow),
-                    static_cast<int8_t>(targetCol));
+            const auto& targetCoords = cmdProto.target();
+            const Coords repairLocation{
+                    static_cast<int8_t>(targetCoords.row()),
+                    static_cast<int8_t>(targetCoords.column())};

            // Check terrain modifiers at target location
            const auto* terrain = GetTerrain(gameState->hex_map(), repairLocation);
@@ -388,16 +378,15 @@ bool AICommandFilter::IsWastefulAction(

        case CommandType::EXTINGUISH_FIRE_COMMAND: {
            // Extinguish fire filtering - don't extinguish fires on enemy-occupied tiles
-            const int targetRow = cmd.GetTargetRow();
-            const int targetCol = cmd.GetTargetColumn();
-            if (targetRow < 0 || targetCol < 0) {
-                throw ShardokInternalErrorException(
-                        "EXTINGUISH_FIRE_COMMAND missing required target information");
+            const auto cmdProto = cmd.GetCommandProto();
+            if (!cmdProto.has_target()) {
+                return true;  // Can't analyze without target info
            }

-            const Coords fireLocation(
-                    static_cast<int8_t>(targetRow),
-                    static_cast<int8_t>(targetCol));
+            const auto& targetCoords = cmdProto.target();
+            const Coords fireLocation{
+                    static_cast<int8_t>(targetCoords.row()),
+                    static_cast<int8_t>(targetCoords.column())};

            // Check if any enemy occupies the fire location - let them burn!
            std::vector<PlayerId> allyPids;  // Empty for now - assume 2-player game
@@ -418,8 +407,8 @@ bool AICommandFilter::IsWastefulMovement(
        PlayerId pid,
        bool isDefender,
        const GameStateW& gameState,
+        const SettingsGetter& settings,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter,
        const CoordsSet& enemyLocations,
        double minDistToEnemies) {
    if (cmd.GetCommandType() != CommandType::MOVE_COMMAND) { return false; }
@@ -429,17 +418,17 @@ bool AICommandFilter::IsWastefulMovement(
        return false;  // Don't filter defender movement or when close to enemies
    }

-    // Get unit and target information directly from command
-    const int unitId = cmd.GetActorUnitId();
-    const int targetRow = cmd.GetTargetRow();
-    const int targetCol = cmd.GetTargetColumn();
+    // Get the command proto to access unit and target information
+    const auto cmdProto = cmd.GetCommandProto();

    // Check if we have the required information
-    if (unitId < 0 || targetRow < 0 || targetCol < 0) {
-        throw ShardokInternalErrorException(
-                "MOVE_COMMAND missing required actor or target information");
+    if (!cmdProto.has_actor() || !cmdProto.has_target()) {
+        return false;  // Can't analyze without unit and target info
    }

+    const auto unitId = cmdProto.actor().value();
+    const auto& targetCoords = cmdProto.target();
+
    // Get the acting unit directly by ID
    const Unit* actingUnit = gameState->units()->Get(unitId);
    // Verify the unit is still active
@@ -455,10 +444,12 @@ bool AICommandFilter::IsWastefulMovement(
    }

    const auto& currentCoords = actingUnit->location();
-    const Coords targetCoordsFlat(static_cast<int8_t>(targetRow), static_cast<int8_t>(targetCol));
+    const Coords targetCoordsFlat{
+            static_cast<int8_t>(targetCoords.row()),
+            static_cast<int8_t>(targetCoords.column())};

    // Get action point distances for this unit's battalion type
-    const auto& battType = battalionTypeGetter(actingUnit->battalion().type());
+    const auto& battType = settings.GetBattalionType(actingUnit->battalion().type());
    const auto* apd = apdCache->GetRaw(
            gameState->hex_map(),
            ActionPointDistancesCache::GetMapId(gameState->hex_map()),
@@ -499,8 +490,7 @@ bool AICommandFilter::IsStrategicBlunder(
        PlayerId /*pid*/,
        bool /*isDefender*/,
        const GameStateW& /*gameState*/,
-        const APDCache& /*apdCache*/,
-        const BattalionTypeGetter& /*battalionTypeGetter*/,
+        const SettingsGetter& /*settings*/,
        double /*minDistToEnemies*/) {
    // Simplified strategic blunder detection for now
    // TODO: Implement proper castle abandonment detection
@@ -8,12 +8,12 @@
 #include <memory>
 #include <vector>

-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
+#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"

 namespace shardok {

@@ -32,8 +32,8 @@ public:
     * @param pid Player ID making the move
     * @param isDefender True if this player is the defender
     * @param gameState Current game state
+     * @param settings Game settings for parameter lookup
     * @param apdCache Action point distance cache for distance calculations
-     * @param battalionTypeLookup Function to look up battalion types by ID
     * @return Filtered list of commands worth evaluating
     */
    static std::vector<size_t> FilterCommands(
@@ -41,8 +41,8 @@ public:
            PlayerId pid,
            bool isDefender,
            const GameStateW& gameState,
-            const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeLookup);
+            const SettingsGetter& settings,
+            const APDCache& apdCache);

 private:
    // Helper to build enemy locations once for efficiency
@@ -54,8 +54,8 @@ private:
            PlayerId pid,
            bool isDefender,
            const GameStateW& gameState,
+            const SettingsGetter& settings,
            const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeLookup,
            const CoordsSet& enemyLocations,
            const CoordsSet& castleLocations,
            double minDistToEnemies);
@@ -66,8 +66,8 @@ private:
            PlayerId pid,
            bool isDefender,
            const GameStateW& gameState,
+            const SettingsGetter& settings,
            const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeLookup,
            const CoordsSet& enemyLocations,
            double minDistToEnemies);

@@ -77,8 +77,7 @@ private:
            PlayerId pid,
            bool isDefender,
            const GameStateW& gameState,
-            const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeLookup,
+            const SettingsGetter& settings,
            double minDistToEnemies);

    // Helper functions for distance and position analysis
@@ -1,23 +0,0 @@
-//
-// AICommonTypes.hpp
-// Common type definitions used across AI utility functions
-//
-
-#ifndef EAGLE0_AICOMMONTYPES_HPP
-#define EAGLE0_AICOMMONTYPES_HPP
-
-#include <functional>
-
-#include "src/main/cpp/net/eagle0/shardok/library/BattalionType.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-
-namespace shardok {
-
-// Function type for looking up battalion types by ID
-// Used across AI utilities to get battalion type information without
-// needing to pass the entire scorer object
-using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AICOMMONTYPES_HPP
@@ -1,25 +0,0 @@
-//
-// AI System Types and Configuration
-//
-
-#ifndef EAGLE0_AI_CONFIG_HPP
-#define EAGLE0_AI_CONFIG_HPP
-
-namespace shardok {
-
-// Enum for AI algorithm selection
-enum class AIAlgorithmType {
-    ITERATIVE_DEEPENING,  // Default: Minimax with sophisticated randomness
-    MCTS                  // Monte Carlo Tree Search with multithreading
-};
-
-// Enum for scoring calculator selection
-enum class ScoringCalculatorType {
-    STANDARD,       // Default: Unbounded raw scores
-    NORMALIZED,     // Normalized scores in [0, 1] range for ML training
-    MCTS_OPTIMIZED  // Bounded linear scores tuned for MCTS
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AI_CONFIG_HPP
@@ -7,10 +7,8 @@
 #include <algorithm>
 #include <ranges>

-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIScoreUtilities.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"

 namespace shardok {
@@ -21,9 +19,8 @@ constexpr double MINIMUM_RATIO_FOR_DEFENDER_TO_HOLD = 0.60;
 auto AIDefenderStrategySelector::BestDefenderStrategy(
        const GameStateW& gameState,
        const CoordsSet& criticalTileCoords,
-        int maxRounds,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter) -> AIStrategy {
+        const SettingsGetter& settings) -> AIStrategy {
    uint32_t attackerNonUndeadUnitCount = 0;
    uint32_t attackerNonUndeadUnitNotRequiringWaterCrossingCount = 0;
    int attackerTroops = 0;
@@ -39,7 +36,7 @@ auto AIDefenderStrategySelector::BestDefenderStrategy(
                    player->player_id(),
                    criticalTileCoords,
                    apdCache,
-                    battalionTypeGetter);
+                    settings);
            attackerUnitIdsRequiringWaterCrossing.insert(
                    attackerUnitIdsRequiringWaterCrossing.end(),
                    unitIdsRequiringWaterCrossing.begin(),
@@ -74,7 +71,7 @@ auto AIDefenderStrategySelector::BestDefenderStrategy(
        }
    }

-    const int roundsRemaining = maxRounds - gameState->current_round();
+    const int roundsRemaining = 32 - gameState->current_round();
    AIStrategy chosenStrategy;

    // Defender will flee if
@@ -6,23 +6,19 @@
 #define EAGLE0_AIDEFENDERSTRATEGYSELECTOR_HPP

 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"

 namespace shardok {
-
 class AIDefenderStrategySelector {
 public:
    static auto BestDefenderStrategy(
            const GameStateW& gameState,
            const CoordsSet& criticalTileCoords,
-            int maxRounds,
            const APDCache& apdCache,
-            const BattalionTypeGetter& battalionTypeGetter) -> AIStrategy;
+            const SettingsGetter& settings) -> AIStrategy;
 };
 }  // namespace shardok

@@ -49,8 +49,8 @@ auto DefenderDistanceBuf(
        const vector<const Unit *> &attackerUnits,
        const APDCache &apdCache,
        const ALCache &alCache,
-        const BattalionTypeGetter &battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter &settings,
+        const int braveWaterActionPointCost,
        const bool lateGame,
        const bool includeUndead) -> double {
    const auto &locationsToAttackMe = alCache->CachedLocations(defenderLocation, lateGame);
@@ -73,14 +73,14 @@ auto DefenderDistanceBuf(
            notBravingDistances[typeInt] = apdCache->GetRaw(
                    hexMap,
                    mapId,
-                    battalionTypeGetter(attacker->battalion().type()),
+                    settings.GetBattalionType(attacker->battalion().type()),
                    false);
            bravingDistances[typeInt] = apdCache->GetRaw(
                    hexMap,
                    mapId,
-                    battalionTypeGetter(attacker->battalion().type()),
+                    settings.GetBattalionType(attacker->battalion().type()),
                    true,
-                    braveWaterCost);
+                    braveWaterActionPointCost);
        }
    }

@@ -6,10 +6,10 @@
 #define EAGLE0_AIDISTANCEDEBUF_HPP

 #include "AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistances.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"

 namespace shardok {

@@ -23,8 +23,8 @@ auto DefenderDistanceBuf(
        const vector<const Unit *> &attackerUnits,
        const APDCache &apdCache,
        const ALCache &alCache,
-        const BattalionTypeGetter &battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter &settings,
+        int braveWaterActionPointCost,
        bool lateGame,
        bool includeUndead) -> double;

@@ -15,15 +15,15 @@
 namespace shardok {

 auto AIFleeDecisionCalculator::GetFleeCommandIndex(
-        const CommandList::const_iterator& fleeCommand,
-        const CommandListSPtr& availableCommands) -> size_t {
-    return static_cast<size_t>(std::distance(availableCommands->begin(), fleeCommand));
+        const vector<CommandProto>::const_iterator& fleeCommand,
+        const vector<CommandProto>& availableCommands) -> size_t {
+    return static_cast<size_t>(std::distance(availableCommands.begin(), fleeCommand));
 }

 auto AIFleeDecisionCalculator::EstimateCombatSuccess(
        PlayerId attackerPlayerId,
        const GameStateW& gameState,
-        int maxRounds) -> double {
+        const SettingsGetter& settings) -> double {
    if (gameState->status() == nullptr ||
        gameState->status()->state() !=
                net::eagle0::shardok::storage::fb::GameStatus_::State_GAME_RUNNING) {
@@ -68,7 +68,7 @@ auto AIFleeDecisionCalculator::EstimateCombatSuccess(
        }
    }

-    const int roundsRemaining = maxRounds - gameState->current_round();
+    const int roundsRemaining = settings.Backing().max_rounds() - gameState->current_round();

    // Special case: Attacker has no heroes - automatic loss
    if (attackerHeroes == 0) {
@@ -133,15 +133,17 @@ auto AIFleeDecisionCalculator::EstimateCombatSuccess(

 auto AIFleeDecisionCalculator::EvaluateFleeVsFight(
        PlayerId playerId,
+        const SettingsGetter& settingsGetter,
        const GameStateW& guessedState,
-        const CommandListSPtr& availableCommands,
-        const CommandList::const_iterator& fleeCommand,
-        int maxRounds,
-        int minimumFleeOddsThreshold,
-        int desperateFleeThreshold,
+        const vector<CommandProto>& availableCommands,
+        const vector<CommandProto>::const_iterator& fleeCommand,
        bool enableDebugLogging) -> FleeDecision {
    // Get flee success odds
-    const int fleeSuccessChance = (*fleeCommand)->GetOddsPercentile();
+    const int fleeSuccessChance = fleeCommand->odds().success_chance();
+
+    // Get thresholds from settings
+    const int minimumFleeOddsThreshold = settingsGetter.Backing().ai_minimum_flee_odds_threshold();
+    const int desperateFleeThreshold = settingsGetter.Backing().ai_desperate_flee_threshold();

    if (enableDebugLogging) {
        printf("AI FinalRound: Evaluating flee (odds=%d%%)...\n", fleeSuccessChance);
@@ -161,7 +163,7 @@ auto AIFleeDecisionCalculator::EvaluateFleeVsFight(
    }

    // Low flee odds - evaluate if fighting might be better
-    const double combatWinChance = EstimateCombatSuccess(playerId, guessedState, maxRounds);
+    const double combatWinChance = EstimateCombatSuccess(playerId, guessedState, settingsGetter);

    // If combat situation is hopeless, even bad flee odds are better than certain death
    if (combatWinChance <= 0.05 && fleeSuccessChance >= desperateFleeThreshold) {
@@ -213,11 +215,11 @@ auto AIFleeDecisionCalculator::EvaluateFleeVsFight(
 auto AIFleeDecisionCalculator::ShouldConsiderFleeing(
        PlayerId attackerPlayerId,
        const GameStateW& guessedState,
-        int maxRounds,
+        const SettingsGetter& settings,
        double fleeConsiderationThreshold) -> bool {
    // Get combat success probability
    const double combatSuccessChance =
-            EstimateCombatSuccess(attackerPlayerId, guessedState, maxRounds);
+            EstimateCombatSuccess(attackerPlayerId, guessedState, settings);

    // Consider fleeing if combat success chance is below threshold
    return combatSuccessChance < fleeConsiderationThreshold;
@@ -9,11 +9,14 @@
 #ifndef AIFleeDecisionCalculator_hpp
 #define AIFleeDecisionCalculator_hpp

-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
+#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"

 namespace shardok {

+using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
+
 class AIFleeDecisionCalculator {
 public:
    // Configuration for flee decision thresholds
@@ -32,33 +35,31 @@ public:
    // Evaluate whether to flee or fight in the final round
    [[nodiscard]] static auto EvaluateFleeVsFight(
            PlayerId playerId,
+            const SettingsGetter& settings,
            const GameStateW& guessedState,
-            const CommandListSPtr& availableCommands,
-            const CommandList::const_iterator& fleeCommand,
-            int maxRounds,
-            int minimumFleeOddsThreshold,
-            int desperateFleeThreshold,
+            const vector<CommandProto>& availableCommands,
+            const vector<CommandProto>::const_iterator& fleeCommand,
            bool enableDebugLogging = false) -> FleeDecision;

    // Estimate probability of combat success for the attacker
    [[nodiscard]] static auto EstimateCombatSuccess(
            PlayerId attackerPlayerId,
            const GameStateW& guessedState,
-            int maxRounds) -> double;
+            const SettingsGetter& settings) -> double;

    // Determine if the attacker should consider fleeing based on combat odds
    // Returns true if fleeing should be considered as an option
    [[nodiscard]] static auto ShouldConsiderFleeing(
            PlayerId attackerPlayerId,
            const GameStateW& guessedState,
-            int maxRounds,
+            const SettingsGetter& settings,
            double fleeConsiderationThreshold = 0.5) -> bool;

 private:
    // Helper to get flee command index
    [[nodiscard]] static auto GetFleeCommandIndex(
-            const CommandList::const_iterator& fleeCommand,
-            const CommandListSPtr& availableCommands) -> size_t;
+            const vector<CommandProto>::const_iterator& fleeCommand,
+            const vector<CommandProto>& availableCommands) -> size_t;
 };

 }  // namespace shardok
@@ -1,251 +0,0 @@
-//
-// Fast heuristic weighting implementation with context-aware logic
-//
-
-#include "AIHeuristicWeighting.hpp"
-
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokException.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistances.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
-
-namespace shardok {
-
-using CommandType = net::eagle0::shardok::common::CommandType;
-using Coords = net::eagle0::shardok::storage::fb::Coords;
-using ProtoCoords = net::eagle0::shardok::common::Coords;
-
-double AIHeuristicWeighting::GetCommandWeight(
-        const CommandType commandType,
-        const UnitId actorUnitId,
-        const PlayerId actorPlayerId,
-        const Coords& targetCoords,
-        const GameStateW& state,
-        const CoordsSet& castleCoords,
-        const APDCache* apdCache,
-        bool isDefender,
-        std::function<BattalionTypeSPtr(BattalionTypeId)> getBattalionType) {
-    // Fast O(1) heuristic weights based on command type and game context
-    // Higher weight = more likely to select in simulation
-    // 0.0 = never select (filtered out)
-
-    const auto* hexMap = state->hex_map();
-    const auto* units = state->units();
-    const bool hasTarget = (targetCoords.row() >= 0 && targetCoords.column() >= 0);
-
-    switch (commandType) {
-        // === HIGH VALUE OFFENSIVE (10.0) ===
-        // Ranged attacks - very valuable, typically available when in range
-        case CommandType::ARCHERY_COMMAND: return 20.0;
-        case CommandType::LIGHTNING_BOLT_COMMAND: return 10.0;
-        case CommandType::FEAR_COMMAND: return 10.0;
-
-        // Area/tactical spells - high impact
-        case CommandType::METEOR_START_COMMAND: {
-            // METEOR_START doesn't have a target - it's based on actor location
-            if (hasTarget) {
-                throw ShardokInternalErrorException(
-                        "METEOR_START_COMMAND should not have target coordinates");
-            }
-
-            // Get actor's location
-            const auto* actorUnit = units->Get(actorUnitId);
-            if (!actorUnit) {
-                throw ShardokInternalErrorException(
-                        "METEOR_START_COMMAND actor unit not found in game state");
-            }
-
-            const Coords& actorLocation = actorUnit->location();
-            int enemyCount = 0;
-
-            // Count enemies within meteor range (3 hexes) of actor location
-            constexpr int METEOR_RANGE = 3;
-            const auto tilesInRange = TilesWithinDistance(hexMap, actorLocation, METEOR_RANGE);
-            for (const auto& tileCoords : tilesInRange) {
-                if (const auto* unit = Occupant(units, tileCoords)) {
-                    if (unit->player_id() != actorPlayerId) { enemyCount++; }
-                }
-            }
-
-            return 1.0 + (enemyCount * 15.0);  // Base 1 + 15 per enemy in range
-        }
-
-        case CommandType::METEOR_TARGET_COMMAND: {
-            // High weight per enemy unit at or adjacent to target
-            if (!hasTarget) {
-                throw ShardokInternalErrorException(
-                        "METEOR_TARGET_COMMAND requires target coordinates for heuristic "
-                        "weighting");
-            }
-
-            int enemyCount = 0;
-
-            // Count enemies at target
-            if (const auto* targetUnit = Occupant(units, targetCoords)) {
-                if (targetUnit->player_id() != actorPlayerId) { enemyCount++; }
-            }
-
-            // Count enemies adjacent to target
-            for (const auto& neighbor : HexMapUtils::GetAdjacentTiles(hexMap, targetCoords)) {
-                if (const auto* unit = Occupant(units, neighbor.coords)) {
-                    if (unit->player_id() != actorPlayerId) { enemyCount++; }
-                }
-            }
-
-            return 1.0 + (enemyCount * 15.0);  // Base 1 + 15 per enemy in range
-        }
-
-        case CommandType::RAISE_DEAD_COMMAND: return 10.0;
-        case CommandType::HOLY_WAVE_COMMAND: return 8.0;
-
-        // Fire on enemy (context-dependent)
-        case CommandType::START_FIRE_COMMAND: {
-            // High if enemy at target, low otherwise
-            if (!hasTarget) {
-                throw ShardokInternalErrorException(
-                        "START_FIRE_COMMAND requires target coordinates for heuristic weighting");
-            }
-
-            if (const auto* targetUnit = Occupant(units, targetCoords)) {
-                if (targetUnit->player_id() != actorPlayerId) {
-                    return 10.0;  // Enemy at target - high value
-                }
-            }
-            return 1.0;  // No enemy - low value but still valid
-        }
-
-        // === MEDIUM-HIGH OFFENSIVE (5.0-7.0) ===
-        // Direct damage melee
-        case CommandType::MELEE_COMMAND: return 7.0;
-        case CommandType::CHARGE_COMMAND: return 7.0;  // Damage + movement
-        case CommandType::CHALLENGE_DUEL_COMMAND: return 5.0;
-
-        // Control and tactical magic
-        case CommandType::CONTROL_COMMAND: return 6.0;
-        case CommandType::METEOR_CAST_COMMAND: return 6.0;  // Finish meteor
-
-        case CommandType::REDUCE_COMMAND: {
-            // High if enemy at target, zero otherwise
-            if (!hasTarget) return 0.0;
-
-            if (const auto* targetUnit = Occupant(units, targetCoords)) {
-                if (targetUnit->player_id() != actorPlayerId) {
-                    return 10.0;  // Enemy at target - very high value
-                }
-            }
-            return 0.0;  // No enemy - don't use
-        }
-
-        // === MOVEMENT - Context-dependent ===
-        case CommandType::MOVE_COMMAND: {
-            if (isDefender) {
-                return 0.0;  // Defenders don't move
-            }
-
-            // Attackers: weight based on distance improvement towards castle
-            if (!hasTarget) {
-                throw ShardokInternalErrorException(
-                        "MOVE_COMMAND requires target coordinates for heuristic weighting");
-            }
-
-            // Get actor unit to determine battalion type and start position
-            const auto* actorUnit = units->Get(actorUnitId);
-            if (!actorUnit) return 4.0;  // Default if can't find actor
-
-            // Get battalion type for distance calculation
-            const auto battalionTypeId = actorUnit->battalion().type();
-            const auto battalionTypePtr = getBattalionType(battalionTypeId);
-            if (!battalionTypePtr) return 4.0;  // Default if can't get battalion type
-
-            // Get ActionPointDistances for this battalion type
-            const auto mapId = ActionPointDistancesCache::GetMapId(hexMap);
-            const auto* apd = (*apdCache)->GetRaw(hexMap, mapId, battalionTypePtr, false, -1);
-            if (!apd) return 4.0;  // Default if can't get distances
-
-            // Calculate minimum distance from start to any castle
-            const Coords startCoords = actorUnit->location();
-            auto minStartDistance = ActionPointDistances::IMPOSSIBLE;
-            for (const auto& castleCoord : castleCoords) {
-                const auto dist = apd->Distance(startCoords, castleCoord);
-                if (dist < minStartDistance) { minStartDistance = dist; }
-            }
-
-            // Calculate minimum distance from end to any castle
-            const Coords& endCoords = targetCoords;
-            auto minEndDistance = ActionPointDistances::IMPOSSIBLE;
-            for (const auto& castleCoord : castleCoords) {
-                const auto dist = apd->Distance(endCoords, castleCoord);
-                if (dist < minEndDistance) { minEndDistance = dist; }
-            }
-
-            // Return weight based on distance improvement
-            // Higher weight if we're moving closer to castle
-            if (minStartDistance == ActionPointDistances::IMPOSSIBLE ||
-                minEndDistance == ActionPointDistances::IMPOSSIBLE) {
-                return 4.0;  // Default if distances are impossible
-            }
-
-            const auto improvement = static_cast<double>(minStartDistance - minEndDistance);
-            return std::max(0.0, improvement);
-        }
-
-        case CommandType::BRAVE_WATER_COMMAND: return 3.0;  // Tactical movement
-        case CommandType::SCOUT_COMMAND:
-            return 2.0;  // Information gathering
-
-        // Terrain manipulation
-        case CommandType::FREEZE_WATER_COMMAND: return 3.0;
-        case CommandType::BUILD_BRIDGE_COMMAND: return 3.0;
-
-        // === LOW VALUE DEFENSIVE/UTILITY (1.0-2.0) ===
-        case CommandType::EXTINGUISH_FIRE_COMMAND: {
-            // High if friendly at target, low otherwise
-            if (!hasTarget) {
-                throw ShardokInternalErrorException(
-                        "EXTINGUISH_FIRE_COMMAND requires target coordinates for heuristic "
-                        "weighting");
-            }
-
-            if (const auto* targetUnit = Occupant(units, targetCoords)) {
-                if (targetUnit->player_id() == actorPlayerId) {
-                    return 8.0;  // Friendly at target - high value
-                }
-            }
-            return 1.0;  // No friendly - low value but still valid
-        }
-
-        case CommandType::UNIT_REST_COMMAND: return 1.5;
-        case CommandType::FORTIFY_COMMAND: return 2.0;
-
-        // Zero weight - don't use in simulation
-        case CommandType::REPAIR_COMMAND: return 0.0;
-        case CommandType::HIDE_COMMAND: return 0.0;
-        case CommandType::RELEASE_UNIT_COMMAND: return 0.0;
-
-        case CommandType::REINFORCE_COMMAND: return 10.0;
-        case CommandType::MANAGE_PRISONER: return 1.0;
-
-        // === ZERO WEIGHT - NEVER SELECT (0.0) ===
-        // Explicitly bad actions
-        case CommandType::FLEE_COMMAND: return 0.0;  // Never flee in simulation
-        case CommandType::RETREAT_COMMAND: return 0.0;
-        case CommandType::BECOME_OUTLAW_COMMAND: return 0.0;  // Never become outlaw
-        case CommandType::DISMISS_UNIT_COMMAND:
-            return 0.0;  // Never dismiss in combat
-
-        // Actions that are fine as a fallback
-        case CommandType::END_TURN_COMMAND: return 1.0;
-        case CommandType::UNIT_STOP_COMMAND: return 1.0;
-        case CommandType::METEOR_CANCEL_COMMAND: return 1.0;
-
-        // Setup commands (shouldn't appear in combat, but filter anyway)
-        case CommandType::PLACE_UNIT_COMMAND: return 10.0;
-        case CommandType::PLACE_HIDDEN_UNIT_COMMAND: return 1.0;
-        case CommandType::END_PLAYER_SETUP_COMMAND: return 1.0;
-
-        // Unknown/unhandled
-        case CommandType::UNKNOWN_COMMAND:
-        default: return 0.0;  // Don't select unknown commands
-    }
-}
-
-}  // namespace shardok
@@ -1,40 +0,0 @@
-//
-// Fast heuristic weighting for MCTS simulations
-// Provides O(1) weights based on command type and context
-//
-
-#ifndef EAGLE0_AI_HEURISTIC_WEIGHTING_HPP
-#define EAGLE0_AI_HEURISTIC_WEIGHTING_HPP
-
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-#pragma clang diagnostic pop
-
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-
-namespace shardok {
-
-// Fast heuristic-based command weighting for MCTS simulation policy
-// Avoids expensive score calculation while maintaining intelligent bias
-class AIHeuristicWeighting {
-public:
-    // Get weight for a command using fast heuristics with game context
-    // Returns weight >= 0.0, where 0.0 means "never select" and higher is more likely
-    static double GetCommandWeight(
-            net::eagle0::shardok::common::CommandType commandType,
-            UnitId actorUnitId,
-            PlayerId actorPlayerId,
-            const Coords& targetCoords,
-            const GameStateW& state,
-            const CoordsSet& castleCoords,
-            const APDCache* apdCache,
-            bool isDefender,
-            std::function<BattalionTypeSPtr(BattalionTypeId)> getBattalionType);
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AI_HEURISTIC_WEIGHTING_HPP
@@ -0,0 +1,72 @@
+//
+// Created by dancrosby on 3/4/20.
+//
+
+#ifndef EAGLE0_AISCORECALCULATOR_HPP
+#define EAGLE0_AISCORECALCULATOR_HPP
+
+#include <chrono>
+#include <future>
+
+#include "src/main/cpp/net/eagle0/common/TaskResult.hpp"
+#include "src/main/cpp/net/eagle0/common/ThreadPool.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
+#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
+#include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
+#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"
+#include "src/main/protobuf/net/eagle0/shardok/api/game_state_view.pb.h"
+
+namespace shardok {
+
+using net::eagle0::shardok::api::GameStateView;
+using GameState = fb::GameState;
+using shardok::PlayerId;
+using std::future;
+using std::vector;
+
+using ScoreValue = double;
+using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
+
+class AIScoreCalculator {
+public:
+    // Start a new metrics collection session
+    static void BeginMetricsSession();
+
+    // End the current session and return metrics
+    static eagle0::common::ThreadPoolMetrics EndMetricsSession();
+    // Evaluate the score of a guessed game state based on the current AI strategy. DOES NOT perform
+    // or evaluate any commands.
+    [[nodiscard]] static auto GuessedStateScore(
+            bool isDefender,
+            const GameStateW &state,
+            const AIStrategy &aiStrategy,
+            const CoordsSet &allCastleCoords,
+            const SettingsGetter &settingsGetter,
+            const APDCache &apdCache,
+            const ALCache &alCache) -> ScoreValue;
+
+    // Evaluates the score for a particular command index for the given player, using lookahead.
+    [[nodiscard]] static auto CommandScore(
+            PlayerId pid,
+            bool isDefender,
+            int remainingLookahead,
+            int maxRepeatCount,
+            const ShardokEngine &guessedEngine,
+            const AIStrategy &attackerStrategy,
+            ScoreValue currentUtility,
+            const SettingsGetter &settingsGetter,
+            const CoordsSet &allCastleCoords,
+            const APDCache &apdCache,
+            const ALCache &alCache,
+            size_t commandIndex,
+            std::chrono::steady_clock::time_point deadline)
+            -> std::future<eagle0::common::TaskResult<ScoreValue>>;
+};
+
+}  // namespace shardok
+
+#endif  // EAGLE0_AISCORECALCULATOR_HPP
@@ -3,7 +3,6 @@
 //

 #include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-
 namespace shardok {
 AIStrategy FleeStrategy = AIStrategy{AIStrategy::STRATEGY_FLEE};
 AIStrategy HoldCastlesStrategy = AIStrategy{AIStrategy::STRATEGY_HOLD_CASTLES};
@@ -24,40 +24,10 @@ int AIEvaluationCounter::GetCurrentCount() { return activeCount.load(); }
 auto CalculateTimeBudget(
        const PlayerId playerId,
        const GameSettingsSPtr &settings,
-        const GameStateW &state,
-        const size_t numCommands) -> AITimeBudget {
+        const GameStateW &state) -> AITimeBudget {
    const auto settingsGetter = settings->GetGetter();
    const auto castleCoords = AllCastleCoords(state->hex_map());

-    // Check if we're in setup phase
-    const bool isSetupPhase = state->status()->state() ==
-                              net::eagle0::shardok::storage::fb::GameStatus_::State_SET_UP;
-
-    // Get maximum budget cap from settings (in seconds)
-    const double maxBudgetSeconds =
-            settingsGetter.Backing().lookahead_time_budget_maximum_seconds();
-    const double maxBudgetMs = maxBudgetSeconds * 1000.0;
-
-    // During setup, use the setup-specific time budget
-    if (isSetupPhase) {
-        // Dynamic budget: msPerCommand × numCommands
-        const double msPerCommand =
-                settingsGetter.Backing().lookahead_time_budget_per_command_setup_ms();
-        const double budgetMs = msPerCommand * static_cast<double>(numCommands);
-
-        // Clamp to reasonable bounds: 200ms minimum, maxBudgetMs maximum
-        const auto clampedBudgetMs = std::clamp(budgetMs, 200.0, maxBudgetMs);
-        const auto remainingBudget =
-                std::chrono::milliseconds(static_cast<int64_t>(clampedBudgetMs));
-
-        const size_t minDepth = settingsGetter.Backing().min_lookahead_turns();
-
-        return AITimeBudget{
-                .remainingBudget = remainingBudget,
-                .minDepthRequired = minDepth,
-                .isCloseToEnemy = false};  // Not relevant during setup
-    }
-
    // Determine proximity (≤4 hex distance) - applies to both attackers and defenders
    bool isClose = false;
    const auto *units = state->units();
@@ -102,25 +72,12 @@ auto CalculateTimeBudget(
        }
    }

-    // Get time budget from settings - dynamic based on number of commands
-    // Dynamic budget: msPerCommand × numCommands
-    const double msPerCommand =
-            isClose ? settingsGetter.Backing().lookahead_time_budget_per_command_close_ms()
-                    : settingsGetter.Backing().lookahead_time_budget_per_command_far_ms();
-    const double budgetMs = msPerCommand * static_cast<double>(numCommands);
+    // Get time budget from settings
+    const auto budget = std::chrono::duration<double>(
+            isClose ? settingsGetter.Backing().lookahead_time_budget_close_in_seconds()
+                    : settingsGetter.Backing().lookahead_time_budget_far_in_seconds());

-    // Clamp to reasonable bounds: 200ms minimum, maxBudgetMs maximum
-    const auto clampedBudgetMs = std::clamp(budgetMs, 200.0, maxBudgetMs);
-    const auto remainingBudget = std::chrono::milliseconds(static_cast<int64_t>(clampedBudgetMs));
-
-    // TEMPORARY DEBUG OUTPUT
-    printf("[DEBUG CalculateTimeBudget] numCommands=%zu, msPerCommand=%.2f, budgetMs=%.2f, "
-           "clampedBudgetMs=%.2f, isClose=%d\n",
-           numCommands,
-           msPerCommand,
-           budgetMs,
-           clampedBudgetMs,
-           isClose);
+    const auto remainingBudget = std::chrono::duration_cast<std::chrono::milliseconds>(budget);

    // Get minimum depth requirement
    const size_t minDepth = settingsGetter.Backing().min_lookahead_turns();
@@ -36,13 +36,10 @@ struct AITimeBudget {
 };

 // Calculate time budget based on proximity to enemies and castles
-// Time budget is calculated dynamically based on number of available commands:
-//   budget = msPerCommand × numCommands (clamped to 200-5000ms)
 auto CalculateTimeBudget(
        PlayerId playerId,
        const GameSettingsSPtr &settings,
-        const GameStateW &state,
-        size_t numCommands) -> AITimeBudget;
+        const GameStateW &state) -> AITimeBudget;

 }  // namespace shardok

@@ -5,7 +5,6 @@
 #include "AIUnitScoreCalculator.hpp"

 #include <algorithm>
-#include <cstdlib>

 #include "AIAttackLocations.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
@@ -17,10 +16,9 @@ using std::end;
 using std::shared_ptr;

 constexpr double kProfessionValue = 200;
-constexpr double kVigorScoreMultiplier = 5.0;
 constexpr double kCastleMultiplierBonus = 1.0;
 constexpr double kOnFireMultiplier = 0.25;
-constexpr double kAdjacentFireMultiplier = 0.80;
+constexpr double kAdjacentFireMultiplier = 0.99;
 constexpr double kOnIceMultiplier = 0.25;
 constexpr double kMeteorStartInRangeValue = 50;
 constexpr double kMeteorDirectTargetingEnemy = 2;
@@ -64,8 +62,7 @@ auto ContextFreeUnitValue(const Unit *unit) -> ScoreValue {
                     4.0;
    }

-    const double vigorValue =
-            unit->has_attached_hero() ? unit->attached_hero().vigor() * kVigorScoreMultiplier : 0.0;
+    const double vigorValue = unit->has_attached_hero() ? unit->attached_hero().vigor() : 0.0;

    double battalionTypeMultiplier = 1.0;
    switch (unit->battalion().type()) {
@@ -91,8 +88,8 @@ auto ContextFreeUnitValue(const Unit *unit) -> ScoreValue {
            break;
    }

-    const double battalionValue = battalionTypeMultiplier * (1.0 + armament / 100.0) *
-                                  (1.0 + training / 100.0) * (0.5 + morale / 100.0) *
+    const double battalionValue = battalionTypeMultiplier * (0.5 + armament / 100.0) *
+                                  (0.5 + training / 100.0) * (0.5 + morale / 100.0) *
                                  unit->battalion().size();

    const double heroValue =
@@ -337,8 +334,7 @@ auto UnitValue(
        const AttackLocations &locationsThisSideCanAttackFrom,
        const CoordsSet &locationsInDangerFromEnemy,
        const ActionPointDistances *distances,
-        int meteorRange,
-        double meteorCastVigorCost) -> ScoreValue {
+        const SettingsGetter &settings) -> ScoreValue {
    const auto &location = unit->location();
    if (location.row() < 0) return 0;  // unplaced unit

@@ -346,8 +342,7 @@ auto UnitValue(
            unit->battalion().type() == net::eagle0::shardok::storage::fb::BattalionTypeId_UNDEAD;

    const int coordsIndex = location.row() * map->column_count() + location.column();
-    const auto *terrain = map->terrain()->Get(coordsIndex);
-
+    const auto &terrain = map->terrain()->Get(coordsIndex);
    double castleMultiplier = 1.0;
    // Only give a multiplier for being in a castle if the castle is useful, and the unit is not
    // undead
@@ -357,12 +352,14 @@ auto UnitValue(
                kCastleMultiplierBonus * (terrain->modifier().castle().integrity() + 25) / 100.0;
    }
    double onFireMultiplier = 1.0;
-    if (terrain->modifier().fire().present()) { onFireMultiplier *= kOnFireMultiplier; }
+    if (terrain->modifier().fire().present() && (isAttacker || attackerWantsCastles)) {
+        onFireMultiplier *= kOnFireMultiplier;
+    }
    {
        for (const auto adjacentCoords = HexMapUtils::GetAdjacentCoords(map, location);
             const auto &c : adjacentCoords) {
-            if (const auto *adjTerrain = GetTerrain(map, c);
-                adjTerrain && adjTerrain->modifier().fire().present()) {
+            if (const auto &adjTerrain = GetTerrain(map, c);
+                adjTerrain->modifier().fire().present()) {
                onFireMultiplier *= kAdjacentFireMultiplier;
            }
        }
@@ -381,8 +378,8 @@ auto UnitValue(
            roundsRemaining,
            attackerUnits,
            defenderUnits,
-            meteorRange,
-            meteorCastVigorCost);
+            settings.Backing().meteor_range(),
+            settings.Backing().meteor_cast_vigor_cost());

    // scouting values
    // attack range
@@ -417,7 +414,7 @@ auto UnitValue(
        if (const auto commandingUnitId = unit->commanding_unit_id(); commandingUnitId != -1) {
            const Unit *commandingUnit = nullptr;
            for (const Unit *attackerUnit : attackerUnits) {
-                if (attackerUnit && attackerUnit->unit_id() == commandingUnitId) {
+                if (attackerUnit->unit_id() == commandingUnitId) {
                    commandingUnit = attackerUnit;
                    break;
                }
@@ -425,7 +422,7 @@ auto UnitValue(

            if (commandingUnit == nullptr) {
                for (const Unit *defenderUnit : defenderUnits) {
-                    if (defenderUnit && defenderUnit->unit_id() == commandingUnitId) {
+                    if (defenderUnit->unit_id() == commandingUnitId) {
                        commandingUnit = defenderUnit;
                        break;
                    }
@@ -46,8 +46,7 @@ auto UnitValue(
        const AttackLocations &locationsThisSideCanAttackFrom,
        const CoordsSet &locationsInDangerFromEnemy,
        const ActionPointDistances *distances,
-        int meteorRange,
-        double meteorCastVigorCost) -> ScoreValue;
+        const SettingsGetter &settings) -> ScoreValue;

 }  // namespace shardok

@@ -7,9 +7,9 @@
 #include <algorithm>
 #include <ranges>

+#include "AIAttackLocations.hpp"
+#include "AIDistanceDebuf.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIDistanceDebuf.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/victory_condition.hpp"

@@ -43,8 +43,8 @@ auto AttackerDebufForOnFireCriticalTile(
        const vector<const Unit*>& extinguishingUnits,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter& settings,
+        const int braveWaterActionPointCost,
        const bool lateGame) -> double {
    double minDebuf = 99999.9;

@@ -60,8 +60,8 @@ auto AttackerDebufForOnFireCriticalTile(
                extinguishingUnits,
                apdCache,
                alCache,
-                battalionTypeGetter,
-                braveWaterCost,
+                settings,
+                braveWaterActionPointCost,
                lateGame,
                /* includeUndead = */ false);
        if (newDebuf < minDebuf) minDebuf = newDebuf;
@@ -77,8 +77,8 @@ auto AttackerDebufForUnoccupiedCriticalTile(
        const vector<const Unit*>& claimableUnits,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter& settings,
+        const int braveWaterActionPointCost,
        const bool lateGame) -> double {
    return UNHELD_VALUE * DefenderDistanceBuf(
                                  criticalTileLocation,
@@ -87,8 +87,8 @@ auto AttackerDebufForUnoccupiedCriticalTile(
                                  claimableUnits,
                                  apdCache,
                                  alCache,
-                                  battalionTypeGetter,
-                                  braveWaterCost,
+                                  settings,
+                                  braveWaterActionPointCost,
                                  lateGame,
                                  /* includeUndead = */ false);
 }
@@ -100,8 +100,8 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
        const vector<const Unit*>& attackerUnits,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost,
+        const SettingsGetter& settings,
+        const int braveWaterActionPointCost,
        const bool lateGame) {
    const double baseUnitValue =
            defenderUnit->battalion().size() +
@@ -117,8 +117,8 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
                   attackerUnits,
                   apdCache,
                   alCache,
-                   battalionTypeGetter,
-                   braveWaterCost,
+                   settings,
+                   braveWaterActionPointCost,
                   lateGame,
                   /* includeUndead = */ false);
 }
@@ -126,7 +126,10 @@ auto AttackerDebufForDefenderOccupiedCriticalTile(
 auto DefenderHoldsCriticalTilesVictoryScore(
        const GameStateW& gameState,
        const CoordsSet& criticalTileLocations,
-        const PlayerInfo* player) -> ScoreValue {
+        const PlayerInfo* player,
+        const APDCache& /*apdCache*/,
+        const ALCache& /*alCache*/,
+        const SettingsGetter& /*settings*/) -> ScoreValue {
    ScoreValue total = 0.0;

    const auto rc = gameState->hex_map()->row_count();
@@ -156,8 +159,7 @@ auto AttackerHoldsCriticalTilesVictoryScore(
        const PlayerInfo* player,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> ScoreValue {
+        const SettingsGetter& settings) -> ScoreValue {
    vector<const Unit*> playerUnits{};
    vector<const Unit*> claimablePlayerUnits{};
    for (const Unit* unit : *gameState->units()) {
@@ -173,6 +175,7 @@ auto AttackerHoldsCriticalTilesVictoryScore(
        return criticalTileLocations.size() * MAX_DEFENDER_HELD_VALUE;
    }

+    const int braveWaterActionPointCost = settings.Backing().brave_water_action_point_cost();
    const MapId mapId = apdCache->GetMapId(gameState->hex_map());

    ScoreValue total = 0.0;
@@ -199,8 +202,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                            claimablePlayerUnits,
                            apdCache,
                            alCache,
-                            battalionTypeGetter,
-                            braveWaterCost,
+                            settings,
+                            braveWaterActionPointCost,
                            IsLateGame(gameState));
                    total += BADLY_HELD_VALUE;
                }
@@ -212,8 +215,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                        playerUnits,
                        apdCache,
                        alCache,
-                        battalionTypeGetter,
-                        braveWaterCost,
+                        settings,
+                        braveWaterActionPointCost,
                        IsLateGame(gameState));
            }
        } else if (terrain->modifier().fire().present()) {
@@ -224,8 +227,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                    claimablePlayerUnits,
                    apdCache,
                    alCache,
-                    battalionTypeGetter,
-                    braveWaterCost,
+                    settings,
+                    braveWaterActionPointCost,
                    IsLateGame(gameState));
        } else {
            total -= AttackerDebufForUnoccupiedCriticalTile(
@@ -235,8 +238,8 @@ auto AttackerHoldsCriticalTilesVictoryScore(
                    claimablePlayerUnits,
                    apdCache,
                    alCache,
-                    battalionTypeGetter,
-                    braveWaterCost,
+                    settings,
+                    braveWaterActionPointCost,
                    IsLateGame(gameState));
        }
    }
@@ -249,8 +252,7 @@ auto LastPlayerStandingVictoryScore(
        const PlayerInfo* player,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> ScoreValue {
+        const SettingsGetter& settings) -> ScoreValue {
    if (!std::ranges::contains(
                *player->victory_conditions(),
                net::eagle0::shardok::storage::fb::
@@ -283,8 +285,8 @@ auto LastPlayerStandingVictoryScore(
                                                 playerUnits,
                                                 apdCache,
                                                 alCache,
-                                                 battalionTypeGetter,
-                                                 braveWaterCost,
+                                                 settings,
+                                                 5,
                                                 IsLateGame(gameState),
                                                 /* includeUndead = */ true);
    }
@@ -9,7 +9,6 @@

 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackGroups.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
@@ -30,21 +29,22 @@ auto AttackerHoldsCriticalTilesVictoryScore(
        const PlayerInfo* player,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> ScoreValue;
+        const SettingsGetter& settings) -> ScoreValue;

 auto DefenderHoldsCriticalTilesVictoryScore(
        const GameStateW& gameState,
        const CoordsSet& criticalTileLocations,
-        const PlayerInfo* player) -> ScoreValue;
+        const PlayerInfo* player,
+        const APDCache& apdCache,
+        const ALCache& alCache,
+        const SettingsGetter& settings) -> ScoreValue;

 auto LastPlayerStandingVictoryScore(
        const GameStateW& gameState,
        const PlayerInfo* player,
        const APDCache& apdCache,
        const ALCache& alCache,
-        const BattalionTypeGetter& battalionTypeGetter,
-        ActionPoints braveWaterCost) -> ScoreValue;
+        const SettingsGetter& settings) -> ScoreValue;

 }  // namespace shardok

@@ -15,7 +15,7 @@ auto UnitIdsRequiringWaterCrossing(
        const PlayerId pid,
        const CoordsSet &destinations,
        const APDCache &apdCache,
-        const BattalionTypeGetter &battalionTypeGetter) -> vector<UnitId> {
+        const SettingsGetter &settings) -> vector<UnitId> {
    // Put out all the fires, except on bridges
    fb::HexMapW mapCopy = fb::CopyHexMap(gameState->hex_map());
    for (uint32_t index = 0; index < mapCopy->terrain()->size(); index++) {
@@ -36,7 +36,7 @@ auto UnitIdsRequiringWaterCrossing(
    for (const auto *unit : *gameState->units()) {
        if (unit->player_id() != pid) continue;

-        const auto &battType = battalionTypeGetter(unit->battalion().type());
+        const auto &battType = settings.GetBattalionType(unit->battalion().type());

        if (unit->status() == net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT) {
            for (const Coords &destination : destinations) {
@@ -76,7 +76,8 @@ auto UnitIdsRequiringWaterCrossing(
 auto UnitIdsToCreateWaterCrossing(
        const GameStateW &gameState,
        const PlayerId pid,
-        const BattalionTypeGetter &battalionTypeGetter) -> vector<UnitId> {
+        const APDCache & /*apdCache*/,
+        const SettingsGetter &settings) -> vector<UnitId> {
    vector<UnitId> unitIds{};

    for (const auto *unit : *gameState->units()) {
@@ -87,7 +88,7 @@ auto UnitIdsToCreateWaterCrossing(
        if (!unit->has_attached_hero()) continue;

        const auto profession = unit->attached_hero().profession_info().profession();
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        const auto &battalionType = settings.GetBattalionType(unit->battalion().type());

        if (profession == net::eagle0::shardok::storage::fb::Profession_ENGINEER ||
            (profession == net::eagle0::shardok::storage::fb::Profession_MAGE &&
@@ -198,14 +199,14 @@ auto IntendedCrossingStarts(
        const GameStateW &gameState,
        const vector<UnitId> &unitIdsCreatingCrossing,
        const CoordsSet &tilesToStartCrossingFrom,
+        const MapId &mapId,
        const APDCache &apdCache,
-        const BattalionTypeGetter &battalionTypeGetter) -> CoordsSet {
+        const SettingsGetter &settings) -> CoordsSet {
    CoordsSet intendedCrossingStarts(gameState->hex_map());
-    const MapId mapId = apdCache->GetMapId(gameState->hex_map());
    for (const UnitId uid : unitIdsCreatingCrossing) {
        const Unit *unit = gameState->units()->Get(uid);
        const Coords &location = unit->location();
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        const auto &battalionType = settings.GetBattalionType(unit->battalion().type());
        const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);

        if (location.row() >= 0) {
@@ -218,111 +219,4 @@ auto IntendedCrossingStarts(
    return intendedCrossingStarts;
 }

-using Unit = net::eagle0::shardok::storage::fb::Unit;
-
-constexpr double kNoRequiredCrossingScore = std::numeric_limits<double>::max();
-constexpr double kNoCrossingCreatorsScore = std::numeric_limits<double>::min();
-
-auto WaterCrossingScore(
-        const PlayerId playerId,
-        const BattalionTypeGetter &battalionTypeGetter,
-        const GameStateW &gameState,
-        const CoordsSet &castleCoords,
-        const CoordsSet &startCrossingFrom,
-        const APDCache &apdCache) -> double {
-    uint32_t castleClaimCount = 0;
-    for (const auto *unit : *gameState->units()) {
-        if (unit->player_id() != playerId) continue;
-        const auto status = unit->status();
-        if (status != net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT &&
-            status != net::eagle0::shardok::storage::fb::UnitStatus_RESERVE_UNIT)
-            continue;
-        if (!unit->has_attached_hero()) continue;
-
-        ++castleClaimCount;
-    }
-
-    CoordsSet destinations = castleCoords;
-    if (castleClaimCount < castleCoords.size()) {
-        destinations = CoordsSet(gameState->hex_map());
-        for (const auto *enemyUnit : *gameState->units()) {
-            if (enemyUnit->player_id() == playerId) continue;
-            const auto status = enemyUnit->status();
-            if (status != net::eagle0::shardok::storage::fb::UnitStatus_NORMAL_UNIT) continue;
-            AssertValid(enemyUnit->location(), gameState->hex_map());
-            destinations.Add(enemyUnit->location());
-        }
-    }
-
-    const auto unitIdsRequiringCrossing = UnitIdsRequiringWaterCrossing(
-            gameState,
-            playerId,
-            castleCoords,
-            apdCache,
-            battalionTypeGetter);
-    if (unitIdsRequiringCrossing.empty()) return kNoRequiredCrossingScore;
-
-    const auto unitIdsCreatingCrossing =
-            UnitIdsToCreateWaterCrossing(gameState, playerId, battalionTypeGetter);
-    if (unitIdsCreatingCrossing.empty()) return kNoCrossingCreatorsScore;
-
-    double totalScore = 0;
-
-    const auto mapId = ActionPointDistancesCache::GetMapId(gameState->hex_map());
-
-    // First put a big penalty on the distance for units that can create a crossing
-    for (const UnitId uid : unitIdsCreatingCrossing) {
-        const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
-        Coords location = unit->location();
-
-        int thisDistance;
-        if (location.row() < 0) thisDistance = 1000;
-        else {
-            const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);
-
-            thisDistance = MinimumDistance(apd, location, startCrossingFrom);
-        }
-
-        totalScore -= thisDistance * 100.0;
-    }
-
-    // Now a smaller penalty for distance for units that need to cross, except if they block -- then
-    // a large penalty
-    for (const UnitId uid : unitIdsRequiringCrossing) {
-        // If this unit ID can also create a crossing, we already handled it
-        if (std::ranges::contains(unitIdsCreatingCrossing, uid)) continue;
-
-        const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
-        Coords location = unit->location();
-        const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);
-
-        int thisDistance;
-        if (location.row() < 0) thisDistance = 1000;
-        else { thisDistance = MinimumDistance(apd, location, startCrossingFrom); }
-
-        bool targetBlocks = false;
-        // If we're not capable of creating a crossing, don't get in the way of somebody that is.
-        for (const UnitId crossingUid : unitIdsCreatingCrossing) {
-            const auto *crossingCapableUnit = gameState->units()->Get(crossingUid);
-
-            // Don't check for units that aren't yet placed
-            if (crossingCapableUnit->location().row() < 0) continue;
-            AssertValid(crossingCapableUnit->location(), gameState->hex_map());
-
-            if (thisDistance <
-                MinimumDistance(apd, crossingCapableUnit->location(), startCrossingFrom)) {
-                targetBlocks = true;
-                break;
-            }
-        }
-        if (targetBlocks) continue;
-
-        totalScore -= thisDistance;
-    }
-
-    return totalScore;
-}
-
 }  // namespace shardok
@@ -5,7 +5,6 @@
 #ifndef EAGLE0_AIWATERCROSSINGCALCULATOR_HPP
 #define EAGLE0_AIWATERCROSSINGCALCULATOR_HPP

-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
@@ -35,13 +34,14 @@ auto UnitIdsRequiringWaterCrossing(
        PlayerId pid,
        const CoordsSet& destinations,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter) -> vector<UnitId>;
+        const SettingsGetter& settings) -> vector<UnitId>;

 // Units belonging to the player that are capable of creating water crossings
 auto UnitIdsToCreateWaterCrossing(
        const GameStateW& gameState,
        PlayerId pid,
-        const BattalionTypeGetter& battalionTypeGetter) -> vector<UnitId>;
+        const APDCache& apdCache,
+        const SettingsGetter& settings) -> vector<UnitId>;

 // Whether a unit of the given type can reach destination from origin, given the current state
 // of the map
@@ -71,17 +71,9 @@ auto IntendedCrossingStarts(
        const GameStateW& gameState,
        const vector<UnitId>& unitIdsCreatingCrossing,
        const CoordsSet& tilesToStartCrossingFrom,
+        const MapId& mapId,
        const APDCache& apdCache,
-        const BattalionTypeGetter& battalionTypeGetter) -> CoordsSet;
-
-// Calculate score based on water crossing strategy
-auto WaterCrossingScore(
-        PlayerId playerId,
-        const BattalionTypeGetter& battalionTypeGetter,
-        const GameStateW& gameState,
-        const CoordsSet& castleCoords,
-        const CoordsSet& startCrossingFrom,
-        const APDCache& apdCache) -> double;
+        const SettingsGetter& settings) -> CoordsSet;

 }  // namespace shardok

@@ -18,7 +18,7 @@ constexpr ScoreValue kNoRequiredCrossingScore = std::numeric_limits<ScoreValue>:
 constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>::min();

 [[nodiscard]] auto AIWaterCrossingCommandChooser::WaterCrossingScore(
-        const BattalionTypeGetter &battalionTypeGetter,
+        const SettingsGetter &settingsGetter,
        const GameStateW &gameState,
        const CoordsSet &castleCoords,
        const CoordsSet &startCrossingFrom) const -> ScoreValue {
@@ -51,13 +51,15 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
            playerId,
            castleCoords,
            apdCache,
-            battalionTypeGetter);
+            settingsGetter);
    if (unitIdsRequiringCrossing.empty()) return kNoRequiredCrossingScore;

    const auto unitIdsCreatingCrossing =
-            UnitIdsToCreateWaterCrossing(gameState, playerId, battalionTypeGetter);
+            UnitIdsToCreateWaterCrossing(gameState, playerId, apdCache, settingsGetter);
    if (unitIdsCreatingCrossing.empty()) return kNoCrossingCreatorsScore;

+    fprintf(stderr, "%lu units require a water crossing\n", unitIdsRequiringCrossing.size());
+
    ScoreValue totalScore = 0;

    const auto mapId = ActionPointDistancesCache::GetMapId(gameState->hex_map());
@@ -65,7 +67,7 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
    // First put a big penalty on the distance for units that can create a crossing
    for (const UnitId uid : unitIdsCreatingCrossing) {
        const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        const auto &battalionType = settingsGetter.GetBattalionType(unit->battalion().type());
        Coords location = unit->location();

        int thisDistance;
@@ -86,7 +88,7 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
        if (std::ranges::contains(unitIdsCreatingCrossing, uid)) continue;

        const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        const auto &battalionType = settingsGetter.GetBattalionType(unit->battalion().type());
        Coords location = unit->location();
        const auto *apd = apdCache->GetRaw(gameState->hex_map(), mapId, battalionType, false);

@@ -118,7 +120,7 @@ constexpr ScoreValue kNoCrossingCreatorsScore = std::numeric_limits<ScoreValue>:
 }

 auto AIWaterCrossingCommandChooser::StartCrossingFrom(
-        const BattalionTypeGetter &battalionTypeGetter,
+        const SettingsGetter &settingsGetter,
        const GameStateW &gameState,
        const CoordsSet &castleCoords) const -> CoordsSet {
    CoordsSet startCrossingFrom(gameState->hex_map());
@@ -152,16 +154,16 @@ auto AIWaterCrossingCommandChooser::StartCrossingFrom(
            playerId,
            castleCoords,
            apdCache,
-            battalionTypeGetter);
+            settingsGetter);
    if (unitIdsRequiringCrossing.empty()) return startCrossingFrom;

    const auto unitIdsCreatingCrossing =
-            UnitIdsToCreateWaterCrossing(gameState, playerId, battalionTypeGetter);
+            UnitIdsToCreateWaterCrossing(gameState, playerId, apdCache, settingsGetter);
    if (unitIdsCreatingCrossing.empty()) return startCrossingFrom;

    for (const UnitId uid : unitIdsRequiringCrossing) {
        const Unit *unit = gameState->units()->Get(uid);
-        const auto &battalionType = battalionTypeGetter(unit->battalion().type());
+        const auto &battalionType = settingsGetter.GetBattalionType(unit->battalion().type());
        Coords origin = unit->location();

        // FIXME: this is just grabbing the first starting position, ideally we'd try them all
@@ -6,16 +6,19 @@
 #define EAGLE0_AIWATERCROSSINGCOMMANDCHOOSER_HPP

 #include <utility>
+#include <vector>

-#include "src/main/cpp/net/eagle0/shardok/ai/AICommonTypes.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
+#include "src/main/cpp/net/eagle0/shardok/library/fb_helpers/FlatbufferWrapper.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
 #include "src/main/flatbuffer/net/eagle0/shardok/storage/game_state.hpp"
+#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"

 namespace shardok {

+using CommandProto = net::eagle0::shardok::api::CommandDescriptor;
 using GameState = net::eagle0::shardok::storage::fb::GameState;
 using Unit = net::eagle0::shardok::storage::fb::Unit;
 using ScoreValue = double;
@@ -30,13 +33,13 @@ public:
        : playerId(pid),
          apdCache(std::move(apdCache)) {}

-    [[nodiscard]] auto StartCrossingFrom(
-            const BattalionTypeGetter &battalionTypeGetter,
+    auto StartCrossingFrom(
+            const SettingsGetter &settingsGetter,
            const GameStateW &gameState,
            const CoordsSet &castleCoords) const -> CoordsSet;

    [[nodiscard]] auto WaterCrossingScore(
-            const BattalionTypeGetter &battalionTypeGetter,
+            const SettingsGetter &settingsGetter,
            const GameStateW &gameState,
            const CoordsSet &castleCoords,
            const CoordsSet &startCrossingFrom) const -> ScoreValue;
@@ -210,556 +210,4 @@ Where:
 - **Magnitude**: Indicates confidence/importance of the evaluation
 - **Relative scoring**: Only score differences matter, not absolute values

-This scoring system provides a robust framework for tactical AI decision-making, balancing immediate tactical gains with strategic objectives while handling the uncertainty inherent in combat outcomes.
-
-## AIScoreCalculator Function Reference
-
-### Public Interface Functions
-
-#### `GuessedStateScore`
-**Purpose**: Evaluates the score of a game state from the perspective of the current AI strategy without performing any commands.
-
-**Parameters**:
- `isDefender`: Whether the AI is playing as defender
- `state`: Current game state to evaluate
- `aiStrategy`: Strategy being used (attack castles, hold castles, scatter, etc.)
- `allCastleCoords`: Set of all castle coordinates on the map
- `settingsGetter`: Game configuration and rules
- `apdCache`: Cached action point distances for movement calculations
- `alCache`: Cached attack locations for combat calculations
-
-**Returns**: Score value representing how favorable the state is for the evaluating player (positive = good, negative = bad)
-
-#### `CommandScore`
-**Purpose**: Evaluates the score for a specific command using lookahead search to consider future consequences.
-
-**Parameters**:
- `pid`: Player ID executing the command
- `isDefender`: Whether the player is a defender
- `remainingLookahead`: Depth of recursive search remaining
- `maxRepeatCount`: Number of random simulations for non-deterministic commands
- `guessedEngine`: Current game engine state
- `attackerStrategy`: Strategy being used by attackers
- `currentUtility`: Current game state score before command execution
- `settingsGetter`: Game configuration
- `allCastleCoords`: Castle locations
- `apdCache` & `alCache`: Cached distance/attack calculations
- `commandIndex`: Index of command to evaluate
- `deadline`: Time limit for computation
-
-**Returns**: Future containing the final score after lookahead evaluation
-
-### Internal Core Functions
-
-#### `BuildDecisionTree` (NEW)
-**Purpose**: Builds a complete decision tree containing all evaluated command paths up to the specified depth.
-
-**Process**:
-1. Filters commands using `AICommandFilter` to reduce search space
-2. For each command, calls `ExecuteCommandForTree` to build complete subtrees
-3. Returns full tree with all possible moves and their consequences
-4. Identifies best command within the complete tree structure
-
-**Returns**: `std::future<CommandDecisionTree>` containing the complete decision tree
-
-#### `BestCommandIndex` (Legacy - Wrapper)
-**Purpose**: Backward compatibility wrapper that uses `BuildDecisionTree` but returns traditional `IndexAndScore`.
-
-**Process**:
-1. Calls `BuildDecisionTree` to get complete tree
-2. Extracts best command information for compatibility
-3. Returns only the optimal command details in legacy format
-
-#### `ExecuteCommandForTree` (NEW)
-**Purpose**: Executes a command and creates a tree node with the resulting game state and scores.
-
-**Process**:
-1. Creates engine copy and executes the command with given random seed
-2. Creates `CommandTreeNode` with command results and game state
-3. Calculates immediate score using `GuessedStateScore`
-4. Calls `RecursiveTreeBuilder` to populate child nodes if depth allows
-5. Calculates lookahead score from children (or uses immediate score)
-
-**Returns**: `std::unique_ptr<CommandTreeNode>` containing the command execution results and subtree
-
-#### `RecursiveTreeBuilder` (NEW)
-**Purpose**: Recursively populates child nodes of a tree node by building subtrees for subsequent moves.
-
-**Process**:
-1. Gets available commands for the next player
-2. Filters commands to reduce search space
-3. For each command, calls `ExecuteCommandForTree` to create child nodes
-4. Handles different command types (deterministic, odds-based, random)
-5. Populates the parent node's children vector with complete subtrees
-
-#### `CalcOne` (Legacy)
-**Purpose**: Executes a single command simulation with specified randomness and returns both immediate and lookahead scores.
-
-**Process**:
-1. Creates engine copy and executes the command with given random seed
-2. Calculates immediate score using `GuessedStateScore`
-3. Initiates recursive lookahead calculation if depth remains
-4. Handles timeouts gracefully by returning default scores
-
-#### `EvaluateCommand`
-**Purpose**: Lower-level command evaluation that handles different command types appropriately.
-
-**Command Type Handling**:
- **Deterministic**: Single evaluation with average randomness (0.5)
- **Odds-based**: Two evaluations (success/failure) weighted by success probability
- **Non-deterministic**: Multiple evaluations with distributed random values, averaged
-
-#### `BasicLookaheadCalculator`
-**Purpose**: Recursive lookahead search that finds the best future command sequence and propagates scores backward.
-
-**Features**:
- Uses transposition table to cache previously computed positions
- Handles depth limits and terminal states
- Returns futures for asynchronous computation
- Stores results in transposition table for reuse
-
-### Strategy-Specific Scoring Functions
-
-#### `AttackerScoreForState`
-**Purpose**: Calculates state score from attacker perspective based on strategy type.
-
-**Strategy Support**:
- `STRATEGY_ATTACK_CASTLES`: Prioritizes capturing castle positions
- `STRATEGY_ATTACK_UNITS`: Focuses on eliminating defender units
- `STRATEGY_HOLD_CASTLES`: Maintains control of captured castles
- `STRATEGY_CROSS_RIVERS`: Special water crossing objectives
- `STRATEGY_FLEE`: Escape-focused scoring
-
-#### `DefenderScoreForState`
-**Purpose**: Calculates state score from defender perspective.
-
-**Strategy Support**:
- `STRATEGY_HOLD_CASTLES`: Defend critical castle positions
- `STRATEGY_SCATTER`: Spread units to avoid elimination
- `STRATEGY_FLEE`: Escape-focused scoring
-
-#### `AttackerUnitsScore`
-**Purpose**: Core unit valuation function that calculates total value of all units on the board with contextual modifiers.
-
-**Features**:
- Uses `UnitValue` for individual unit calculations
- Applies distance multipliers based on proximity to objectives
- Handles special cases like undead, VIP units, and scattered defenders
- Incorporates castle bonuses and environmental penalties
-
-### Specialized Strategy Functions
-
-#### `DefenderScatterStrategyScoreForState`
-**Purpose**: Implements scatter strategy scoring that rewards defensive units for staying far from enemies and friendlies.
-
-#### `DefenderHoldCastlesStrategyScoreForState`
-**Purpose**: Implements castle defense strategy with victory condition scoring.
-
-#### `FleeStrategyScoreForState`
-**Purpose**: Implements flee strategy that heavily penalizes remaining on the battlefield.
-
-### Utility Functions
-
-#### `AttackerMultiplierForTargetDistance`
-**Purpose**: Calculates distance-based scoring multipliers for attackers based on proximity to priority targets.
-
-**Features**:
- Uses recursive priority list evaluation
- Accounts for occupied vs. unoccupied targets
- Incorporates brave water crossing capabilities
- Uses cached action point distances for efficiency
-
-#### `CommandSorter`
-**Purpose**: Comparison function for ranking commands by lookahead score (primary) and immediate score (tiebreaker).
-
-#### `IsDeterministic`
-**Purpose**: Determines if a command type has predictable outcomes or requires random simulation.
-
-### Performance and Caching
-
-#### `EffectiveDistanceCache`
-**Purpose**: Memoization cache for expensive distance calculations between units and targets.
-
-#### `AttackerScorePerformanceLogger`
-**Purpose**: Performance monitoring system that tracks call frequency and timing for `AttackerScoreForState`.
-
-The function architecture supports parallel evaluation, caching, and recursive lookahead while maintaining separation between strategy-specific logic and core evaluation mechanics.
-
-## Decision Tree Data Structures (NEW)
-
-### CommandTreeNode
-**Purpose**: Represents a single command execution and its consequences in the decision tree.
-
-**Key Fields**:
- `commandIndex`: Index of the command in the original command list
- `commandType`: Type of command (MOVE, MELEE, END_TURN, etc.)
- `immediateScore`: Score of the game state immediately after this command
- `lookaheadScore`: Best achievable score considering future moves
- `resultingGameState`: Game state after command execution
- `children`: Vector of child nodes representing subsequent possible moves
- `playerId`, `depth`, `isDefender`: Metadata about the command context
-
-**Features**:
- Stores complete game state for each decision point
- Maintains parent-child relationships for tree traversal
- Supports both immediate and lookahead scoring
- Contains metadata for debugging and analysis
-
-### CommandDecisionTree
-**Purpose**: Complete decision tree containing all evaluated command paths from a given position.
-
-**Key Fields**:
- `rootNodes`: All possible first moves from the starting position
- `bestCommand`: Pointer to the optimal root command
- `maxDepth`: Maximum lookahead depth of the tree
- `totalNodes`: Total number of nodes in the tree (for statistics)
-
-**Features**:
- Provides complete visibility into AI decision-making process
- Enables analysis of alternative moves and their consequences
- Supports tree statistics and debugging information
- Maintains backward compatibility through `GetBestCommandIndex()`
-
-**Memory Management**:
- Uses `std::unique_ptr` for automatic memory cleanup
- `GameStateW` objects are stored directly (not shared pointers for simplicity)
- Tree structure ensures proper cleanup when nodes go out of scope
-
-### Tree vs. Legacy Approach Comparison
-
-| Aspect | Legacy (Single Best) | Tree-Based (Complete) |
-|--------|---------------------|----------------------|
-| **Output** | Best command only | Complete decision tree |
-| **Memory** | Minimal | Higher (stores all paths) |
-| **Analysis** | Limited visibility | Full decision transparency |
-| **Debugging** | Single command info | Complete move sequences |
-| **Performance** | Slightly faster | Comparable (same calculations) |
-| **Compatibility** | Direct usage | Wrapper maintains compatibility |
-
-### Usage Patterns
-
-**For AI Decision Making**:
-```cpp
-auto treeFuture = BuildDecisionTree(pid, isDefender, depth, maxRepeat,
-                                   engine, strategy, utility, settings,
-                                   castles, apdCache, alCache, deadline);
-CommandDecisionTree tree = treeFuture.get();
-size_t bestCommand = tree.bestCommand->commandIndex;
-```
-
-**For Analysis and Debugging**:
-```cpp
-CommandDecisionTree tree = treeFuture.get();
-// Examine all possible moves
-for (const auto& rootNode : tree.rootNodes) {
-    std::cout << "Command " << rootNode->commandIndex
-              << " Score: " << rootNode->lookaheadScore << std::endl;
-    // Traverse children to see consequences
-    for (const auto& child : rootNode->children) {
-        // ... analyze child moves
-    }
-}
-```
-
-**Legacy Compatibility**:
-```cpp
-// Existing code continues to work unchanged
-auto indexScoreFuture = BestCommandIndex(pid, isDefender, ...);
-IndexAndScore result = indexScoreFuture.get();
-size_t bestCommand = result.index;
-```
-
-The tree-based approach provides complete decision transparency while maintaining full backward compatibility with existing AI code.
-
-## MCTS Alternative: Randomness Handling Recommendations
-
-The new MCTS-based AI system is available in `MCTSAI.hpp/.cpp` and provides an alternative to the iterative deepening approach. However, the current MCTS implementation uses simplified randomness handling compared to the sophisticated approach in the original system.
-
-### Current MCTS Limitations
-
-1. **Expansion Phase**: Uses average rolls (0.5) for all commands during tree expansion
-2. **Simulation Phase**: Uses random command selection with average rolls
-3. **Missing**: No explicit chance nodes for commands with `HasOdds()`
-4. **Missing**: No multi-sample evaluation for stochastic commands
-
-### Recommended Improvements: Chance Node Integration
-
-#### 1. **Explicit Chance Nodes** (Highest Priority)
-
-For commands with `HasOdds()`, create explicit chance nodes in the MCTS tree:
-
-```cpp
-// During MCTSExpansion
-if (descriptor->HasOdds()) {
-    // Create TWO child nodes: success and failure
-    auto successNode = CreateMCTSNode(commandIndex, SUCCESS_VARIANT);
-    auto failureNode = CreateMCTSNode(commandIndex, FAILURE_VARIANT);
-
-    // Execute with deterministic rolls (matching original system)
-    ExecuteWithRoll(successNode, 1.0 - successChance/2.0);  // High roll
-    ExecuteWithRoll(failureNode, (1.0 - successChance)/2.0); // Low roll
-
-    // Set probability weights for selection
-    successNode->probabilityWeight = successChance;
-    failureNode->probabilityWeight = 1.0 - successChance;
-}
-```
-
-#### 2. **Weighted Selection for Chance Nodes**
-
-Modify `MCTSSelection` to handle chance nodes:
-
-```cpp
-if (node->isChanceNode) {
-    // Select based on probability distribution, not UCB1
-    return SelectByProbability(node->children);
-} else {
-    // Normal UCB1 selection for decision nodes
-    return node->GetBestChild(explorationConstant);
-}
-```
-
-#### 3. **Probability-Weighted Backpropagation**
-
-Update backpropagation to account for chance node probabilities:
-
-```cpp
-void MCTSBackpropagation(MCTSNode* node, double reward) {
-    while (node) {
-        node->visitCount++;
-
-        // Weight reward by probability for chance nodes
-        double weightedReward = reward;
-        if (node->parent && node->parent->isChanceNode) {
-            weightedReward *= node->probabilityWeight;
-        }
-
-        node->totalReward += weightedReward;
-        node->averageReward = node->totalReward / node->visitCount;
-        node = node->parent;
-    }
-}
-```
-
-#### 4. **Multi-Sample Commands**
-
-For commands without explicit odds but with randomness, use stratified sampling:
-
-```cpp
-// During expansion, create multiple child nodes with different rolls
-for (int sample = 0; sample < numSamples; ++sample) {
-    double roll = static_cast<double>(sample) / (numSamples - 1);
-    auto sampleNode = CreateMCTSNodeWithRoll(commandIndex, roll);
-    sampleNode->probabilityWeight = 1.0 / numSamples;
-}
-```
-
-### Benefits of Chance Node Integration
-
-1. **Accurate Evaluation**: Preserves the sophisticated randomness handling from the original system
-2. **Better Convergence**: MCTS can properly explore both success/failure outcomes
-3. **Realistic Simulations**: Tree accurately represents game's probability distributions
-4. **Comparable Results**: Makes MCTS results directly comparable to iterative deepening
-
-### Implementation Priority
-
-1. **Phase 1**: Add explicit chance nodes for `HasOdds()` commands
-2. **Phase 2**: Implement probability-weighted selection and backpropagation
-3. **Phase 3**: Add multi-sample support for general stochastic commands
-4. **Phase 4**: Optimize performance with lazy expansion of chance nodes
-
-### Alternative: Determinization Approach
-
-If explicit chance nodes prove too complex, consider **determinization**:
-
- Run multiple MCTS trees with different fixed random seeds
- Aggregate results across all determinizations
- Simpler to implement but potentially less accurate than explicit chance nodes
-
-### Switching Between AI Systems
-
-Both AI systems (`IterativeDeepeningAI` and `MCTSAI`) implement compatible interfaces. The algorithm is selected at **runtime** via the ShardokAIClient constructor:
-
-```cpp
-// Using Iterative Deepening (default)
-ShardokAIClient client(playerId, isDefender, hexMap, settings);
-// Or explicitly:
-ShardokAIClient client(playerId, isDefender, hexMap, settings,
-                      AIAlgorithmType::ITERATIVE_DEEPENING);
-
-// Using MCTS
-ShardokAIClient client(playerId, isDefender, hexMap, settings,
-                      AIAlgorithmType::MCTS);
-
-// Note: MCTS configuration can be customized via MCTSConfig:
-// - maxIterations: 10000 (max MCTS iterations per move)
-// - maxSimulationDepth: 10 (depth for rollout phase)
-// - maxTreeDepth: 20 (max tree depth to prevent stack overflow)
-// - explorationConstant: 1.414 (UCB1 exploration vs exploitation)
-// - useMultithreading: true (APD cache is thread-safe with TLS + mutex protection)
-// - numThreads: 4
-```
-
-The selection is made per AI client instance, allowing different algorithms for different players or game situations within the same server process.
-
-#### Direct AI Usage (Lower Level)
-
-Both AI systems can also be used directly:
-
-```cpp
-// Using Iterative Deepening directly
-auto iterativeAI = IterativeDeepeningAI(playerId, isDefender, strategy,
-                                       castleCoords, apdCache, alCache);
-auto result = iterativeAI.IterativeSearch(settings, state, commands, budget);
-
-// Using MCTS directly
-auto mctsAI = MCTSAI(playerId, isDefender, strategy,
-                    castleCoords, apdCache, alCache);
-auto result = mctsAI.Search(settings, state, commands, budget);
-```
-
-#### Algorithm Comparison
-
-| Feature | Iterative Deepening | MCTS |
-|---------|-------------------|------|
-| **Randomness Handling** | Sophisticated (chance nodes, multi-sample) | Simplified (average rolls) |
-| **Performance** | Single-threaded | Multithreaded |
-| **Search Type** | Fixed depth with iterative deepening | Adaptive with time budget |
-| **Memory Usage** | Lower | Higher (maintains tree) |
-| **Max Tree Depth** | Limited by lookahead setting | Limited by `maxTreeDepth` config (default: 20) |
-| **Tree Destruction** | Not applicable | Iterative (avoids stack overflow) |
-| **Best For** | Precise evaluation, production | Performance testing, fast decisions |
-
-The MCTS implementation provides a solid foundation. Known limitations:
-1. **Randomness Handling**: Simplified compared to iterative deepening (no explicit chance nodes)
-2. **Simulation Quality**: Uses random rollouts instead of sophisticated evaluation
-
-Note: The APD cache is fully thread-safe using thread-local storage and mutex-protected shared cache.
-
-Adding chance node handling and ensuring thread safety would make it a superior replacement for the iterative deepening approach while maintaining the sophisticated randomness evaluation that makes the current system effective.
-
-## MCTS Configuration Options
-
-The MCTS AI system provides extensive configuration through the `MCTSConfig` structure:
-
-### Core MCTS Parameters
-
-```cpp
-struct MCTSConfig {
-    double explorationConstant = 1.414;  // UCB1 constant (sqrt(2) by default)
-    int maxSimulationDepth = 1000;       // Maximum depth for rollout
-    int maxTreeDepth = 2000;             // Maximum tree depth to prevent stack overflow
-    bool useMultithreading = true;       // Enable parallel MCTS
-    int numThreads = 16;                 // Number of threads for parallel MCTS (when enabled)
-    MCTSSimulationPolicy simulationPolicy = MCTSSimulationPolicy::BEST_IMMEDIATE;
-    bool enableTranspositionDetection = true;  // Enable pruning of duplicate states
-    double immediateScoreTieBreakThreshold = 5.0;  // When avg rewards differ by less than this, prefer higher immediate score
-    double visitCountTolerance = 0.05;  // Treat visit counts as equal if within this % of best count
-    bool enableImmediateScoreInUCB1 = true;  // Apply immediate score tie-breaking in UCB1 selection too
-};
-```
-
-### Exploration vs Exploitation
-
- **`explorationConstant`**: Controls the exploration vs exploitation balance in UCB1 selection
-  - Higher values (>1.414): More exploration of unvisited nodes
-  - Lower values (<1.414): More exploitation of known good moves
-  - Default: 1.414 (√2, theoretical optimum for UCB1)
-
-### Tree Structure Limits
-
- **`maxTreeDepth`**: Prevents stack overflow in deep game trees
-  - Default: 2000 (very high limit for most tactical scenarios)
-  - Terminal detection stops expansion when this depth is reached
-
- **`maxSimulationDepth`**: Controls rollout length during simulation phase
-  - Default: 1000 (sufficient for most tactical scenarios)
-  - Longer simulations provide more accurate estimates but use more time
-
-### Multithreading Configuration
-
- **`useMultithreading`**: Enable/disable parallel MCTS execution
-  - Default: true (takes advantage of modern multi-core CPUs)
-  - Requires thread-safe game engine and scoring components
-
- **`numThreads`**: Number of worker threads for parallel tree building
-  - Default: 16 (adjust based on available CPU cores)
-  - More threads can improve search speed but with diminishing returns
-
-### Simulation Policies
-
-The `MCTSSimulationPolicy` enum controls how commands are selected during the rollout phase:
-
- **`RANDOM`**: Pure random selection from all available commands
-  - Fastest but least informed simulations
-  - Good baseline for testing MCTS convergence
-
- **`FILTERED_RANDOM`**: Random selection from AICommandFilter-approved commands
-  - Eliminates obviously bad moves (moving away from objectives, etc.)
-  - Better simulation quality with minimal overhead
-
- **`BEST_IMMEDIATE`**: Always choose command with highest immediate score
-  - Most informed simulations
-  - Slower but higher quality rollouts
-  - Default setting for production use
-
- **`WEIGHTED_BEST_IMMEDIATE`**: Random selection weighted by immediate score ranking
-  - Balances exploration with informed choice
-  - Alternative to pure greedy selection
-
-### Transposition Detection
-
- **`enableTranspositionDetection`**: Enable pruning of duplicate game states
-  - Default: true (improves search efficiency)
-  - Uses hash-based state identification
-  - Prevents wasted computation on equivalent positions reached via different move sequences
-
-### Immediate Score Tie-Breaking
-
-These settings address MCTS's tendency to choose indirect paths when direct paths lead to the same outcome:
-
- **`immediateScoreTieBreakThreshold`**: Score difference threshold for tie-breaking
-  - Default: 5.0 (when backpropagated rewards differ by less than this, prefer immediate score)
-  - Helps AI choose direct moves over equivalent indirect sequences
-  - Improves user experience by reducing unnecessary intermediate moves
-
- **`visitCountTolerance`**: Visit count equality threshold for tie-breaking
-  - Default: 0.05 (5% tolerance - visit counts within this percentage are considered equal)
-  - Prevents minor visit count differences from overriding immediate score preferences
-
- **`enableImmediateScoreInUCB1`**: Apply immediate score tie-breaking during exploration
-  - Default: true (consistent tie-breaking in both exploration and final selection)
-  - When UCB1 values are very close, prefer nodes with higher immediate scores
-  - Improves convergence on direct paths to objectives
-
-### Usage Example
-
-```cpp
-// Custom MCTS configuration for performance testing
-MCTSConfig config;
-config.explorationConstant = 2.0;  // More exploration
-config.simulationPolicy = MCTSSimulationPolicy::FILTERED_RANDOM;  // Faster rollouts
-config.numThreads = 8;  // Reduce threads for testing environment
-config.immediateScoreTieBreakThreshold = 10.0;  // More aggressive tie-breaking
-
-MCTSAI ai(playerId, isDefender, strategy, castleCoords, apdCache, alCache, config);
-```
-
-### Configuration Recommendations
-
-**For Production Use:**
- Use default settings for balanced performance and quality
- Consider reducing `numThreads` on systems with limited CPU cores
- `BEST_IMMEDIATE` simulation policy provides highest quality decisions
-
-**For Performance Testing:**
- `FILTERED_RANDOM` or `RANDOM` simulation policies for faster rollouts
- Lower `explorationConstant` (1.0) for more exploitation
- Disable transposition detection for baseline comparison
-
-**For Analysis/Debugging:**
- Single-threaded execution (`useMultithreading = false`) for deterministic results
- Higher `immediateScoreTieBreakThreshold` to emphasize direct paths
- `BEST_IMMEDIATE` simulation for most predictable behavior
-
-The configuration system allows fine-tuning MCTS behavior for different scenarios while maintaining compatibility with the existing AI infrastructure.
+This scoring system provides a robust framework for tactical AI decision-making, balancing immediate tactical gains with strategic objectives while handling the uncertainty inherent in combat outcomes.
@@ -1,16 +1,5 @@
 load("//tools:copts.bzl", "COPTS")

-cc_library(
-    name = "ai_common_types",
-    hdrs = ["AICommonTypes.hpp"],
-    copts = COPTS,
-    visibility = ["//visibility:public"],
-    deps = [
-        "//src/main/cpp/net/eagle0/shardok/library:battalion_type",
-        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
-    ],
-)
-
 cc_library(
    name = "ai_attacker_strategy_selector",
    srcs = ["AIAttackerStrategySelector.cpp"],
@@ -39,15 +28,14 @@ cc_library(
    hdrs = ["AIAttackGroups.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
+        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
    deps = [
        ":ai_attack_locations",
-        ":ai_common_types",
        ":ai_score_utilities",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
+        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:hex_map_cc_fbs",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:unit_cc_fbs",
@@ -59,10 +47,6 @@ cc_library(
    srcs = ["AIAttackLocations.cpp"],
    hdrs = ["AIAttackLocations.hpp"],
    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
    deps = [
        ":ai_score_utilities",
        "//src/main/cpp/net/eagle0/shardok/library/map:terrain",
@@ -101,14 +85,11 @@ cc_library(
    hdrs = ["AIDistanceDebuf.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
    ],
    deps = [
        ":ai_attack_locations",
-        ":ai_common_types",
        ":ai_score_utilities",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
@@ -137,10 +118,8 @@ cc_library(
    hdrs = ["AIScoreUtilities.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
    ],
    deps = [
        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
@@ -163,48 +142,9 @@ cc_library(
        ":ai_score_utilities",
        ":ai_unit_score_calculator",
        "//src/main/cpp/net/eagle0/shardok/library:engine",
+        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
-    ],
-)
-
-cc_library(
-    name = "ai_heuristic_weighting",
-    srcs = ["AIHeuristicWeighting.cpp"],
-    hdrs = ["AIHeuristicWeighting.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts/adapters:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
-        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
-    ],
-)
-
-cc_library(
-    name = "ai_command_evaluator",
-    srcs = ["AICommandEvaluator.cpp"],
-    hdrs = ["AICommandEvaluator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
-    ],
-    deps = [
-        ":ai_command_filter",
-        ":ai_strategy",
-        ":transposition_table",
-        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
-        "//src/main/cpp/net/eagle0/shardok/library/util:hex_cube_utils",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
+        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
    ],
 )

@@ -214,33 +154,39 @@ cc_library(
    hdrs = ["AICommandFilter.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts/adapters:__pkg__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
    deps = [
-        ":ai_common_types",
        "//src/main/cpp/net/eagle0/shardok/library:engine",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
+        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
    ],
 )

 cc_library(
-    name = "transposition_table",
-    srcs = ["TranspositionTable.cpp"],
-    hdrs = ["TranspositionTable.hpp"],
+    name = "ai_score_calculator",
+    srcs = ["AIScoreCalculator.cpp"],
+    hdrs = ["AIScoreCalculator.hpp"],
    copts = COPTS,
    visibility = [
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
    deps = [
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
+        ":ai_attacker_strategy_selector",
+        ":ai_command_filter",
+        ":ai_unit_score_calculator",
+        ":ai_victory_condition_score_calculator",
+        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
+        "//src/main/cpp/net/eagle0/common:task_result",
+        "//src/main/cpp/net/eagle0/common:thread_pool",
+        "//src/main/cpp/net/eagle0/shardok/library:engine",
+        "//src/main/cpp/net/eagle0/shardok/library/view_filters:game_state_guesser",
    ],
 )

@@ -250,13 +196,11 @@ cc_library(
    hdrs = ["AIStrategy.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
    ],
    deps = [
        ":ai_attack_groups",
-        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
    ],
 )

@@ -266,7 +210,6 @@ cc_library(
    hdrs = ["AIUnitScoreCalculator.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
    ],
@@ -277,6 +220,27 @@ cc_library(
    ],
 )

+cc_library(
+    name = "ai_victory_condition_score_calculator",
+    srcs = ["AIVictoryConditionScoreCalculator.cpp"],
+    hdrs = ["AIVictoryConditionScoreCalculator.hpp"],
+    copts = COPTS,
+    visibility = [
+        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
+        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
+    ],
+    deps = [
+        ":ai_attack_groups",
+        ":ai_attack_locations",
+        ":ai_distance_debuf",
+        ":ai_score_utilities",
+        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
+        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
+        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
+        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
+    ],
+)
+
 cc_library(
    name = "ai_water_crossing_calculator",
    srcs = ["AIWaterCrossingCalculator.cpp"],
@@ -284,13 +248,10 @@ cc_library(
    copts = COPTS,
    visibility = [
        "//src/main/cpp/net/eagle0/shardok:__pkg__",
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
    ],
    deps = [
-        ":ai_common_types",
        ":ai_minimum_distance_and_target",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
@@ -312,6 +273,7 @@ cc_library(
        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
+        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
    ],
 )

@@ -321,7 +283,6 @@ cc_library(
    hdrs = ["AITimeBudget.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
@@ -340,30 +301,20 @@ cc_library(
    hdrs = ["IterativeDeepeningAI.hpp"],
    copts = COPTS,
    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
    ],
    deps = [
        ":ai_attacker_strategy_selector",
-        ":ai_command_evaluator",
        ":ai_defender_strategy_selector",
+        ":ai_score_calculator",
        ":ai_time_budget",
        ":ai_water_crossing_command_chooser",
+        "//src/main/cpp/net/eagle0/common:task_result",
        "//src/main/cpp/net/eagle0/common:time_utils",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
        "//src/main/cpp/net/eagle0/shardok/library:engine",
        "//src/main/cpp/net/eagle0/shardok/library/util:hex_map_utils",
-    ],
-)
-
-cc_library(
-    name = "ai_config",
-    hdrs = ["AIConfig.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__pkg__",
+        "//src/main/protobuf/net/eagle0/shardok/api:command_descriptor_cc_proto",
    ],
 )

@@ -375,21 +326,15 @@ cc_library(
    visibility = ["//visibility:public"],
    deps = [
        ":ai_attacker_strategy_selector",
-        ":ai_config",
        ":ai_defender_strategy_selector",
        ":ai_flee_decision_calculator",
-        ":ai_iterative_deepening",  # Direct dependency for runtime selection
+        ":ai_iterative_deepening",
+        ":ai_score_calculator",
        ":ai_time_budget",
        ":ai_water_crossing_command_chooser",
        "//src/main/cpp/net/eagle0/common:time_utils",
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:shardok_mcts_ai",  # MCTS with abstraction layer
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:mcts_optimized_ai_score_calculator",  # Bounded linear scorer for MCTS
-        "//src/main/cpp/net/eagle0/shardok/ai/score:normalized_ai_score_calculator",  # Normalized [0,1] scorer for ML training
-        "//src/main/cpp/net/eagle0/shardok/ai/score:standard_ai_score_calculator",  # Standard unbounded scorer (default)
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/util:game_state_dumper",
        "@com_google_protobuf//:protobuf",
    ],
 )
@@ -5,14 +5,15 @@
 #include "IterativeDeepeningAI.hpp"

 #include <algorithm>
+#include <cmath>
 #include <limits>
 #include <numeric>
 #include <utility>

 #include "AIAttackerStrategySelector.hpp"
-#include "AICommandEvaluator.hpp"
-#include "TranspositionTable.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
+#include "AIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/common/TaskResult.hpp"
+#include "src/main/cpp/net/eagle0/common/TimeUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"

 namespace shardok {
@@ -24,21 +25,19 @@ IterativeDeepeningAI::IterativeDeepeningAI(
        const bool isDefender,
        AIStrategy strategy,
        const CoordsSet& castleCoords,
-        const AIScoreCalculator& scorer,
        const APDCache& apdCache,
-        BattalionTypeGetter battalionTypeGetter)
+        const ALCache& alCache)
    : playerId(playerId),
      isDefender(isDefender),
      strategy(std::move(strategy)),
      castleCoords(castleCoords),
-      scorer(scorer),
      apdCache(apdCache),
-      battalionTypeGetter(std::move(battalionTypeGetter)) {}  // Move the function object
+      alCache(alCache) {}

 auto IterativeDeepeningAI::IterativeSearch(
        const GameSettingsSPtr& settings,
        const GameStateW& state,
-        const CommandListSPtr& commands,
+        const std::vector<CommandProto>& commands,
        const AITimeBudget& initialBudget) const -> SearchResult {
    // Make a mutable copy of the time budget to track remaining time
    AITimeBudget timeBudget = initialBudget;
@@ -46,38 +45,53 @@ auto IterativeDeepeningAI::IterativeSearch(
    const auto initialBudgetMs = initialBudget.remainingBudget;
    SearchResult result;

-    // Increment TT age for replacement strategy (new search)
-    g_transpositionTable.incrementAge();
+    // Start ThreadPool metrics session
+    AIScoreCalculator::BeginMetricsSession();

-    // DEBUG: Clear TT to see if that's causing the suspicious depth reaching
-    // g_transpositionTable.clear();  // Uncomment to test without cross-search caching
-    if (commands->empty()) {
+    if (commands.empty()) {
 #if DEBUG_ITERATIVE_DEEPENING_TIMINGS
        printf("ID AI: Commands are empty, returning early\n");
 #endif
        result.searchCompleted = true;
+
+        // End session and print metrics (only if session was long enough to be interesting)
+        auto metrics = AIScoreCalculator::EndMetricsSession();
+        if (metrics.session_duration.count() >= 100) {
+            printf("ThreadPool Metrics (empty commands):\n");
+            printf("  Tasks enqueued: %zu\n", metrics.tasks_enqueued);
+            printf("  Tasks succeeded: %zu\n", metrics.tasks_succeeded);
+            printf("  Tasks deadline exceeded: %zu\n", metrics.tasks_deadline_exceeded);
+            printf("  Average thread load: %.1f%%\n", metrics.average_thread_load * 100.0);
+            printf("  Session duration: %lldms\n", metrics.session_duration.count());
+        }
+
        return result;
    }

-    // Check if we're in SET_UP phase and enforce maximum depth limit
+    // Check if we're in SET_UP phase
    bool isSetupPhase =
            (state->status()->state() ==
             net::eagle0::shardok::storage::fb::GameStatus_::State_SET_UP);
-    // Limit depth to prevent thread pool exhaustion and keep search reasonable
-    size_t maxDepth = isSetupPhase ? 2 : 8;
+    size_t maxDepth = isSetupPhase ? 2 : std::numeric_limits<int>::max();

    // Calculate current utility and create engine once for all command evaluations
    const auto& settingsGetter = settings->GetGetter();
    const auto guessedEngine = ShardokEngine(settings, state);
    const auto maxRepeatCount = settingsGetter.Backing().ai_utility_repeat_count();
-    const ScoreValue currentUtility =
-            scorer.GuessedStateScore(isDefender, state, strategy, castleCoords);
+    const ScoreValue currentUtility = AIScoreCalculator::GuessedStateScore(
+            isDefender,
+            state,
+            strategy,
+            castleCoords,
+            settingsGetter,
+            apdCache,
+            alCache);

    // Initialize data structures for tracking scores at each depth
    scoresByDepth.clear();
-    scoresByDepth.resize(commands->size());
+    scoresByDepth.resize(commands.size());
    highestDepthCompleted.clear();
-    highestDepthCompleted.resize(commands->size(), 0);
+    highestDepthCompleted.resize(commands.size(), 0);

    size_t currentDepth = 1;
    size_t previousBestCommand = 0;  // Track best command from previous depth
@@ -86,6 +100,12 @@ auto IterativeDeepeningAI::IterativeSearch(

    // Main iterative deepening loop
    while ((currentDepth == 1 || !IsTimeExpired(timeBudget)) && currentDepth <= maxDepth) {
+        // Track depth timing
+        auto depthStartTime = std::chrono::steady_clock::now();
+        auto elapsedSinceStart =
+                std::chrono::duration_cast<std::chrono::milliseconds>(depthStartTime - startTime);
+        printf("ID AI: Starting depth %zu at %lldms\n", currentDepth, elapsedSinceStart.count());
+
        // Get command indices sorted by best score from previous depth
        std::vector<size_t> sortedIndices = GetCommandsSortedByPreviousDepth(
                currentDepth,
@@ -108,34 +128,50 @@ auto IterativeDeepeningAI::IterativeSearch(

            auto future = SearchCommandAtDepthWithEngine(
                    guessedEngine,
-                    scorer,
+                    settingsGetter,
                    maxRepeatCount,
                    commands,
                    cmdIndex,
-                    currentDepth,  // Pass current iteration depth as desired search depth
+                    currentDepth,
                    currentUtility,
                    timeBudget);

            futures.emplace_back(cmdIndex, std::move(future));
        }

+        auto afterTaskSubmission = std::chrono::steady_clock::now();
+        auto submissionTime = std::chrono::duration_cast<std::chrono::milliseconds>(
+                afterTaskSubmission - depthStartTime);
+        printf("ID AI: Submitted %zu tasks for depth %zu (took %lldms)\n",
+               futures.size(),
+               currentDepth,
+               submissionTime.count());
+
        // Now wait for all futures and collect results
+        printf("ID AI: Waiting for %zu futures at depth %zu\n", futures.size(), currentDepth);
+        auto waitStartTime = std::chrono::steady_clock::now();
+
        for (auto& [cmdIndex, future] : futures) {
            auto cmdResult = future.get();

-            // Ensure scoresByDepth[cmdIndex] has enough space
-            if (scoresByDepth[cmdIndex].size() <= currentDepth) {
-                scoresByDepth[cmdIndex].resize(currentDepth + 1);
-            }
-            scoresByDepth[cmdIndex][currentDepth] = cmdResult.bestScore;
-            highestDepthCompleted[cmdIndex] = currentDepth;
-            evaluatedCount++;
+            // Only record results for successfully completed evaluations
+            if (cmdResult.searchCompleted) {
+                // Ensure scoresByDepth[cmdIndex] has enough space
+                if (scoresByDepth[cmdIndex].size() <= currentDepth) {
+                    scoresByDepth[cmdIndex].resize(currentDepth + 1);
+                }
+                scoresByDepth[cmdIndex][currentDepth] = cmdResult.bestScore;
+                highestDepthCompleted[cmdIndex] = currentDepth;
+                evaluatedCount++;

-            // Check if this command is not END_TURN_COMMAND
-            if ((*commands)[cmdIndex]->GetCommandType() !=
-                net::eagle0::shardok::common::END_TURN_COMMAND) {
-                allEndTurnCommands = false;
+                // Check if this command is not END_TURN_COMMAND
+                if (commands[cmdIndex].type() != net::eagle0::shardok::common::END_TURN_COMMAND) {
+                    allEndTurnCommands = false;
+                }
            }
+            // If searchCompleted is false, we don't increment evaluatedCount or update
+            // highestDepthCompleted This means the iterative deepening logic will correctly handle
+            // incomplete evaluations
        }

        // Find the best command at current depth and check if it changed
@@ -144,7 +180,7 @@ auto IterativeDeepeningAI::IterativeSearch(
            size_t currentBestCommand = 0;
            ScoreValue currentBestScore = -std::numeric_limits<ScoreValue>::infinity();

-            for (size_t i = 0; i < commands->size(); ++i) {
+            for (size_t i = 0; i < commands.size(); ++i) {
                if (highestDepthCompleted[i] >= currentDepth) {
                    if (scoresByDepth[i][currentDepth] > currentBestScore) {
                        currentBestScore = scoresByDepth[i][currentDepth];
@@ -157,26 +193,40 @@ auto IterativeDeepeningAI::IterativeSearch(
            if (currentDepth > 1 && currentBestCommand != previousBestCommand) {
 #if DEBUG_ITERATIVE_DEEPENING_TIMINGS
                printf("ID AI: Best command changed at depth %lu:\n", currentDepth);
-                printf("  Depth %lu best: command %zu (score %.2f) - type: %s\n",
+                printf("  Depth %lu best: command %zu (score %.2f) - %s\n",
                       currentDepth - 1,
                       previousBestCommand,
                       scoresByDepth[previousBestCommand][currentDepth - 1],
-                       net::eagle0::shardok::common::CommandType_Name(
-                               (*commands)[previousBestCommand]->GetCommandType())
-                               .c_str());
-                printf("  Depth %lu best: command %zu (score %.2f) - type: %s\n",
+                       commands[previousBestCommand].DebugString().c_str());
+                printf("  Depth %lu best: command %zu (score %.2f) - %s\n",
                       currentDepth,
                       currentBestCommand,
                       currentBestScore,
-                       net::eagle0::shardok::common::CommandType_Name(
-                               (*commands)[currentBestCommand]->GetCommandType())
-                               .c_str());
+                       commands[currentBestCommand].DebugString().c_str());
 #endif
            }

            previousBestCommand = currentBestCommand;
        }

+        // Log depth completion timing
+        auto depthEndTime = std::chrono::steady_clock::now();
+        auto depthDuration = std::chrono::duration_cast<std::chrono::milliseconds>(
+                depthEndTime - depthStartTime);
+        auto waitDuration =
+                std::chrono::duration_cast<std::chrono::milliseconds>(depthEndTime - waitStartTime);
+        auto totalElapsed =
+                std::chrono::duration_cast<std::chrono::milliseconds>(depthEndTime - startTime);
+
+        printf("ID AI: Completed depth %zu at %lldms (depth took %lldms, wait took %lldms, "
+               "evaluated %zu/%zu)\n",
+               currentDepth,
+               totalElapsed.count(),
+               depthDuration.count(),
+               waitDuration.count(),
+               evaluatedCount,
+               sortedIndices.size());
+
        // Only proceed to next depth if we completed all commands at current depth
        if (!allEvaluated) {
            completionReason = EvaluationCompletionReason::RAN_OUT_OF_TIME;
@@ -220,8 +270,9 @@ auto IterativeDeepeningAI::IterativeSearch(
        }

        // Check if we've used more than 50% of total budget
-        auto totalElapsed = std::chrono::steady_clock::now() - startTime;
-        auto totalElapsedMs = std::chrono::duration_cast<std::chrono::milliseconds>(totalElapsed);
+        auto totalElapsedCheck = std::chrono::steady_clock::now() - startTime;
+        auto totalElapsedMs =
+                std::chrono::duration_cast<std::chrono::milliseconds>(totalElapsedCheck);
        double budgetUsedPercent = static_cast<double>(totalElapsedMs.count()) /
                                   static_cast<double>(initialBudgetMs.count());

@@ -249,7 +300,7 @@ auto IterativeDeepeningAI::IterativeSearch(
    result.searchCompleted = result.minimumDepthCompleted;
    result.timeUsed = std::chrono::duration_cast<std::chrono::milliseconds>(
            std::chrono::steady_clock::now() - startTime);
-    result.availableCommandCount = commands->size();
+    result.availableCommandCount = commands.size();
    result.commandCountEvaluated = evaluatedCountAtHighestDepth;
    result.completionReason = completionReason;

@@ -261,8 +312,28 @@ auto IterativeDeepeningAI::IterativeSearch(
               result.availableCommandCount);
    }

-    // Print TranspositionTable statistics
-    g_transpositionTable.printStats();
+    // End session and print ThreadPool metrics (only for sessions >= 100ms)
+    auto metrics = AIScoreCalculator::EndMetricsSession();
+    if (metrics.session_duration.count() >= 100) {
+        printf("ThreadPool Metrics (depth %zu, %s):\n",
+               result.depthAchieved,
+               completionReason == EvaluationCompletionReason::RAN_OUT_OF_TIME       ? "timeout"
+               : completionReason == EvaluationCompletionReason::RAN_OUT_OF_COMMANDS ? "complete"
+               : completionReason == EvaluationCompletionReason::NOT_ENOUGH_TIME_TO_CONTINUE
+                       ? "no_time"
+                       : "unknown");
+        printf("  Tasks enqueued: %zu\n", metrics.tasks_enqueued);
+        printf("  Tasks succeeded: %zu\n", metrics.tasks_succeeded);
+        printf("  Tasks deadline exceeded: %zu\n", metrics.tasks_deadline_exceeded);
+        printf("  Tasks cancelled: %zu\n", metrics.tasks_cancelled);
+        printf("  Average thread load: %.1f%%\n", metrics.average_thread_load * 100.0);
+        printf("  Session duration: %lldms\n", metrics.session_duration.count());
+        printf("  Tasks per ms: %.2f\n",
+               metrics.session_duration.count() > 0 ? static_cast<double>(metrics.tasks_enqueued) /
+                                                              metrics.session_duration.count()
+                                                    : 0.0);
+    }
+
    return result;
 }

@@ -272,69 +343,81 @@ bool IterativeDeepeningAI::IsTimeExpired(const AITimeBudget& budget) {

 auto IterativeDeepeningAI::SearchCommandAtDepthWithEngine(
        const ShardokEngine& guessedEngine,
-        const AIScoreCalculator& scorer,
+        const GameSettings::Getter& settingsGetter,
        const int maxRepeatCount,
-        const CommandListSPtr& commands,
+        const std::vector<CommandProto>& commands,
        const size_t commandIndex,
-        const int desiredDepth,
+        const int depth,
        const ScoreValue currentUtility,
        AITimeBudget& timeBudget) const -> std::future<SearchResult> {
    SearchResult result;
    result.bestCommandIndex = commandIndex;
-    result.depthAchieved = desiredDepth;
+    result.depthAchieved = depth;
    result.searchCompleted = true;
    result.minimumDepthCompleted = true;
-    result.availableCommandCount = commands->size();
+    result.availableCommandCount = commands.size();
    result.commandCountEvaluated = 1;  // We're evaluating just this command

-    if (commandIndex >= commands->size()) {
+    if (commandIndex >= commands.size()) {
        result.bestScore = 0.0;
        std::promise<SearchResult> p;
        p.set_value(result);
        return p.get_future();
    }

-    // Track concurrent evaluations and adjust time accounting
-    AIEvaluationCounter counter;
-    const auto startTime = std::chrono::steady_clock::now();
+    try {
+        // Track concurrent evaluations and adjust time accounting
+        AIEvaluationCounter counter;
+        const auto startTime = std::chrono::steady_clock::now();

-    // Calculate deadline from remaining time budget
-    const auto deadline = startTime + timeBudget.remainingBudget;
+        // Calculate deadline from remaining time budget
+        const auto deadline = startTime + timeBudget.remainingBudget;

-    // Create command evaluator for lookahead search
-    AICommandEvaluator evaluator(scorer, apdCache, battalionTypeGetter);
+        // Get the future from CommandScore - don't wait yet
+        auto commandScoreFuture = AIScoreCalculator::CommandScore(
+                playerId,
+                isDefender,
+                depth,
+                maxRepeatCount,
+                guessedEngine,
+                strategy,
+                currentUtility,
+                settingsGetter,
+                castleCoords,
+                apdCache,
+                alCache,
+                commandIndex,
+                deadline);

-    // Get the future from EvaluateCommand - don't wait yet
-    // Note: EvaluateCommand expects remainingLookahead, not desiredDepth
-    // desiredDepth 1 = evaluate immediate (remainingLookahead 0)
-    // desiredDepth 2 = look 1 move ahead (remainingLookahead 1)
-    // desiredDepth N = look N-1 moves ahead (remainingLookahead N-1)
-    auto commandScoreFuture = evaluator.EvaluateCommand(
-            playerId,
-            isDefender,
-            desiredDepth - 1,  // Convert desiredDepth to remainingLookahead
-            maxRepeatCount,
-            guessedEngine,
-            strategy,
-            currentUtility,
-            castleCoords,
-            commandIndex,
-            deadline);
+        // Calculate time and adjust budget before waiting
+        // This is needed because we need to update timeBudget synchronously
+        const auto commandResult = commandScoreFuture.get();

-    // Calculate time and adjust budget before waiting
-    // This is needed because we need to update timeBudget synchronously
-    const auto commandScore = commandScoreFuture.get();
+        const auto elapsed = std::chrono::steady_clock::now() - startTime;
+        const int concurrentCount = AIEvaluationCounter::GetCurrentCount();
+        const auto adjustedElapsed = elapsed / std::max(1, concurrentCount);
+        const auto adjustedElapsedMs =
+                std::chrono::duration_cast<std::chrono::milliseconds>(adjustedElapsed);

-    const auto elapsed = std::chrono::steady_clock::now() - startTime;
-    const int concurrentCount = AIEvaluationCounter::GetCurrentCount();
-    const auto adjustedElapsed = elapsed / std::max(1, concurrentCount);
-    const auto adjustedElapsedMs =
-            std::chrono::duration_cast<std::chrono::milliseconds>(adjustedElapsed);
+        // Deduct adjusted time from remaining budget
+        timeBudget.remainingBudget -= adjustedElapsedMs;

-    // Deduct adjusted time from remaining budget
-    timeBudget.remainingBudget -= adjustedElapsedMs;
-
-    result.bestScore = commandScore;
+        // Check if we got a valid result or if evaluation failed/timed out
+        if (!commandResult.succeeded()) {
+            // Command evaluation failed or timed out - mark as incomplete
+            result.bestScore = 0.0;
+            result.searchCompleted = false;
+            result.minimumDepthCompleted = false;
+        } else {
+            result.bestScore = commandResult.value;
+        }
+    } catch (const std::exception& e) {
+        // If evaluation fails, return a neutral score rather than crashing
+#if DEBUG_ITERATIVE_DEEPENING_TIMINGS
+        printf("SearchCommandAtDepthWithEngine: evaluation failed with exception: %s\n", e.what());
+#endif
+        result.bestScore = 0.0;
+    }

    std::promise<SearchResult> p;
    p.set_value(result);
@@ -356,19 +439,9 @@ auto IterativeDeepeningAI::GetCommandsSortedByPreviousDepth(
    // Sort by score at previous depth
    const size_t prevDepth = currentDepth - 1;
    std::ranges::sort(indices, [&](const size_t a, const size_t b) {
-        // Bounds check - if indices are out of range, or inner vectors are too small, treat as not
-        // evaluated
-        if (a >= scoresByDepth.size() || b >= scoresByDepth.size() ||
-            a >= highestDepthCompleted.size() || b >= highestDepthCompleted.size()) {
-            return a < b;  // Maintain stable order for out-of-bounds indices
-        }
-
-        // Check if the scores for previous depth exist
+        // Only consider commands that were evaluated at previous depth
        if (highestDepthCompleted[a] >= prevDepth && highestDepthCompleted[b] >= prevDepth) {
-            // Additional safety check for inner vector size
-            if (scoresByDepth[a].size() > prevDepth && scoresByDepth[b].size() > prevDepth) {
-                return scoresByDepth[a][prevDepth] > scoresByDepth[b][prevDepth];
-            }
+            return scoresByDepth[a][prevDepth] > scoresByDepth[b][prevDepth];
        }
        // Commands not evaluated at prev depth go to the end
        return highestDepthCompleted[a] >= prevDepth;
@@ -12,18 +12,17 @@
 #include "AIStrategy.hpp"
 #include "AITimeBudget.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
+#include "src/main/protobuf/net/eagle0/shardok/api/command_descriptor.pb.h"

 namespace shardok {

 // Forward declarations
 class ShardokEngine;
 using ScoreValue = double;
-using BattalionTypeGetter = std::function<BattalionTypeSPtr(BattalionTypeId)>;
+using CommandProto = net::eagle0::shardok::api::CommandDescriptor;

 /// Reason why AI evaluation completed at the achieved depth.
 enum class EvaluationCompletionReason {
@@ -62,14 +61,13 @@ public:
            bool isDefender,
            AIStrategy strategy,
            const CoordsSet& castleCoords,
-            const AIScoreCalculator& scorer,
            const APDCache& apdCache,
-            BattalionTypeGetter battalionTypeGetter);  // Pass by value
+            const ALCache& alCache);

    [[nodiscard]] SearchResult IterativeSearch(
            const GameSettingsSPtr& settings,
            const GameStateW& state,
-            const CommandListSPtr& commands,
+            const std::vector<CommandProto>& commands,
            const AITimeBudget& initialBudget) const;

 private:
@@ -77,9 +75,8 @@ private:
    bool isDefender;
    AIStrategy strategy;
    CoordsSet castleCoords;
-    const AIScoreCalculator& scorer;
    const APDCache& apdCache;
-    BattalionTypeGetter battalionTypeGetter;  // Store by value, not reference!
+    const ALCache& alCache;

    // Reusable vectors to reduce memory allocations
    mutable std::vector<std::vector<ScoreValue>> scoresByDepth;
@@ -90,11 +87,11 @@ private:

    [[nodiscard]] std::future<SearchResult> SearchCommandAtDepthWithEngine(
            const ShardokEngine& guessedEngine,
-            const AIScoreCalculator& scorer,
+            const GameSettings::Getter& settingsGetter,
            int maxRepeatCount,
-            const CommandListSPtr& commands,
+            const std::vector<CommandProto>& commands,
            size_t commandIndex,
-            int desiredDepth,
+            int depth,
            ScoreValue currentUtility,
            AITimeBudget& timeBudget) const;

@@ -10,27 +10,15 @@

 #define DEBUG_FLEE_DECISIONS

-// Enable to dump game state and debug tree to /tmp for debugging
-// #define ENABLE_MCTS_DEBUG_DUMP
-
-#ifdef ENABLE_MCTS_DEBUG_DUMP
-#include <chrono>
-#include <fstream>
-#include <iomanip>
-#include <sstream>
-#endif
+#include <google/protobuf/util/message_differencer.h>

 #include "AIAttackerStrategySelector.hpp"
-#include "AIConfig.hpp"
 #include "AIDefenderStrategySelector.hpp"
 #include "AIFleeDecisionCalculator.hpp"
 #include "AIScoreUtilities.hpp"
 #include "AITimeBudget.hpp"
 #include "IterativeDeepeningAI.hpp"
-#include "mcts/ShardokMCTSAI.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/MCTSOptimizedAIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/NormalizedAIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/StandardAIScoreCalculator.hpp"
+#include "src/main/cpp/net/eagle0/common/TimeUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
 #include "src/main/cpp/net/eagle0/shardok/library/view_filters/GameStateGuesser.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/api/action_result_view.pb.h"
@@ -54,17 +42,11 @@ ShardokAIClient::ShardokAIClient(
        const PlayerId playerId,
        const bool isDefender,
        const HexMap *hexMap,
-        const SettingsGetter &settings,
-        const AIAlgorithmType aiAlgorithmType,
-        const ScoringCalculatorType scoringCalculatorType,
-        const mcts::MCTSConfig &mctsConfig)
+        const SettingsGetter &settings)
    : playerId(playerId),
      isDefender(isDefender),
-      aiAlgorithmType(aiAlgorithmType),
-      scoringCalculatorType(scoringCalculatorType),
      alCache(std::make_unique<AttackLocationsCache>(hexMap, settings)),
-      waterCrossingCommandChooser(playerId, apdCache),
-      mctsConfig(mctsConfig) {
+      waterCrossingCommandChooser(playerId, apdCache) {
    // Pre-generate the most common cache entries for better performance
    const auto mapId = ActionPointDistancesCache::GetMapId(hexMap);

@@ -88,110 +70,38 @@ ShardokAIClient::ShardokAIClient(
    apdCache->ConsolidateThreadLocalCache_Racy();
 }

-void CheckCommand(const CommandSPtr &realCommand, const CommandSPtr &guessedCommand) {
-    // Verify that the AI's guessed state produces the same available commands as the real state.
-    // We only compare fields that uniquely identify a command - metadata fields like action_points,
-    // will_unhide, next_round_target_info are not part of command identity.
+void CheckCommand(const CommandProto &realDescriptor, const CommandProto &guessedDescriptor) {
+    string diff;
+    auto differencer = google::protobuf::util::MessageDifferencer();
+    differencer.IgnoreField(CommandProto::descriptor()->FindFieldByNumber(
+            CommandProto::kFollowUpCommandTypesFieldNumber));
+    differencer.ReportDifferencesToString(&diff);
+    if (!differencer.Compare(realDescriptor, guessedDescriptor)) {
+        printf("diff: %s\n\n", diff.c_str());

-    if (realCommand->GetCommandType() != guessedCommand->GetCommandType()) {
-        throw ShardokInternalErrorException("Command type mismatch between real and guessed state");
-    }
-
-    if (realCommand->GetPlayerId() != guessedCommand->GetPlayerId()) {
-        throw ShardokInternalErrorException("Player ID mismatch between real and guessed state");
-    }
-
-    if (realCommand->GetActorUnitId() != guessedCommand->GetActorUnitId()) {
-        throw ShardokInternalErrorException("Actor unit mismatch between real and guessed state");
-    }
-
-    if (realCommand->GetTargetRow() != guessedCommand->GetTargetRow() ||
-        realCommand->GetTargetColumn() != guessedCommand->GetTargetColumn()) {
-        throw ShardokInternalErrorException(
-                "Target coordinates mismatch between real and guessed state");
-    }
-
-    // For commands with odds (like FLEE), verify the odds match
-    if (realCommand->HasOdds() != guessedCommand->HasOdds()) {
-        throw ShardokInternalErrorException(
-                "Odds presence mismatch between real and guessed state");
-    }
-
-    if (realCommand->HasOdds() && guessedCommand->HasOdds()) {
-        if (realCommand->GetOddsPercentile() != guessedCommand->GetOddsPercentile()) {
-            throw ShardokInternalErrorException(
-                    "Odds percentile mismatch between real and guessed state");
-        }
+        printf("Selected command descriptor\n%s\ndoes not match guessed\n%s\n\n",
+               realDescriptor.DebugString().c_str(),
+               guessedDescriptor.DebugString().c_str());
+        throw ShardokInternalErrorException("Illegal state for AI client");
    }
 }

 auto ShardokAIClient::StandardChooseCommandIndex(
        const GameSettingsSPtr &settings,
        const GameStateW &guessedState,
-        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
+        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
    const auto settingsGetter = settings->GetGetter();
    const auto guessedEngine = ShardokEngine(settings, guessedState);
-    const auto guessedCommands = guessedEngine.GetAvailableCommandsForAIPlayer(playerId);
-    const auto commandCount = guessedCommands->size();

-    // Calculate time budget based on game situation using new dynamic per-command settings
-    const auto timeBudget = CalculateTimeBudget(playerId, settings, guessedState, commandCount);
+    // Calculate time budget based on game situation using new settings
+    const auto timeBudget = CalculateTimeBudget(playerId, settings, guessedState);

-    // Configure MCTS based on proximity to enemy
-    // When far from enemy: use AVERAGING with maxPlayerFlips=0 (single-player lookahead)
-    //   - AVERAGING naturally penalizes longer paths through variance
-    //   - No opponent nodes, so no one-bad-child problem
-    // When close to enemy: use MINIMAX with maxPlayerFlips=1 (adversarial lookahead)
-    //   - MINIMAX correctly models opponent choosing best response
-    //   - Explores through one opponent turn for tactical accuracy
-    auto adjustedMCTSConfig = mctsConfig;
+    const auto guessedCommands = guessedEngine.GetAvailableCommandProtos(playerId, false);
+    const auto commandCount = guessedCommands.size();

-    // For fair evaluation: simulate leaves to opponent's turn start (maxSimulationFlips=1)
-    // This ensures all leaves are scored at the same game phase:
-    // - Leaves at playerFlips=0 (still my turn): simulate through END_TURN to playerFlips=1
-    // - Leaves at playerFlips=1 (opponent's turn): evaluate immediately
-    // Result: consistent comparison of "what happens after I end my turn"
-    // adjustedMCTSConfig.maxSimulatfixionFlips = 1;
-
-    // adjustedMCTSConfig.maxPlayerFlips = 0;
-    // if (timeBudget.isCloseToEnemy) {
-    //     adjustedMCTSConfig.maxPlayerFlips = 1;
-    //     adjustedMCTSConfig.backpropagationPolicy = mcts::MCTSBackpropagationPolicy::MINIMAX;
-    //     if constexpr (kPerformanceLogging) {
-    //         printf("MCTS Config: Close to enemy - using maxPlayerFlips=1, MINIMAX backprop\n");
-    //     }
-    // } else {
-    //     adjustedMCTSConfig.maxPlayerFlips = 0;
-    //     adjustedMCTSConfig.backpropagationPolicy = mcts::MCTSBackpropagationPolicy::AVERAGING;
-    //     if constexpr (kPerformanceLogging) {
-    //         printf("MCTS Config: Far from enemy - using maxPlayerFlips=0, AVERAGING backprop\n");
-    //     }
-    // }
-
-    assert(commandCount == realAvailableCommands->size());
-    // Verify that the AI's guessed state produces the same available commands as reality
+    assert(commandCount == realAvailableCommands.size());
    for (size_t i = 0; i < commandCount; i++) {
-        CheckCommand((*realAvailableCommands)[i], (*guessedCommands)[i]);
-    }
-
-    // Extract values directly from settings for strategy selection
-    const auto maxRounds = settingsGetter.Backing().max_rounds();
-    const auto braveWaterCost = settingsGetter.Backing().brave_water_action_point_cost();
-    const auto battalionTypeGetter = [&settingsGetter](BattalionTypeId typeId) {
-        return settingsGetter.GetBattalionType(typeId);
-    };
-
-    // Create scorer for actual scoring during search - type selected at construction
-    std::unique_ptr<AIScoreCalculator> scorer;
-    switch (scoringCalculatorType) {
-        case ScoringCalculatorType::NORMALIZED:
-            scorer = MakeNormalizedAIScoreCalculator(settingsGetter, apdCache, alCache);
-            break;
-        case ScoringCalculatorType::MCTS_OPTIMIZED:
-            scorer = MakeMCTSOptimizedAIScoreCalculator(settingsGetter, apdCache, alCache);
-            break;
-        case ScoringCalculatorType::STANDARD:
-        default: scorer = MakeStandardAIScoreCalculator(settingsGetter, apdCache, alCache); break;
+        CheckCommand(realAvailableCommands[i], guessedCommands[i]);
    }

    // Determine strategy once for consistent scoring throughout iterative deepening
@@ -199,80 +109,23 @@ auto ShardokAIClient::StandardChooseCommandIndex(
    const AIStrategy strategy = isDefender ? AIDefenderStrategySelector::BestDefenderStrategy(
                                                     guessedState,
                                                     castleCoords,
-                                                     maxRounds,
                                                     apdCache,
-                                                     battalionTypeGetter)
+                                                     settingsGetter)
                                           : AIAttackerStrategySelector::BestAttackerStrategy(
                                                     playerId,
                                                     guessedState,
                                                     castleCoords,
-                                                     maxRounds,
                                                     apdCache,
                                                     alCache,
-                                                     battalionTypeGetter,
-                                                     braveWaterCost,
+                                                     settingsGetter,
                                                     waterCrossingCommandChooser,
                                                     realAvailableCommands);

-    // AI implementation chosen at runtime via constructor parameter
-    IterativeDeepeningAI::SearchResult search_result;
-
-    if (aiAlgorithmType == AIAlgorithmType::MCTS) {
-#ifdef ENABLE_MCTS_DEBUG_DUMP
-        // Set unique debug dump path for each action using timestamp
-        const auto now = std::chrono::system_clock::now();
-        const auto nowTime = std::chrono::system_clock::to_time_t(now);
-        const auto nowMs =
-                std::chrono::duration_cast<std::chrono::milliseconds>(now.time_since_epoch()) %
-                1000;
-
-        std::ostringstream pathStream;
-        pathStream << "/tmp/shardok_debug_"
-                   << std::put_time(std::localtime(&nowTime), "%Y%m%d_%H%M%S") << "_"
-                   << std::setfill('0') << std::setw(3) << nowMs.count() << "_p"
-                   << static_cast<int>(playerId) << ".txt";
-        adjustedMCTSConfig.debugDumpPath = pathStream.str();
-
-        // Also dump the game state to a file for reproduction
-        std::ostringstream statePathStream;
-        statePathStream << "/tmp/shardok_state_"
-                        << std::put_time(std::localtime(&nowTime), "%Y%m%d_%H%M%S") << "_"
-                        << std::setfill('0') << std::setw(3) << nowMs.count() << "_p"
-                        << static_cast<int>(playerId) << ".bin";
-        const std::string statePath = statePathStream.str();
-
-        // Write the flatbuffer game state to file using SaveTo method
-        if (guessedState.SaveTo(statePath)) {
-            printf("Game state dumped to: %s\n", statePath.c_str());
-        } else {
-            printf("Failed to dump game state to: %s\n", statePath.c_str());
-        }
-#endif  // ENABLE_MCTS_DEBUG_DUMP
-
-        // Using Monte Carlo Tree Search AI (with abstraction layer)
-        ShardokMCTSAI ai(
-                playerId,
-                isDefender,
-                strategy,
-                castleCoords,
-                *scorer,
-                apdCache,
-                alCache,
-                adjustedMCTSConfig);
-        search_result = ai.Search(settings, guessedState, timeBudget);
-    } else {
-        // Using Iterative Deepening AI (default)
-        IterativeDeepeningAI ai(
-                playerId,
-                isDefender,
-                strategy,
-                castleCoords,
-                *scorer,
-                apdCache,
-                battalionTypeGetter);
-        search_result =
-                ai.IterativeSearch(settings, guessedState, realAvailableCommands, timeBudget);
-    }
+    // Use iterative deepening AI for Phase 2 implementation
+    IterativeDeepeningAI
+            iterativeAI(playerId, isDefender, strategy, castleCoords, apdCache, alCache);
+    auto search_result =
+            iterativeAI.IterativeSearch(settings, guessedState, realAvailableCommands, timeBudget);

    CommandChoiceResults result{};
    result.chosenIndex = search_result.bestCommandIndex;
@@ -288,12 +141,9 @@ auto ShardokAIClient::StandardChooseCommandIndex(
                   result.commandCountEvaluated,
                   result.availableCommandCount);
        }
-        const auto chosenCommandType =
-                (*realAvailableCommands)[result.chosenIndex]->GetCommandType();
-        printf("ID AI: Search complete - achieved depth %d for best command %zu (%s)\n",
+        printf("ID AI: Search complete - achieved depth %d for best command %zu\n",
               result.depthAchieved,
-               result.chosenIndex,
-               net::eagle0::shardok::common::CommandType_Name(chosenCommandType).c_str());
+               result.chosenIndex);

        fflush(stdout);
    }
@@ -304,20 +154,19 @@ auto ShardokAIClient::StandardChooseCommandIndex(
 auto ShardokAIClient::LateRoundAttackerChooseCommandIndex(
        const GameSettingsSPtr &settings,
        const GameStateW &guessedState,
-        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
+        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
    if (const auto dismissCommand = std::ranges::find_if(
-                *realAvailableCommands,
-                [](const CommandSPtr &cmd) {
-                    return cmd->GetCommandType() ==
-                           net::eagle0::shardok::common::DISMISS_UNIT_COMMAND;
+                realAvailableCommands,
+                [](const net::eagle0::shardok::api::CommandDescriptor &cmd) {
+                    return cmd.type() == net::eagle0::shardok::common::DISMISS_UNIT_COMMAND;
                });
-        dismissCommand == realAvailableCommands->end()) {
+        dismissCommand == realAvailableCommands.end()) {
        return StandardChooseCommandIndex(settings, guessedState, realAvailableCommands);
    } else {
        CommandChoiceResults results{};
        results.chosenIndex =
-                static_cast<size_t>(std::distance(realAvailableCommands->begin(), dismissCommand));
-        results.availableCommandCount = realAvailableCommands->size();
+                static_cast<size_t>(std::distance(realAvailableCommands.begin(), dismissCommand));
+        results.availableCommandCount = realAvailableCommands.size();
        results.depthAchieved = 1;          // Simple heuristic choice
        results.commandCountEvaluated = 1;  // Only evaluated one command type
        results.completionReason =
@@ -329,31 +178,24 @@ auto ShardokAIClient::LateRoundAttackerChooseCommandIndex(
 auto ShardokAIClient::FinalRoundAttackerChooseCommandIndex(
        const GameSettingsSPtr &settings,
        const GameStateW &guessedState,
-        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
-    const auto fleeCommand =
-            std::ranges::find_if(*realAvailableCommands, [](const CommandSPtr &cmd) {
-                return cmd->GetCommandType() == net::eagle0::shardok::common::FLEE_COMMAND;
+        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
+    const auto fleeCommand = std::ranges::find_if(
+            realAvailableCommands,
+            [](const net::eagle0::shardok::api::CommandDescriptor &cmd) {
+                return cmd.type() == net::eagle0::shardok::common::FLEE_COMMAND;
            });

-    if (fleeCommand == realAvailableCommands->end()) {
+    if (fleeCommand == realAvailableCommands.end()) {
        return LateRoundAttackerChooseCommandIndex(settings, guessedState, realAvailableCommands);
    }

-    // Extract values directly from settings for flee decision evaluation
-    const auto settingsGetter = settings->GetGetter();
-    const auto maxRounds = settingsGetter.Backing().max_rounds();
-    const auto minimumFleeOddsThreshold = settingsGetter.Backing().ai_minimum_flee_odds_threshold();
-    const auto desperateFleeThreshold = settingsGetter.Backing().ai_desperate_flee_threshold();
-
    // Use the flee decision calculator
    const auto fleeDecision = AIFleeDecisionCalculator::EvaluateFleeVsFight(
            playerId,
+            settings->GetGetter(),
            guessedState,
            realAvailableCommands,
            fleeCommand,
-            maxRounds,
-            minimumFleeOddsThreshold,
-            desperateFleeThreshold,
 #ifdef DEBUG_FLEE_DECISIONS
            true  // Enable debug logging
 #else
@@ -364,7 +206,7 @@ auto ShardokAIClient::FinalRoundAttackerChooseCommandIndex(
    if (fleeDecision.shouldFlee) {
        CommandChoiceResults results{};
        results.chosenIndex = fleeDecision.commandIndex;
-        results.availableCommandCount = realAvailableCommands->size();
+        results.availableCommandCount = realAvailableCommands.size();
        results.depthAchieved = 1;          // Heuristic choice
        results.commandCountEvaluated = 1;  // Only evaluated one command type
        results.completionReason = EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;
@@ -378,7 +220,7 @@ auto ShardokAIClient::FinalRoundAttackerChooseCommandIndex(
 auto ShardokAIClient::ChooseCommandIndex(
        const GameSettingsSPtr &settings,
        const GameStateView &gsv,
-        const CommandListSPtr &realAvailableCommands) const -> CommandChoiceResults {
+        const vector<CommandProto> &realAvailableCommands) const -> CommandChoiceResults {
    static int typeChosenCount[net::eagle0::shardok::common::CommandType_MAX + 1];
    static int totalChoices = 0;

@@ -397,7 +239,7 @@ auto ShardokAIClient::ChooseCommandIndex(
        results = StandardChooseCommandIndex(settings, guessedState, realAvailableCommands);
    }

-    const auto chosenType = (*realAvailableCommands)[results.chosenIndex]->GetCommandType();
+    const auto chosenType = realAvailableCommands[results.chosenIndex].type();
    typeChosenCount[static_cast<int>(chosenType)]++;
    totalChoices++;

@@ -423,8 +265,8 @@ auto ShardokAIClient::ChooseCommandIndex(

 auto ShardokAIClient::ChooseCommandIndex(const ShardokEngine &engine) const
        -> CommandChoiceResults {
-    if (const auto &availableCommands = engine.GetAvailableCommandsForAIPlayer(playerId);
-        availableCommands->empty()) {
+    if (const auto &availableCommands = engine.GetAvailableCommandProtos(playerId, false);
+        availableCommands.empty()) {
        printf("no commands for player %d\n", playerId);
        throw ShardokInternalErrorException(
                "Asked to choose a command, but there are none available");
@@ -12,13 +12,10 @@
 #include <vector>

 #include "src/main/cpp/net/eagle0/common/RandomGenerator.hpp"
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSTypes.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIConfig.hpp"
+#include "src/main/cpp/net/eagle0/shardok/ai/AIScoreCalculator.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AITimeBudget.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/AIWaterCrossingCommandChooser.hpp"
 #include "src/main/cpp/net/eagle0/shardok/ai/IterativeDeepeningAI.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
 #include "src/main/protobuf/net/eagle0/shardok/api/game_state_view.pb.h"

 namespace shardok {
@@ -41,54 +38,42 @@ class ShardokAIClient {
 private:
    const PlayerId playerId;
    const bool isDefender;
-    const AIAlgorithmType aiAlgorithmType;
-    const ScoringCalculatorType scoringCalculatorType;

    APDCache apdCache = std::make_shared<ActionPointDistancesCache>();
    ALCache alCache;

    const AIWaterCrossingCommandChooser waterCrossingCommandChooser;

-    // MCTS configuration (only used when aiAlgorithmType == MCTS)
-    mcts::MCTSConfig mctsConfig;
-
    [[nodiscard]] auto StandardChooseCommandIndex(
            const GameSettingsSPtr& settings,
            const GameStateW& guessedState,
-            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
+            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;
    [[nodiscard]] auto LateRoundAttackerChooseCommandIndex(
            const GameSettingsSPtr& settings,
            const GameStateW& guessedState,
-            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
+            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;
    [[nodiscard]] auto FinalRoundAttackerChooseCommandIndex(
            const GameSettingsSPtr& settings,
            const GameStateW& guessedState,
-            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
+            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;

    [[nodiscard]] auto ChooseCommandIndex(
            const GameSettingsSPtr& settings,
            const net::eagle0::shardok::api::GameStateView& gsv,
-            const CommandListSPtr& realAvailableCommands) const -> CommandChoiceResults;
+            const vector<CommandProto>& realAvailableCommands) const -> CommandChoiceResults;

 public:
    explicit ShardokAIClient(
            PlayerId playerId,
            bool isDefender,
            const HexMap* hexMap,
-            const SettingsGetter& settings,
-            AIAlgorithmType aiAlgorithmType,
-            ScoringCalculatorType scoringCalculatorType,
-            const mcts::MCTSConfig& mctsConfig);
+            const SettingsGetter& settings);
    ~ShardokAIClient() = default;

    [[nodiscard]] auto GetPlayerId() const -> PlayerId { return playerId; }

    [[nodiscard]] auto ChooseCommandIndex(const ShardokEngine& engine) const
            -> CommandChoiceResults;
-
-    // MCTS configuration methods (only relevant when using MCTS algorithm)
-    [[nodiscard]] auto GetMCTSConfig() const -> const mcts::MCTSConfig& { return mctsConfig; }
-    void SetMCTSConfig(const mcts::MCTSConfig& config) { mctsConfig = config; }
 };
 }  // namespace shardok

@@ -1,113 +0,0 @@
-//
-// TranspositionTable.cpp - Implementation of game state evaluation cache
-//
-
-#include "TranspositionTable.hpp"
-
-#include <cstdio>
-#include <cstring>
-
-namespace shardok {
-
-// Global instance
-TranspositionTable g_transpositionTable;
-
-TranspositionTable::TranspositionTable() : table(TABLE_SIZE) {
-    // Initialize all entries to zero
-    clear();
-}
-
-uint64_t TranspositionTable::hashGameState(const GameStateW& state) const {
-    // The FlatBuffer is contiguous in memory and units are sorted by ID,
-    // so we can just hash the raw bytes for order-independent hashing
-    // Use ComputeFNV1aHash to avoid creating a string copy
-    return state.ComputeFNV1aHash();
-}
-
-std::optional<ScoreValue>
-TranspositionTable::probe(const GameStateW& state, int depth, PlayerId player) {
-    stats.probes++;
-
-    uint64_t hash = hashGameState(state);
-    size_t index = hash & INDEX_MASK;
-
-    const auto& entry = table[index];
-
-    // Check if this entry matches our position using FULL hash
-    uint64_t stored_hash = entry.hash_full.load(std::memory_order_relaxed);
-    uint8_t stored_depth = entry.depth.load(std::memory_order_relaxed);
-    uint8_t stored_player = entry.player_id.load(std::memory_order_relaxed);
-
-    if (stored_hash == hash && stored_depth >= depth && stored_player == player) {
-        stats.hits++;
-        float score = entry.score.load(std::memory_order_relaxed);
-        return static_cast<ScoreValue>(score);
-    }
-
-    // Track collisions (different position mapped to same index)
-    // Note: We use depth==0 to indicate empty entries, not hash==0
-    if (stored_depth != 0 && stored_hash != hash) { stats.collisions++; }
-
-    return std::nullopt;
-}
-
-void TranspositionTable::store(
-        const GameStateW& state,
-        int depth,
-        PlayerId player,
-        ScoreValue score) {
-    stats.stores++;
-
-    uint64_t hash = hashGameState(state);
-    size_t index = hash & INDEX_MASK;
-
-    auto& entry = table[index];
-
-    // Simple replacement strategy: always replace if:
-    // 1. Entry is from an older search (different age)
-    // 2. New search is deeper
-    // 3. Entry is empty (depth == 0)
-
-    uint16_t stored_age = entry.age.load(std::memory_order_relaxed);
-    uint8_t stored_depth = entry.depth.load(std::memory_order_relaxed);
-
-    bool should_replace = (stored_depth == 0) ||          // Empty entry (depth 0 means unused)
-                          (stored_age != current_age) ||  // Old entry
-                          (depth >= stored_depth);        // Deeper or equal search
-
-    if (should_replace) {
-        // Store all fields with relaxed ordering (TT races are benign)
-        entry.hash_full.store(hash, std::memory_order_relaxed);
-        entry.score.store(static_cast<float>(score), std::memory_order_relaxed);
-        entry.depth.store(static_cast<uint8_t>(depth), std::memory_order_relaxed);
-        entry.player_id.store(static_cast<uint8_t>(player), std::memory_order_relaxed);
-        entry.age.store(current_age, std::memory_order_relaxed);
-    }
-}
-
-void TranspositionTable::clear() {
-    // Reset all entries
-    for (auto& entry : table) {
-        entry.hash_full.store(0, std::memory_order_relaxed);
-        entry.score.store(0.0f, std::memory_order_relaxed);
-        entry.depth.store(0, std::memory_order_relaxed);
-        entry.player_id.store(0, std::memory_order_relaxed);
-        entry.age.store(0, std::memory_order_relaxed);
-    }
-
-    stats.reset();
-    current_age = 0;
-}
-
-void TranspositionTable::printStats() const {
-    printf("TranspositionTable Stats:\n");
-    printf("  Probes: %llu\n", stats.probes.load());
-    printf("  Hits: %llu (%.1f%%)\n", stats.hits.load(), stats.hitRate());
-    printf("  Stores: %llu\n", stats.stores.load());
-    printf("  Collisions: %llu\n", stats.collisions.load());
-    printf("  Table size: %zu entries (%.1f MB)\n",
-           TABLE_SIZE,
-           (TABLE_SIZE * sizeof(TTEntry)) / (1024.0 * 1024.0));
-}
-
-}  // namespace shardok
@@ -1,91 +0,0 @@
-//
-// TranspositionTable.hpp - Cache for game state evaluations to avoid redundant calculations
-//
-
-#ifndef EAGLE0_TRANSPOSITIONTABLE_HPP
-#define EAGLE0_TRANSPOSITIONTABLE_HPP
-
-#include <atomic>
-#include <cstdint>
-#include <optional>
-#include <vector>
-
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-
-namespace shardok {
-
-using ScoreValue = double;
-// PlayerId already defined in ShardokCTypes.h
-
-class TranspositionTable {
-public:
-    // Statistics for monitoring effectiveness
-    struct Stats {
-        std::atomic<uint64_t> probes{0};
-        std::atomic<uint64_t> hits{0};
-        std::atomic<uint64_t> stores{0};
-        std::atomic<uint64_t> collisions{0};
-
-        double hitRate() const {
-            uint64_t p = probes.load();
-            return p > 0 ? (100.0 * hits.load() / p) : 0.0;
-        }
-
-        void reset() {
-            probes = 0;
-            hits = 0;
-            stores = 0;
-            collisions = 0;
-        }
-    };
-
-private:
-    // Compact entry structure (actual size is greater than 16 bytes due to atomics and alignment)
-    struct TTEntry {
-        std::atomic<uint64_t> hash_full;  // Full hash for validation
-        std::atomic<float> score;         // Score as float to save space
-        std::atomic<uint8_t> depth;       // Search depth (0-255)
-        std::atomic<uint8_t> player_id;   // Player who is to move
-        std::atomic<uint16_t> age;        // For replacement strategy
-    };
-
-    static constexpr size_t TABLE_SIZE_BITS = 22;                  // 2^22 entries
-    static constexpr size_t TABLE_SIZE = 1ULL << TABLE_SIZE_BITS;  // 4M entries = 64MB
-    static constexpr size_t INDEX_MASK = TABLE_SIZE - 1;
-
-    std::vector<TTEntry> table;
-    Stats stats;
-    std::atomic<uint16_t> current_age{0};
-
-    // Hash function for FlatBuffer game state
-    uint64_t hashGameState(const GameStateW& state) const;
-
-public:
-    TranspositionTable();
-
-    // Probe the table for a cached evaluation
-    std::optional<ScoreValue> probe(const GameStateW& state, int depth, PlayerId player);
-
-    // Store an evaluation in the table
-    void store(const GameStateW& state, int depth, PlayerId player, ScoreValue score);
-
-    // Clear the entire table
-    void clear();
-
-    // Increment age for replacement strategy (call at start of each search)
-    void incrementAge() { current_age++; }
-
-    // Get statistics
-    const Stats& getStats() const { return stats; }
-
-    // Print statistics to stdout
-    void printStats() const;
-};
-
-// Global instance for the AI to use
-extern TranspositionTable g_transpositionTable;
-
-}  // namespace shardok
-
-#endif  // EAGLE0_TRANSPOSITIONTABLE_HPP
@@ -1,24 +0,0 @@
-load("//tools:copts.bzl", "COPTS")
-
-cc_library(
-    name = "shardok_mcts_ai",
-    srcs = ["ShardokMCTSAI.cpp"],
-    hdrs = ["ShardokMCTSAI.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__pkg__",
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/common/mcts/abstract:abstract_mcts_ai",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_iterative_deepening",  # For SearchResult compatibility
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_time_budget",
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts/adapters:shardok_mcts_factory",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-    ],
-)
@@ -1,813 +0,0 @@
-# Chance Nodes in MCTS for Shardok
-
-## Problem Statement
-
-### Current Behavior
-The current MCTS implementation uses a fixed roll (50th percentile) for all probabilistic outcomes during simulation. This creates several issues:
-
-1. **Binary success actions overvalued**: A START_FIRE command with 51% success is treated as always succeeding, making it appear better than it actually is.
-2. **Discontinuity at 50%**: Actions with 49% vs 51% success have dramatically different evaluations, when they should be similar.
-3. **Variable-outcome actions simplified**: Melee/archery attacks with damage ranges are evaluated at a single point rather than their full distribution.
-
-### Example Issue
-```
-START_FIRE with 51% success:
- Current MCTS: Assumes always succeeds (roll = 50)
- Reality: Succeeds 51% of time, fails 49% of time
- Result: AI overvalues this action
-```
-
-### How Iterative Deepening Solves This
-The iterative deepening AI (see `AICommandEvaluator.cpp:352-393`) handles randomness correctly:
-
-```cpp
-// For actions with odds (binary success/fail):
-// 1. Evaluate success outcome with representative roll
-auto [successScore, successLookahead] = EvaluateWithRandomness(
-    ...,
-    std::make_shared<SequenceRandomGenerator>(std::vector{1.0 - successChance / 2.0})
-);
-
-// 2. Evaluate failure outcome with representative roll
-auto [failureScore, failureLookahead] = EvaluateWithRandomness(
-    ...,
-    std::make_shared<SequenceRandomGenerator>(std::vector{(1.0 - successChance) / 2.0})
-);
-
-// 3. Compute weighted average (expected value)
-immediateScore = std::lerp(failureScore, successScore, successChance);
-lookaheadScore = std::lerp(failureLookahead.get(), successLookahead.get(), successChance);
-```
-
-This is essentially an implicit form of chance nodes - evaluating both outcomes and weighting by probability.
-
-## Chance Nodes Concept
-
-### Classic MCTS with Chance Nodes
-
-In games with randomness (e.g., backgammon), MCTS uses two types of nodes:
-
-1. **Decision Nodes**: Player chooses an action
-   - Selection uses UCB formula (exploration/exploitation tradeoff)
-   - One child per legal action
-
-2. **Chance Nodes**: Nature determines outcome
-   - Selection uses expectation (weighted by probability)
-   - One child per possible outcome
-
-```
-Decision Node (Player to move)
-├─ Action A
-│  └─ Chance Node
-│     ├─ Outcome 1 (prob 0.3) → Game State
-│     ├─ Outcome 2 (prob 0.5) → Game State
-│     └─ Outcome 3 (prob 0.2) → Game State
-└─ Action B
-   └─ Deterministic → Game State
-```
-
-### Example: START_FIRE in Shardok
-
-**Current approach:**
-```
-State S
-└─ START_FIRE (roll=50)
-   └─ State S' (fire always starts)
-```
-
-**With chance nodes:**
-```
-State S
-└─ START_FIRE action
-   └─ Chance Node
-      ├─ Success (51%) → State S_success (fire started)
-      └─ Failure (49%) → State S_failure (no fire, vigor spent)
-```
-
-### Value Propagation
-
-**Decision nodes:** Maximize/minimize over children (depending on player)
-**Chance nodes:** Expected value over children (weighted by probability)
-
-```cpp
-// Decision node value (max for current player)
-value = max(child.value for child in children)
-
-// Chance node value (expectation)
-value = sum(prob[i] * child[i].value for i in outcomes)
-```
-
-## Implementation Approaches
-
-### Option 1: Explicit Chance Nodes (Full Implementation)
-
-Modify the MCTS tree structure to explicitly represent chance nodes.
-
-**Pros:**
- Theoretically sound
- Handles arbitrary outcome distributions
- Clear separation of decision vs chance
-
-**Cons:**
- Significant code changes
- Larger tree (more memory)
- More complex tree traversal
-
-**Tree Structure:**
-```cpp
-enum class NodeType { DECISION, CHANCE };
-
-struct MCTSNode {
-    NodeType type;
-
-    // For decision nodes
-    MCTSPlayerId player;
-    std::vector<std::unique_ptr<MCTSAction>> actions;
-    std::vector<std::unique_ptr<MCTSNode>> children;  // One per action
-
-    // For chance nodes
-    std::vector<double> probabilities;  // One per outcome
-    std::vector<std::unique_ptr<MCTSNode>> outcomes;  // One per outcome
-
-    double visits;
-    double totalReward;
-};
-```
-
-**Selection Phase:**
-```cpp
-MCTSNode* select(MCTSNode* node) {
-    while (!node->isLeaf()) {
-        if (node->type == DECISION) {
-            // Use UCB to select action
-            node = selectChildUCB(node);
-        } else {  // CHANCE node
-            // Use probability-weighted selection
-            node = selectOutcomeByProbability(node);
-        }
-    }
-    return node;
-}
-```
-
-**Backpropagation:**
-```cpp
-void backpropagate(MCTSNode* node, double reward) {
-    while (node != nullptr) {
-        node->visits++;
-        if (node->type == DECISION) {
-            node->totalReward += reward;  // Sum for averaging
-        } else {  // CHANCE node
-            node->totalReward += reward;  // Still sum, but averaged differently
-        }
-        node = node->parent;
-    }
-}
-```
-
-### Option 2: Implicit Chance Nodes (Hybrid Approach)
-
-Keep the current tree structure but sample outcomes during expansion/simulation.
-
-**Pros:**
- Smaller code changes
- More memory efficient
- Easier to implement incrementally
-
-**Cons:**
- Less theoretically pure
- May need more visits to converge
- Sampling introduces variance
-
-**Approach:**
-```cpp
-// During expansion
-std::unique_ptr<MCTSGameState> expand(
-    const MCTSGameState& state,
-    const MCTSAction& action
-) {
-    if (action.isDeterministic()) {
-        return applyActionDeterministic(state, action);
-    } else {
-        // Sample an outcome based on probabilities
-        auto outcome = sampleOutcome(action);
-        return applyActionWithOutcome(state, action, outcome);
-    }
-}
-```
-
-**For binary actions (e.g., START_FIRE):**
-```cpp
-// Expand creates one of two children based on sampling
-if (random() < successProbability) {
-    return applySuccess(state, action);
-} else {
-    return applyFailure(state, action);
-}
-
-// Over many visits, visit ratio will approach probability ratio
-// E.g., 51% success action will have ~51% success children, 49% failure children
-```
-
-### Option 3: Determinized Sampling (Simplest)
-
-Pre-sample all random outcomes at the start of each simulation rollout.
-
-**Pros:**
- Minimal code changes
- Easy to understand
- Works with existing tree structure
-
-**Cons:**
- May converge slowly
- Doesn't explicitly represent probability
- Can waste simulations on unlikely outcomes
-
-**Approach:**
-```cpp
-// At start of each simulation
-std::vector<double> rollSequence = generateRollSequence(maxDepth);
-
-// Use sequence during simulation
-auto state = rootState;
-for (int depth = 0; depth < maxDepth; depth++) {
-    auto action = selectAction(state);
-    state = applyAction(state, action, rollSequence[depth]);
-}
-```
-
-## Recommended Approach: Progressive Enhancement
-
-Implement in phases to manage complexity:
-
-### Phase 1: Binary Chance Nodes (Explicit)
-
-Start with actions that have clear success/failure outcomes (e.g., START_FIRE, EXTINGUISH_FIRE, RAISE_DEAD):
-
-1. Identify binary actions (commands with `HasOdds()`)
-2. Add chance node support for these actions only
-3. Modify tree expansion to create chance nodes
-4. Update selection/backpropagation for chance nodes
-
-**Implementation:**
-```cpp
-// In ShardokGameEngine::getLegalActions()
-// Mark which actions require chance nodes
-struct ActionMetadata {
-    std::unique_ptr<MCTSAction> action;
-    bool requiresChanceNode;
-    double successProbability;  // If requiresChanceNode = true
-};
-```
-
-```cpp
-// In tree expansion
-if (action.requiresChanceNode) {
-    // Create chance node with two children
-    auto chanceNode = std::make_unique<MCTSNode>(CHANCE);
-    chanceNode->probabilities = {successProb, 1.0 - successProb};
-
-    // Expand both outcomes
-    chanceNode->outcomes.push_back(applySuccess(state, action));
-    chanceNode->outcomes.push_back(applyFailure(state, action));
-
-    return chanceNode;
-} else {
-    // Normal deterministic expansion
-    return applyAction(state, action);
-}
-```
-
-### Phase 2: Multi-Outcome Actions
-
-Extend to actions with multiple outcomes (e.g., melee damage ranges):
-
-1. Discretize continuous distributions into buckets
-2. For melee/archery, use 3-5 representative damage values (min, low, avg, high, max)
-3. Compute probabilities for each bucket
-4. Create chance nodes with multiple children
-
-**Example: Melee Attack**
-```cpp
-// Instead of sampling full damage distribution,
-// use representative values
-struct DamageBucket {
-    int damageValue;  // Representative damage
-    double probability;  // Probability of this range
-};
-
-// For a melee attack that can deal 10-20 damage
-std::vector<DamageBucket> buckets = {
-    {10, 0.1},  // Min damage (unlucky)
-    {13, 0.2},  // Low damage
-    {15, 0.4},  // Average damage
-    {17, 0.2},  // High damage
-    {20, 0.1}   // Max damage (lucky)
-};
-```
-
-### Phase 3: Optimization
-
-Once chance nodes work correctly:
-
-1. Add transposition table support for chance nodes
-2. Optimize memory layout
-3. Consider progressive widening (start with 2 outcomes, expand to more if visited often)
-4. Profile and tune
-
-## Design Decisions
-
-### How to Represent Outcomes?
-
-**Option A: Explicit state copies**
-```cpp
-struct ChanceNode {
-    std::vector<std::unique_ptr<MCTSGameState>> outcomeStates;
-    std::vector<double> probabilities;
-};
-```
-
-**Option B: Lazy evaluation**
-```cpp
-struct ChanceNode {
-    MCTSGameState baseState;
-    MCTSAction action;
-    std::vector<int> outcomeRolls;  // Roll values for each outcome
-    std::vector<double> probabilities;
-
-    // Compute state on-demand
-    MCTSGameState getOutcome(size_t index) {
-        return applyActionWithRoll(baseState, action, outcomeRolls[index]);
-    }
-};
-```
-
-**Recommendation:** Option B - lazy evaluation. Only materialize states when visited.
-
-### How Many Outcomes per Action?
-
-**Binary actions (START_FIRE, etc.):**
- Exactly 2 outcomes (success/fail)
- Use exact probabilities from `GetOddsPercentile()`
-
-**Damage actions (MELEE, ARCHERY):**
- Start with 3 outcomes (low/med/high)
- Can expand to 5 if needed for accuracy
- Use representative rolls: 10th, 50th, 90th percentile
-
-**Complex actions (METEOR):**
- Consider 2-3 outcomes initially
- Can model as "hits N enemies" for N in {0, 1, 2, 3+}
-
-### How to Handle Transposition Table?
-
-**Challenge:** Same state can be reached via different chance outcomes
-
-**Solution:**
- Hash based on game state only (not the path taken)
- When looking up, return cached evaluation if state matches
- This is already how transposition tables work!
-
-```cpp
-// Current approach works fine:
-auto hash = computeHash(gameState);  // Doesn't include how we got here
-if (auto cached = transpositionTable.lookup(hash)) {
-    return cached->value;
-}
-```
-
-### Selection at Chance Nodes
-
-**During tree traversal:**
-```cpp
-size_t selectOutcome(const ChanceNode& node) {
-    // Option 1: Sample by probability (introduces variance)
-    double r = random();
-    double cumulative = 0.0;
-    for (size_t i = 0; i < node.probabilities.size(); i++) {
-        cumulative += node.probabilities[i];
-        if (r < cumulative) return i;
-    }
-
-    // Option 2: Round-robin weighted by visit count vs probability
-    // (Explore under-visited outcomes more)
-    size_t leastVisited = findMostUnderExploredOutcome(node);
-    return leastVisited;
-}
-```
-
-**Recommendation:** Use Option 2 to ensure all outcomes get explored proportionally.
-
-## Integration Points
-
-### Modified Functions
-
-1. **`ShardokGameEngine::getLegalActions()`**
-   - Add metadata about which actions need chance nodes
-   - Return action + probability information
-
-2. **`ShardokGameEngine::applyAction()`**
-   - For binary actions, return both possible outcomes
-   - Or: take an explicit outcome index parameter
-
-3. **`AbstractMCTSAI::selection()`**
-   - Handle chance nodes differently from decision nodes
-   - Use probability-weighted selection instead of UCB
-
-4. **`AbstractMCTSAI::expand()`**
-   - Create chance node children for probabilistic actions
-   - May create multiple child nodes per action
-
-5. **`AbstractMCTSAI::backpropagate()`**
-   - Update all nodes in path (both decision and chance)
-   - Value calculation already handles this correctly (just averages)
-
-### New Functions Needed
-
-```cpp
-// In ShardokGameEngine
-struct ChanceOutcome {
-    int roll;  // The dice roll that produces this outcome
-    double probability;  // Probability of this outcome
-};
-
-std::vector<ChanceOutcome> getChanceOutcomes(const MCTSAction& action) const;
-```
-
-```cpp
-// In MCTSNode
-bool isChanceNode() const;
-const std::vector<double>& getOutcomeProbabilities() const;
-```
-
-## Testing Strategy
-
-### Unit Tests
-
-1. **Binary action correctness**
-   ```cpp
-   TEST(ChanceNodes, BinaryActionExpectedValue) {
-       // START_FIRE with 60% success
-       // Run MCTS with chance nodes
-       // Verify: visits to success ~= 60%, visits to failure ~= 40%
-       // Verify: expected value matches manual calculation
-   }
-   ```
-
-2. **Comparison with iterative deepening**
-   ```cpp
-   TEST(ChanceNodes, MatchesIterativeDeepening) {
-       // Same position, both AIs
-       // Should choose same action
-       // Scores should be similar (within variance)
-   }
-   ```
-
-3. **Transposition table with chance**
-   ```cpp
-   TEST(ChanceNodes, TranspositionConsistency) {
-       // Two paths to same state via different chance outcomes
-       // Should reuse cached evaluation
-   }
-   ```
-
-### Integration Tests
-
-1. Compare MCTS with/without chance nodes on test positions
-2. Verify that chance nodes reduce overvaluation of marginal actions
-3. Performance test: measure slowdown (expect 1.5-2x for binary actions)
-
-### Real-World Validation
-
-Run the problematic START_FIRE scenario:
- With current MCTS: Should overvalue START_FIRE
- With chance nodes: Should correctly weight success/failure
- Expected: END_TURN should get significantly more visits
-
-## Performance Considerations
-
-### Memory Overhead
-
-**Per chance node:**
- Probability vector: `N * sizeof(double)` (N = number of outcomes)
- Outcome children: `N * sizeof(unique_ptr)`
- For binary: ~32 bytes per chance node
-
-**Estimate:**
- Current tree: ~100K nodes per search
- With chance nodes: ~150K nodes (50% actions are probabilistic)
- Extra memory: ~50K * 32 bytes = ~1.6 MB
- **Acceptable overhead**
-
-### Computational Overhead
-
-**Per simulation:**
- Current: 1 path through tree
- With chance nodes: Still 1 path, but more nodes
- Overhead: ~20-30% (more node visits)
-
-**Mitigation:**
- Transposition table helps (same states via different paths)
- Progressive widening (start with 2 outcomes, expand if visited often)
- Lazy state evaluation (don't materialize until needed)
-
-### Convergence Speed
-
-Chance nodes may require more visits to converge because:
- More children per action (branching factor increases)
- Outcomes need proportional exploration
-
-**Mitigation:**
- Use visit count thresholds before expanding chance nodes
- Consider progressive widening (UCT-ProgressiveWidening)
-
-## Migration Path
-
-### Step 1: Infrastructure (1-2 days)
- Add `NodeType` enum and metadata to MCTSNode
- Implement chance node creation (without using them yet)
- Add unit tests for chance node structure
-
-### Step 2: Binary Actions (2-3 days)
- Identify all binary success/fail actions
- Modify expansion to create chance nodes for these
- Update selection/backpropagation
- Test on START_FIRE scenario
-
-### Step 3: Integration Testing (1 day)
- Run full MCTS tests with chance nodes enabled
- Compare with iterative deepening on test positions
- Validate that it fixes the START_FIRE overvaluation
-
-### Step 4: Multi-Outcome Actions (2-3 days)
- Implement damage bucketing for MELEE/ARCHERY
- Create chance nodes with 3-5 outcomes
- Test on combat scenarios
-
-### Step 5: Optimization (1-2 days)
- Profile performance
- Add progressive widening if needed
- Tune outcome granularity
-
-### Step 6: Documentation & Cleanup (1 day)
- Document the new approach
- Clean up code
- Add comprehensive tests
-
-## Alternative: Simpler Hybrid Approach
-
-If full chance nodes are too complex, consider a hybrid:
-
-1. **Keep current tree structure** (no explicit chance nodes)
-2. **During expansion:** Sample outcome and create one child
-3. **Over many simulations:** Statistics converge to correct probabilities
-4. **Add outcome tracking:** Store "which outcome" in edge/node metadata
-
-**Example:**
-```cpp
-// Expansion samples an outcome
-auto expand(state, action) {
-    if (action.hasBinaryOutcome()) {
-        // Sample once
-        bool success = (random() < successProb);
-        // Store which outcome this edge represents
-        edge.metadata.outcome = success ? OUTCOME_SUCCESS : OUTCOME_FAILURE;
-        return applyWithOutcome(state, action, success);
-    }
-}
-
-// Selection prioritizes under-explored outcomes
-auto selectChild(node) {
-    // Find action where outcome distribution is unbalanced
-    // E.g., 60% success action should have ~60% success children
-    // If we have 80% success children, prefer exploring failure
-}
-```
-
-This is simpler but less theoretically sound. It's a reasonable starting point if full chance nodes prove too complex.
-
-## Comparison: Chance Nodes vs Open-Loop MCTS
-
-### What is Open-Loop MCTS?
-
-**Open-loop MCTS** (also called "determinization MCTS" or "information set MCTS") is an alternative approach to handling randomness:
-
-1. At the **start of each simulation**, sample all random outcomes needed for that simulation
-2. Play out the entire simulation using those fixed random values
-3. Different simulations use different random seeds
-4. The tree structure doesn't explicitly model randomness - it's all in the rollouts
-
-**Example implementation:**
-```cpp
-// At start of simulation
-std::vector<double> rollSequence = sampleRolls(maxDepth);  // Pre-sample all rolls
-
-// During simulation
-MCTSNode* node = root;
-for (int depth = 0; depth < maxDepth; depth++) {
-    Action action = selectAction(node);
-    node = applyAction(node, action, rollSequence[depth]);  // Use pre-sampled roll
-}
-```
-
-### Open-Loop MCTS for Shardok
-
-**How it would work:**
-```cpp
-// Each simulation samples a "possible world"
-void simulate(MCTSNode* root) {
-    // Sample random rolls for this simulation
-    auto rolls = generateRollSequence();  // e.g., {0.45, 0.78, 0.23, ...}
-
-    // Play out simulation using these fixed rolls
-    auto state = root->state;
-    for (int depth = 0; depth < maxDepth; depth++) {
-        auto action = selectAction(state);
-        state = applyAction(state, action, rolls[depth]);
-    }
-
-    double reward = evaluate(state);
-    backpropagate(root, reward);
-}
-```
-
-**Would this fix the START_FIRE issue?**
-
-**Yes** - partially. Different simulations would see different outcomes:
- Some simulations: START_FIRE succeeds (roll < 0.51)
- Some simulations: START_FIRE fails (roll >= 0.51)
- Over many simulations, the action's value would approach the expected value
-
-**However**, it's less efficient than chance nodes because:
- Needs MORE simulations to converge
- Wastes effort exploring unlikely scenarios equally with likely ones
- Doesn't explicitly guide exploration based on probability
-
-### Detailed Comparison
-
-| Aspect | Chance Nodes (Closed-Loop) | Open-Loop MCTS | Current (Fixed Roll) |
-|--------|---------------------------|----------------|----------------------|
-| **Randomness Handling** | Explicit in tree structure | Implicit in simulation sampling | Fixed roll=50 |
-| **Convergence Speed** | Fast - probabilities guide search | Slower - needs more samples | N/A (wrong answer) |
-| **Memory Usage** | Higher (more nodes) | Lower (no extra nodes) | Lowest |
-| **Implementation Complexity** | High (tree structure changes) | Medium (sampling layer) | Low (current) |
-| **Theoretical Soundness** | Highest (models true game tree) | Medium (approximation via sampling) | Low (assumes fixed outcome) |
-| **START_FIRE Fix** | ✅ Yes, accurately | ✅ Yes, eventually | ❌ No |
-| **Efficiency** | Most efficient per simulation | Less efficient (wasted samples) | Efficient but wrong |
-| **Handles Hidden Information** | Poor | Excellent | N/A |
-
-### When to Prefer Each Approach
-
-**Prefer Chance Nodes when:**
- Randomness outcomes are discrete and enumerable (e.g., binary success/fail)
- Probabilities are known precisely
- You want fastest convergence to correct answer
- Game tree is the primary concern (no hidden information)
- **This is Shardok's situation** ✅
-
-**Prefer Open-Loop when:**
- Randomness is continuous and high-dimensional
- Hidden information or imperfect information is present
- Simplicity is paramount
- You can afford many simulations
- Used in games like poker, bridge, Skat
-
-### Why Chance Nodes are Better for Shardok
-
-1. **Discrete outcomes**: Most Shardok randomness is binary (success/fail) or small discrete sets (damage ranges)
-   - START_FIRE: 2 outcomes (success/fail)
-   - MELEE: Can bucket into 3-5 damage ranges
-   - Not continuous - perfect fit for chance nodes
-
-2. **Known probabilities**: We have exact probabilities from `GetOddsPercentile()`
-   - Chance nodes can use exact probabilities
-   - Open-loop just samples blindly
-
-3. **No hidden information**: Shardok is perfect information (all units visible to AI)
-   - Chance nodes' main weakness doesn't apply
-   - Open-loop's main strength doesn't help
-
-4. **Convergence matters**: Limited simulation budget
-   - Need to converge quickly
-   - Chance nodes achieve this better
-
-5. **Existing infrastructure**: We already have deterministic state transitions
-   - Adding chance nodes builds on what we have
-   - Open-loop would need different rollout structure
-
-### Performance Analysis
-
-**Chance Nodes:**
-```
-Time per simulation: 1.3x current
-Simulations needed: 10,000 to converge
-Total time: 13,000x units
-
-Memory: 1.5x current (extra chance nodes)
-```
-
-**Open-Loop:**
-```
-Time per simulation: 1.0x current (same as now)
-Simulations needed: 30,000 to converge (more variance)
-Total time: 30,000x units
-
-Memory: 1.0x current (no extra nodes)
-```
-
-**Result:** Chance nodes are **2.3x faster overall** despite being slower per simulation, because they converge with fewer simulations.
-
-### Hybrid Approach: Best of Both Worlds?
-
-Could we combine them?
-
-**Idea:** Use chance nodes for high-probability branches, open-loop for rare events
-```cpp
-if (probability > 0.1 && outcomeCount <= 5) {
-    // Use explicit chance node
-    createChanceNode(outcomes, probabilities);
-} else {
-    // Use open-loop sampling
-    sampleOutcome();
-}
-```
-
-**Verdict:** Probably not worth the complexity. Shardok's randomness is simple enough that chance nodes handle everything well.
-
-### Recommendation for Shardok
-
-**Use Chance Nodes**, specifically:
-
-1. **Phase 1:** Binary actions (START_FIRE, RAISE_DEAD, etc.)
-   - 2 outcomes, exact probabilities
-   - Biggest bang for buck
-
-2. **Phase 2:** Damage ranges (MELEE, ARCHERY)
-   - 3-5 buckets
-   - Still manageable
-
-3. **If needed:** Could fall back to open-loop for complex actions
-   - E.g., METEOR with many possible outcomes
-   - But likely unnecessary
-
-### Why Not Open-Loop?
-
-While open-loop would eventually fix the START_FIRE issue, it has significant downsides for Shardok:
-
-1. **Slower convergence**: Needs 2-3x more simulations
-2. **Doesn't leverage known probabilities**: We have exact odds, why ignore them?
-3. **Less interpretable**: Harder to debug why AI chose an action
-4. **Doesn't align with iterative deepening**: We want MCTS to match the proven algorithm
-
-The only advantage of open-loop (simplicity) is outweighed by chance nodes' efficiency and correctness.
-
-### Could We Use Current Approach + Better Sampling?
-
-**Idea:** Keep fixed rolls but use different rolls per simulation?
-
-```cpp
-// Instead of always roll=50
-double roll = random();  // Different each simulation
-```
-
-**Problem:** This is essentially open-loop without the tree!
- Even slower to converge
- Tree doesn't learn the outcome probabilities
- Worst of both worlds
-
-**Verdict:** No, this doesn't help. If we're going to sample, do it properly (open-loop). Otherwise, use chance nodes.
-
-### Final Verdict
-
-**For Shardok, chance nodes are clearly superior:**
-
- ✅ Faster convergence (2-3x vs open-loop)
- ✅ Leverages exact probabilities
- ✅ Perfect fit for discrete outcomes
- ✅ Aligns with iterative deepening approach
- ✅ Better debuggability and interpretability
- ❌ More complex implementation (but manageable)
-
-Open-loop would be a fallback if chance nodes prove too difficult, but given the benefits and the bounded complexity (only binary and small discrete outcomes), chance nodes are the right choice.
-
-## Conclusion
-
-Implementing chance nodes will fix the overvaluation of marginal probabilistic actions like START_FIRE with 51% success. The recommended approach is:
-
-1. Start with **explicit chance nodes for binary actions**
-2. Use **lazy state evaluation** to minimize memory
-3. **Progressive enhancement** - binary first, then multi-outcome
-4. Compare with iterative deepening to validate correctness
-
-Expected benefits:
- More accurate action evaluation
- Better handling of probabilistic outcomes
- Closer alignment with theoretical MCTS
- Fixes the START_FIRE issue without tuning heuristics
-
-Expected costs:
- ~20-30% slower per simulation (more nodes)
- ~1-2MB extra memory
- ~1-2 weeks development time
-
-The benefits significantly outweigh the costs for a more theoretically sound and accurate AI.
@@ -1,111 +0,0 @@
-//
-// Shardok-specific MCTS AI implementation using abstract interfaces
-//
-
-#include "ShardokMCTSAI.hpp"
-
-#include "adapters/ShardokGameEngine.hpp"
-#include "adapters/ShardokGameState.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommandFilter.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/util/HexMapUtils.hpp"
-
-namespace shardok {
-
-ShardokMCTSAI::ShardokMCTSAI(
-        PlayerId playerId,
-        bool isDefender,
-        AIStrategy strategy,
-        const CoordsSet& castleCoords,
-        const AIScoreCalculator& scoreCalculator,
-        const APDCache& apdCache,
-        const ALCache& alCache,
-        MCTSConfig config)
-    : abstractAI_(std::make_unique<mcts::AbstractMCTSAI>(
-              static_cast<mcts::MCTSPlayerId>(
-                      playerId),  // Use actual player ID for correct scoring
-              config)),
-      isDefender_(isDefender),
-      strategy_(strategy),
-      castleCoords_(castleCoords),
-      scoreCalculator_(scoreCalculator),
-      apdCache_(apdCache),
-      alCache_(alCache) {}
-
-auto ShardokMCTSAI::Search(
-        const GameSettingsSPtr& settings,
-        const GameStateW& state,
-        const AITimeBudget& budget) const -> SearchResult {
-    // Compute critical tiles once to avoid 8.5% runtime overhead in ShardokEngine construction
-    const auto criticalTiles = GetCriticalTileLocations(state->hex_map());
-
-    // Create Shardok engine for simulation
-    ShardokEngine engine(settings, state, criticalTiles, 0, false);
-
-    // Create game state adapter
-    auto gameState = mcts::ShardokMCTSFactory::createGameState(
-            state,
-            &scoreCalculator_,  // Pass the score calculator
-            settings,           // Pass shared_ptr directly
-            isDefender_,
-            strategy_,
-            castleCoords_,
-            apdCache_,
-            alCache_,
-            criticalTiles);
-
-    // Create game engine adapter (passing critical tiles to avoid recomputation)
-    auto gameEngine = mcts::ShardokMCTSFactory::createGameEngine(
-            engine,
-            &scoreCalculator_,  // Pass the score calculator
-            settings,
-            apdCache_,
-            alCache_,
-            isDefender_,
-            strategy_,
-            castleCoords_,
-            criticalTiles);
-
-    // Perform abstract search
-    const auto timeLimit = budget.remainingBudget;
-    const auto abstractResult = abstractAI_->Search(*gameEngine, *gameState, timeLimit);
-
-    // Report cache statistics for performance analysis
-    if (auto* shardokEngine = dynamic_cast<mcts::ShardokGameEngine*>(gameEngine.get())) {
-        shardokEngine->reportCacheStatistics();
-    }
-
-    // Get unfiltered command count for consistent reporting with IterativeDeepeningAI
-    // (MCTS uses filtered commands internally, but we report unfiltered count for metrics)
-    const auto unfilteredCommands = engine.GetAvailableCommandsForAIPlayer(
-            static_cast<PlayerId>(gameState->currentPlayerId()));
-    const size_t unfilteredCount = unfilteredCommands ? unfilteredCommands->size() : 0;
-
-    // Convert result back to Shardok format
-    SearchResult result;
-    // Map filtered index back to original unfiltered index
-    result.bestCommandIndex =
-            gameEngine->mapFilteredIndexToOriginal(abstractResult.bestActionIndex, *gameState);
-    result.bestScore = abstractResult.bestScore;
-    result.depthAchieved = static_cast<size_t>(abstractResult.searchDepth);
-    result.commandCountEvaluated = static_cast<size_t>(abstractResult.nodesEvaluated);
-    result.timeUsed = abstractResult.searchTime;
-    result.availableCommandCount = unfilteredCount;
-    result.minimumDepthCompleted =
-            (abstractResult.searchDepth >= static_cast<int>(budget.minDepthRequired));
-    result.searchCompleted = true;  // MCTS is anytime - always returns a valid result
-
-    // Determine completion reason based on what actually happened
-    if (abstractResult.foundWinningMove || unfilteredCount == 0) {
-        // Found a terminal winning state or no commands available
-        result.completionReason = EvaluationCompletionReason::RAN_OUT_OF_COMMANDS;
-    } else {
-        // Normal case - time budget exhausted while exploring
-        result.completionReason = EvaluationCompletionReason::RAN_OUT_OF_TIME;
-    }
-
-    return result;
-}
-
-}  // namespace shardok
@@ -1,71 +0,0 @@
-//
-// Shardok-specific MCTS AI that wraps the abstract implementation
-//
-
-#ifndef EAGLE0_SHARDOK_MCTSAI_HPP
-#define EAGLE0_SHARDOK_MCTSAI_HPP
-
-#include <memory>
-#include <vector>
-
-#include "adapters/ShardokMCTSFactory.hpp"
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/AbstractMCTSAI.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AITimeBudget.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/IterativeDeepeningAI.hpp"  // For SearchResult compatibility
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
-#pragma clang diagnostic pop
-
-namespace shardok {
-
-// Forward declarations
-class ShardokEngine;
-class AICommandFilter;
-class AIScoreCalculator;
-
-class ShardokMCTSAI {
-public:
-    using SearchResult = IterativeDeepeningAI::SearchResult;
-    using MCTSConfig = mcts::MCTSConfig;
-
-    ShardokMCTSAI(
-            PlayerId playerId,
-            bool isDefender,
-            AIStrategy strategy,
-            const CoordsSet& castleCoords,
-            const AIScoreCalculator& scoreCalculator,
-            const APDCache& apdCache,
-            const ALCache& alCache,
-            MCTSConfig config = MCTSConfig{});
-
-    // Main search interface - compatible with IterativeDeepeningAI
-    [[nodiscard]] auto Search(
-            const GameSettingsSPtr& settings,
-            const GameStateW& state,
-            const AITimeBudget& budget) const -> SearchResult;
-
-    // Configuration
-    [[nodiscard]] auto GetConfig() const -> const MCTSConfig& { return abstractAI_->GetConfig(); }
-    void SetConfig(const MCTSConfig& newConfig) { abstractAI_->SetConfig(newConfig); }
-
-private:
-    std::unique_ptr<mcts::AbstractMCTSAI> abstractAI_;
-
-    // Shardok-specific context
-    bool isDefender_;
-    AIStrategy strategy_;
-    const CoordsSet& castleCoords_;
-    const AIScoreCalculator& scoreCalculator_;
-    const APDCache& apdCache_;
-    const ALCache& alCache_;
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_MCTSAI_HPP
@@ -1,82 +0,0 @@
-load("//tools:copts.bzl", "COPTS")
-
-cc_library(
-    name = "shardok_action",
-    srcs = ["ShardokAction.cpp"],
-    hdrs = ["ShardokAction.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/common/mcts/abstract:mcts_action",
-        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
-    ],
-)
-
-cc_library(
-    name = "shardok_game_state",
-    srcs = ["ShardokGameState.cpp"],
-    hdrs = ["ShardokGameState.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/common/mcts/abstract:mcts_game_state",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-        "//src/main/protobuf/net/eagle0/shardok/common:command_type_cc_proto",
-    ],
-)
-
-cc_library(
-    name = "shardok_game_engine",
-    srcs = ["ShardokGameEngine.cpp"],
-    hdrs = ["ShardokGameEngine.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-    ],
-    deps = [
-        ":shardok_action",
-        ":shardok_game_state",
-        "//src/main/cpp/net/eagle0/common:sequence_random_generator",
-        "//src/main/cpp/net/eagle0/common/mcts/abstract:mcts_game_engine",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_command_filter",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_heuristic_weighting",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-    ],
-)
-
-cc_library(
-    name = "shardok_mcts_factory",
-    srcs = ["ShardokMCTSFactory.cpp"],
-    hdrs = ["ShardokMCTSFactory.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__pkg__",
-        "//src/main/cpp/net/eagle0/shardok/ai/mcts:__pkg__",
-        "//src/test/cpp/net/eagle0/common/mcts:__subpackages__",
-    ],
-    deps = [
-        ":shardok_action",
-        ":shardok_game_engine",
-        ":shardok_game_state",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_command_filter",
-        "//src/main/cpp/net/eagle0/shardok/ai/score:ai_score_calculator_interface",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-    ],
-)
@@ -1,88 +0,0 @@
-//
-// Shardok-specific action adapter implementation
-//
-
-#include "ShardokAction.hpp"
-
-#include <sstream>
-
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-#pragma clang diagnostic pop
-
-namespace shardok::mcts {
-
-// Constructor: extract and store just the essential fields
-ShardokAction::ShardokAction(
-        size_t index,
-        CommandType type,
-        PlayerId player,
-        int actorId,
-        int targetRow,
-        int targetCol,
-        bool hasOdds)
-    : commandIndex_(index),
-      type_(type),
-      player_(player),
-      actorId_(actorId),
-      targetRow_(targetRow),
-      targetCol_(targetCol),
-      hasOdds_(hasOdds) {}
-
-std::string ShardokAction::getDescription() const {
-    std::stringstream ss;
-
-    // Show player
-    ss << "P" << static_cast<int>(player_) << " ";
-
-    ss << net::eagle0::shardok::common::CommandType_Name(type_);
-
-    if (actorId_ >= 0) { ss << " Unit:" << actorId_; }
-
-    if (targetRow_ >= 0 && targetCol_ >= 0) {
-        ss << " @(" << targetRow_ << "," << targetCol_ << ")";
-    }
-
-    return ss.str();
-}
-
-std::unique_ptr<MCTSAction> ShardokAction::clone() const {
-    return std::make_unique<ShardokAction>(
-            commandIndex_,
-            type_,
-            player_,
-            actorId_,
-            targetRow_,
-            targetCol_,
-            hasOdds_);
-}
-
-bool ShardokAction::equals(const MCTSAction& other) const {
-    const auto* shardokOther = dynamic_cast<const ShardokAction*>(&other);
-    if (!shardokOther) { return false; }
-
-    // Compare by index only - actions from same command list are uniquely identified by index
-    return commandIndex_ == shardokOther->commandIndex_;
-}
-
-bool ShardokAction::requiresChanceNode() const {
-    // Actions with probabilistic outcomes require chance nodes:
-    // 1. Binary success/failure actions (hasOdds_): START_FIRE, FEAR, etc.
-    // 2. END_TURN: random effects (fire spread, weather changes)
-    // 3. Combat actions: roll affects damage dealt (MELEE, ARCHERY, CHARGE, DUEL)
-    if (hasOdds_) { return true; }
-
-    using namespace net::eagle0::shardok::common;
-    switch (type_) {
-        case END_TURN_COMMAND:
-        case MELEE_COMMAND:
-        case ARCHERY_COMMAND:
-        case CHARGE_COMMAND:
-        case CHALLENGE_DUEL_COMMAND:
-        case REDUCE_COMMAND: return true;
-        default: return false;
-    }
-}
-
-}  // namespace shardok::mcts
@@ -1,61 +0,0 @@
-//
-// Shardok-specific action adapter for MCTS
-//
-
-#ifndef EAGLE0_SHARDOK_ACTION_HPP
-#define EAGLE0_SHARDOK_ACTION_HPP
-
-#include <memory>
-#include <string>
-
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSAction.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdeprecated-redundant-constexpr-static-def"
-#include "src/main/protobuf/net/eagle0/shardok/common/command_type.pb.h"
-#pragma clang diagnostic pop
-
-namespace shardok::mcts {
-
-class ShardokAction : public MCTSAction {
-public:
-    using CommandType = net::eagle0::shardok::common::CommandType;
-
-    // Constructor: store just the essential fields (no proto, no pointer)
-    ShardokAction(
-            size_t index,
-            CommandType type,
-            PlayerId player,
-            int actorId,
-            int targetRow,
-            int targetCol,
-            bool hasOdds);
-
-    // MCTSAction interface implementation
-    [[nodiscard]] size_t getIndex() const override { return commandIndex_; }
-    [[nodiscard]] std::string getDescription() const override;
-    [[nodiscard]] std::unique_ptr<MCTSAction> clone() const override;
-    [[nodiscard]] bool equals(const MCTSAction& other) const override;
-    [[nodiscard]] bool requiresChanceNode() const override;
-
-    // Shardok-specific accessors (O(1), no allocations)
-    [[nodiscard]] int getType() const { return static_cast<int>(type_); }
-    [[nodiscard]] PlayerId getPlayer() const { return player_; }
-    [[nodiscard]] int getActorId() const { return actorId_; }
-    [[nodiscard]] std::pair<int, int> getTarget() const { return {targetRow_, targetCol_}; }
-
-private:
-    // Store only essential fields (~25 bytes, all POD, cache-friendly)
-    size_t commandIndex_;
-    CommandType type_;
-    PlayerId player_;
-    int actorId_;    // -1 if no actor
-    int targetRow_;  // -1 if no target
-    int targetCol_;  // -1 if no target
-    bool hasOdds_;   // true if command has probabilistic outcome
-};
-
-}  // namespace shardok::mcts
-
-#endif  // EAGLE0_SHARDOK_ACTION_HPP
@@ -1,628 +0,0 @@
-//
-// Shardok-specific game engine adapter implementation
-//
-
-#include "ShardokGameEngine.hpp"
-
-#include <algorithm>
-#include <chrono>
-#include <numeric>
-
-#include "ShardokAction.hpp"
-#include "ShardokGameState.hpp"
-#include "src/main/cpp/net/eagle0/common/SequenceRandomGenerator.hpp"
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSTypes.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AICommandFilter.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIHeuristicWeighting.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokException.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok::mcts {
-
-// Shared cache for legal actions (uses lock-free parallel hash map for thread safety)
-// Using 8 submaps to reduce contention with 16 MCTS threads
-gtl::parallel_flat_hash_map<
-        uint64_t,
-        ShardokGameEngine::LegalActionsCache,
-        std::hash<uint64_t>,
-        std::equal_to<uint64_t>,
-        std::allocator<std::pair<const uint64_t, ShardokGameEngine::LegalActionsCache>>,
-        8,
-        std::mutex>
-        ShardokGameEngine::legalActionsCache_;
-std::atomic<uint64_t> ShardokGameEngine::cacheHits_{0};
-std::atomic<uint64_t> ShardokGameEngine::cacheMisses_{0};
-std::atomic<uint64_t> ShardokGameEngine::timeInHashComputation_{0};
-std::atomic<uint64_t> ShardokGameEngine::timeInLegalActionsComputation_{0};
-
-ShardokGameEngine::ShardokGameEngine(
-        [[maybe_unused]] const ShardokEngine* engine,
-        const AIScoreCalculator* scoreCalculator,
-        const GameSettingsSPtr& gameSettings,
-        const APDCache* apdCache,
-        const ALCache* alCache,
-        bool isDefender,
-        const AIStrategy& strategy,
-        const CoordsSet& castleCoords,
-        const CoordsSet& criticalTileCoords)
-    : scoreCalculator_(scoreCalculator),
-      gameSettings_(gameSettings),
-      apdCache_(apdCache),
-      alCache_(alCache),
-      isDefender_(isDefender),
-      strategy_(strategy),
-      castleCoords_(castleCoords),
-      criticalTileCoords_(criticalTileCoords) {
-    // Thread-local cache is automatically initialized per thread
-    // Reserve space to reduce rehashing (based on profiling: ~30-50K unique states per search)
-    legalActionsCache_.reserve(100000);
-}
-
-std::unique_ptr<MCTSGameState> ShardokGameEngine::applyAction(
-        const MCTSGameState& state,
-        const MCTSAction& action,
-        double deterministicRoll) const {
-    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
-    const auto* shardokAction = dynamic_cast<const ShardokAction*>(&action);
-
-    if (!shardokState || !shardokAction) { return nullptr; }
-
-    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
-
-    // Use cached engine if available (avoids recomputing GetAvailableCommands for same state)
-    std::shared_ptr<ShardokEngine> engine;
-    if (auto cachedEngine = shardokState->getCachedEngine()) {
-        // Clone the cached engine to preserve command cache
-        engine = std::make_shared<ShardokEngine>(*cachedEngine);
-    } else {
-        // Create fresh engine and populate command cache
-        engine = std::make_shared<ShardokEngine>(
-                gameSettings_,
-                shardokState->getShardokState(),
-                criticalTileCoords_,
-                0,
-                false);
-        // Populate command cache (result intentionally unused, just populating cache)
-        [[maybe_unused]] const auto commands =
-                engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-        // Cache the engine for future use with this state
-        shardokState->setCachedEngine(engine);
-        // Clone it for applying the action (don't mutate the cached engine)
-        engine = std::make_shared<ShardokEngine>(*engine);
-    }
-
-    // Create deterministic random generator if a specific roll is requested
-    // deterministicRoll of -1.0 (default) means use random generator
-    // Any other value (including negative) creates a deterministic generator
-    // For open-ended percentile commands, we compute a sequence of values that will
-    // produce the desired final result through the normal open-ended mechanics
-    std::shared_ptr<::RandomGenerator> randomGen = nullptr;
-    constexpr double kNoRollSentinel = -1.0;
-    if (deterministicRoll != kNoRollSentinel) {
-        std::vector<double> sequence;
-
-        if (deterministicRoll >= 5.0 && deterministicRoll <= 95.0) {
-            // Normal range: single value works directly
-            sequence = {deterministicRoll / 100.0};
-        } else if (deterministicRoll < 5.0) {
-            // Need open-ended LOW result (e.g., -100 for guaranteed success)
-            // OpenEndedPercentile: if initial < 5, returns initial - OpenEndedHighImpl(0, 4)
-            // We want: initial - accumulated = deterministicRoll
-            // Use initial = 2 (clearly < 5), so accumulated = 2 - deterministicRoll
-            constexpr double kInitialLow = 2.0;
-            sequence = {kInitialLow / 100.0};
-            // OpenEndedHighImpl accumulates rolls until one < 95
-            // Split accumulated into rolls: 96 (continues) + remaining (stops)
-            double remaining = kInitialLow - deterministicRoll;
-            while (remaining > 95.0) {
-                sequence.push_back(0.96);  // 96 > 95, continues accumulation
-                remaining -= 96.0;
-            }
-            sequence.push_back(remaining / 100.0);  // Final roll < 95, stops
-        } else {
-            // Need open-ended HIGH result (e.g., 150 for guaranteed failure)
-            // OpenEndedPercentile: if initial > 95, returns OpenEndedHighImpl(initial, 4)
-            // OpenEndedHighImpl accumulates rolls until one < 95
-            constexpr double kInitialHigh = 96.0;
-            sequence = {kInitialHigh / 100.0};
-            double remaining = deterministicRoll - kInitialHigh;
-            while (remaining > 95.0) {
-                sequence.push_back(0.96);
-                remaining -= 96.0;
-            }
-            sequence.push_back(remaining / 100.0);
-        }
-
-        randomGen = std::make_shared<::SequenceRandomGenerator>(sequence);
-    }
-
-    engine->PostCommand(currentPlayer, shardokAction->getIndex(), randomGen);
-
-    // Create and return the new state
-    auto newState = std::make_unique<ShardokGameState>(
-            engine->GetCurrentGameState(),
-            scoreCalculator_,
-            gameSettings_.get(),
-            isDefender_,
-            strategy_,
-            castleCoords_,
-            *apdCache_,
-            *alCache_,
-            criticalTileCoords_);
-
-    // Cache the engine on the new state so score() can use it for END_TURN normalization
-    // The engine's command list may be stale after the action was applied, but that's OK -
-    // we'll refresh it when we call GetAvailableCommandsForAIPlayer() in score()
-    newState->setCachedEngine(engine);
-
-    // Don't pre-compute hash - let it be computed lazily on first use
-    // Many states (especially in simulation) never need their hash computed
-    return newState;
-}
-
-void ShardokGameEngine::applyActionMutable(
-        std::unique_ptr<MCTSGameState>& state,
-        const MCTSAction& action) const {
-    auto* shardokState = dynamic_cast<ShardokGameState*>(state.get());
-    const auto* shardokAction = dynamic_cast<const ShardokAction*>(&action);
-
-    if (!shardokState || !shardokAction) {
-        // Fallback to default implementation
-        state = applyAction(*state, action);
-        return;
-    }
-
-    const auto currentPlayer = static_cast<PlayerId>(state->currentPlayerId());
-
-    // Use cached engine if available
-    std::shared_ptr<ShardokEngine> engine;
-    if (auto cachedEngine = shardokState->getCachedEngine()) {
-        engine = std::make_shared<ShardokEngine>(*cachedEngine);
-    } else {
-        engine = std::make_shared<ShardokEngine>(
-                gameSettings_,
-                shardokState->getShardokState(),
-                criticalTileCoords_,
-                0,
-                false);
-        // Populate command cache (result intentionally unused, just populating cache)
-        [[maybe_unused]] const auto commands =
-                engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-        shardokState->setCachedEngine(engine);
-        engine = std::make_shared<ShardokEngine>(*engine);
-    }
-
-    engine->PostCommand(currentPlayer, shardokAction->getIndex(), nullptr);
-    shardokState->getMutableShardokState() = engine->GetCurrentGameState();
-    // Clear the cached engine and hash since the state has been mutated
-    shardokState->setCachedEngine(nullptr);
-    shardokState->invalidateHashCache();
-}
-
-std::vector<std::unique_ptr<MCTSAction>> ShardokGameEngine::getLegalActions(
-        const MCTSGameState& state,
-        MCTSPlayerId /*rootPlayerId*/,
-        int currentPlayerFlips,
-        int maxPlayerFlips) const {
-    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
-    if (!shardokState) { return {}; }
-
-    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
-
-    // Check if we've exceeded the maximum allowed player flips
-    // currentPlayerFlips is the number of times the player has changed since root
-    // maxPlayerFlips is the maximum number of changes we allow
-    // If maxPlayerFlips is 0, only explore root player's moves (stop when player first changes)
-    // If maxPlayerFlips is 1, explore through opponent's response (stop after opponent's moves)
-    if (currentPlayerFlips > maxPlayerFlips) {
-        return {};  // Stop exploration - we've exceeded the flip limit
-    }
-
-    // Time hash computation
-    const auto hashStart = std::chrono::high_resolution_clock::now();
-    const uint64_t stateHash = shardokState->hash();
-    const auto hashEnd = std::chrono::high_resolution_clock::now();
-    timeInHashComputation_.fetch_add(
-            std::chrono::duration_cast<std::chrono::microseconds>(hashEnd - hashStart).count(),
-            std::memory_order_relaxed);
-
-    // Check transposition table for cached legal actions
-    if (auto it = legalActionsCache_.find(stateHash); it != legalActionsCache_.end()) {
-        cacheHits_.fetch_add(1, std::memory_order_relaxed);
-
-        // Use cached engine
-        shardokState->setCachedEngine(it->second.engine);
-
-        // Get commands from the cached engine (Engine already caches these internally)
-        const CommandListSPtr commands =
-                it->second.engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-
-        if (!commands || commands->empty()) { return {}; }
-
-        // Convert to MCTSActions using stored filtered indices
-        std::vector<std::unique_ptr<MCTSAction>> actions;
-        actions.reserve(it->second.filteredIndices.size());
-
-        for (const size_t origIdx : it->second.filteredIndices) {
-            if (origIdx < commands->size()) {
-                const auto& cmd = commands->at(origIdx);
-
-                // Extract essential fields directly from command (no proto conversion!)
-                actions.push_back(std::make_unique<ShardokAction>(
-                        origIdx,
-                        cmd->GetCommandType(),
-                        cmd->GetPlayerId(),
-                        cmd->GetActorUnitId(),
-                        cmd->GetTargetRow(),
-                        cmd->GetTargetColumn(),
-                        cmd->HasOdds()));
-            }
-        }
-
-        // Sort actions by weight (descending) to ensure MCTS explores high-value actions first
-        const std::vector<double> weights = getActionWeights(actions, state);
-
-        std::vector<size_t> sortedIndices(actions.size());
-        std::iota(sortedIndices.begin(), sortedIndices.end(), 0);
-
-        std::sort(sortedIndices.begin(), sortedIndices.end(), [&weights](size_t a, size_t b) {
-            return weights[a] > weights[b];
-        });
-
-        std::vector<std::unique_ptr<MCTSAction>> sortedActions;
-        sortedActions.reserve(actions.size());
-        for (size_t idx : sortedIndices) { sortedActions.push_back(std::move(actions[idx])); }
-
-        return sortedActions;
-    }
-
-    cacheMisses_.fetch_add(1, std::memory_order_relaxed);
-
-    // Time legal actions computation
-    const auto actionsStart = std::chrono::high_resolution_clock::now();
-
-    // Use cached engine if available, otherwise create and cache it
-    std::shared_ptr<ShardokEngine> engine;
-    if (auto cachedEngine = shardokState->getCachedEngine()) {
-        engine = cachedEngine;
-    } else {
-        engine = std::make_shared<ShardokEngine>(
-                gameSettings_,
-                shardokState->getShardokState(),
-                criticalTileCoords_);
-        shardokState->setCachedEngine(engine);
-    }
-
-    const CommandListSPtr commands = engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-
-    if (!commands || commands->empty()) { return {}; }
-
-    // Filter commands using AICommandFilter (matching original MCTSAI behavior)
-    // Use gameSettings for battalion type lookups
-    const std::vector<size_t> filteredIndices = AICommandFilter::FilterCommands(
-            commands,
-            currentPlayer,
-            isDefender_,
-            shardokState->getShardokState(),
-            *apdCache_,
-            [this](BattalionTypeId typeId) {
-                return gameSettings_->GetGetter().GetBattalionType(typeId);
-            });
-
-    // Convert only filtered commands to MCTSActions
-    std::vector<std::unique_ptr<MCTSAction>> actions;
-    actions.reserve(filteredIndices.size());
-
-    for (const size_t idx : filteredIndices) {
-        if (idx < commands->size()) {
-            const auto& cmd = commands->at(idx);
-
-            // Extract essential fields directly from command (no proto conversion!)
-            actions.push_back(std::make_unique<ShardokAction>(
-                    idx,
-                    cmd->GetCommandType(),
-                    cmd->GetPlayerId(),
-                    cmd->GetActorUnitId(),
-                    cmd->GetTargetRow(),
-                    cmd->GetTargetColumn(),
-                    cmd->HasOdds()));
-        }
-    }
-
-    // Sort actions by weight (descending) to ensure MCTS explores high-value actions first
-    // This is critical when maxPlayerFlips is low (e.g., 1), as only the first few actions
-    // get explored deeply. Original indices are preserved in ShardokAction::getIndex()
-    const std::vector<double> weights = getActionWeights(actions, state);
-
-    // Create index vector for sorting
-    std::vector<size_t> sortedIndices(actions.size());
-    std::iota(sortedIndices.begin(), sortedIndices.end(), 0);
-
-    // Sort indices by weight (descending)
-    std::sort(sortedIndices.begin(), sortedIndices.end(), [&weights](size_t a, size_t b) {
-        return weights[a] > weights[b];
-    });
-
-    // Reorder actions according to sorted indices
-    std::vector<std::unique_ptr<MCTSAction>> sortedActions;
-    sortedActions.reserve(actions.size());
-    for (size_t idx : sortedIndices) { sortedActions.push_back(std::move(actions[idx])); }
-    actions = std::move(sortedActions);
-
-    const auto actionsEnd = std::chrono::high_resolution_clock::now();
-    timeInLegalActionsComputation_.fetch_add(
-            std::chrono::duration_cast<std::chrono::microseconds>(actionsEnd - actionsStart)
-                    .count(),
-            std::memory_order_relaxed);
-
-    // Store in transposition table for future lookups
-    // Note: We only store filtered indices and the engine (which caches commands internally)
-    // This avoids duplicating heavy protocol buffer objects
-    // Use lazy_emplace_l to ensure thread-safe insertion (locks the bucket during construction)
-    legalActionsCache_.lazy_emplace_l(
-            stateHash,
-            [&](typename decltype(legalActionsCache_)::value_type& v) {
-                // Update existing entry
-                v.second.filteredIndices = filteredIndices;
-                v.second.engine = engine;
-            },
-            [&](const typename decltype(legalActionsCache_)::constructor& ctor) {
-                // Create new entry
-                ctor(stateHash, LegalActionsCache{filteredIndices, engine});
-            });
-
-    return actions;
-}
-
-bool ShardokGameEngine::isTerminal(const MCTSGameState& state) const { return state.isTerminal(); }
-
-double ShardokGameEngine::evaluateState(const MCTSGameState& state, MCTSPlayerId playerId) const {
-    return state.score(playerId);
-}
-
-std::vector<size_t> ShardokGameEngine::filterActions(
-        const std::vector<std::unique_ptr<MCTSAction>>& actions,
-        const MCTSGameState& /*state*/) const {
-    // All filtering is already done in getLegalActions() using AICommandFilter
-    // This method is used by simulation policies and doesn't need additional filtering
-    std::vector<size_t> indices;
-    indices.reserve(actions.size());
-    for (size_t i = 0; i < actions.size(); ++i) { indices.push_back(i); }
-    return indices;
-}
-
-std::vector<double> ShardokGameEngine::getActionWeights(
-        const std::vector<std::unique_ptr<MCTSAction>>& actions,
-        const MCTSGameState& state) const {
-    // Cast to ShardokGameState to access Shardok-specific methods
-    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
-    if (!shardokState) {
-        throw MCTSInternalError(
-                "ShardokGameEngine::getActionWeights called with non-Shardok state - this "
-                "indicates a type mismatch in the MCTS adapter layer");
-    }
-
-    // Get cached engine and command list for looking up command protos
-    auto cachedEngine = shardokState->getCachedEngine();
-    if (!cachedEngine) {
-        throw MCTSInternalError(
-                "ShardokGameEngine::getActionWeights called with state that has no cached engine");
-    }
-
-    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
-    const CommandListSPtr commands = cachedEngine->GetAvailableCommandsForAIPlayer(currentPlayer);
-
-    // Determine if current player is defender (not root player!)
-    // During simulation we need to use the correct perspective for action weighting
-    bool currentPlayerIsDefender = false;
-    const auto& gameState = shardokState->getShardokState();
-    for (const auto* pi : *gameState->player_infos()) {
-        if (pi->player_id() == currentPlayer) {
-            currentPlayerIsDefender = pi->is_defender();
-            break;
-        }
-    }
-
-    // Use AIHeuristicWeighting for fast O(1) context-aware command weighting
-    std::vector<double> weights;
-    weights.reserve(actions.size());
-
-    for (const auto& action : actions) {
-        const auto* shardokAction = dynamic_cast<const ShardokAction*>(action.get());
-        if (!shardokAction) {
-            throw MCTSInternalError(
-                    "ShardokGameEngine::getActionWeights encountered non-Shardok action - this "
-                    "indicates a type mismatch in the MCTS adapter layer");
-        }
-
-        // Look up command proto from cached engine using action's index
-        const size_t cmdIndex = shardokAction->getIndex();
-        if (cmdIndex >= commands->size()) {
-            throw MCTSInternalError(
-                    "ShardokGameEngine::getActionWeights: action index out of bounds");
-        }
-
-        const auto& cmd = commands->at(cmdIndex);
-
-        weights.push_back(AIHeuristicWeighting::GetCommandWeight(
-                cmd->GetCommandType(),
-                cmd->GetActorUnitId(),
-                cmd->GetPlayerId(),
-                Coords{cmd->GetTargetRow(), cmd->GetTargetColumn()},
-                gameState,
-                castleCoords_,
-                apdCache_,
-                currentPlayerIsDefender,  // Use current player's role, not root player's!
-                [this](BattalionTypeId typeId) {
-                    return gameSettings_->GetGetter().GetBattalionType(typeId);
-                }));
-    }
-
-    return weights;
-}
-
-double ShardokGameEngine::getActionScore(
-        const MCTSGameState& state,
-        const MCTSAction& action,
-        MCTSPlayerId playerId) const {
-    auto newState = applyAction(state, action);
-    if (!newState) { return 0.0; }
-
-    return newState->score(playerId);
-}
-
-bool ShardokGameEngine::shouldStopSearch(
-        const MCTSGameState& /*state*/,
-        int /*iterations*/,
-        std::chrono::steady_clock::time_point /*startTime*/) const {
-    // Could add early termination logic here
-    return false;
-}
-
-size_t ShardokGameEngine::mapFilteredIndexToOriginal(
-        size_t filteredIndex,
-        const MCTSGameState& state) const {
-    // Get the filtered actions (uses cached engine)
-    auto actions = getLegalActions(state, state.currentPlayerId(), 0, 0);
-
-    // Check bounds
-    if (filteredIndex >= actions.size()) { return filteredIndex; }
-
-    // Extract the original index from the ShardokAction
-    const auto* shardokAction = dynamic_cast<const ShardokAction*>(actions[filteredIndex].get());
-    if (!shardokAction) { return filteredIndex; }
-
-    // ShardokAction stores the original unfiltered index
-    return shardokAction->getIndex();
-}
-
-void ShardokGameEngine::reportCacheStatistics() const {
-    const uint64_t hits = cacheHits_.load(std::memory_order_relaxed);
-    const uint64_t misses = cacheMisses_.load(std::memory_order_relaxed);
-    const uint64_t hashTime = timeInHashComputation_.load(std::memory_order_relaxed);
-    const uint64_t actionsTime = timeInLegalActionsComputation_.load(std::memory_order_relaxed);
-    const uint64_t totalLookups = hits + misses;
-
-    if (totalLookups > 0) {
-        const double hitRate = static_cast<double>(hits) / static_cast<double>(totalLookups);
-        const double avgHashTimeUs =
-                static_cast<double>(hashTime) / static_cast<double>(totalLookups);
-        const double avgActionsTimeUs =
-                misses > 0 ? static_cast<double>(actionsTime) / static_cast<double>(misses) : 0.0;
-
-        printf("Legal Actions Cache Stats:\n");
-        printf("  Lookups: %llu hits, %llu misses, %.1f%% hit rate, %zu entries\n",
-               static_cast<unsigned long long>(hits),
-               static_cast<unsigned long long>(misses),
-               hitRate * 100.0,
-               legalActionsCache_.size());
-        printf("  Timing: %.2f us avg hash, %.2f us avg actions (on miss)\n",
-               avgHashTimeUs,
-               avgActionsTimeUs);
-        printf("  Total time: %.2f ms in hash, %.2f ms in actions\n",
-               hashTime / 1000.0,
-               actionsTime / 1000.0);
-
-        // Calculate if transposition table is worth it
-        const double timeWithCache = hashTime + actionsTime;
-        const double timeWithoutCache =
-                avgActionsTimeUs * static_cast<double>(totalLookups);  // All lookups recompute
-        const double savings = (timeWithoutCache - timeWithCache) / timeWithoutCache * 100.0;
-        printf("  Cache savings: %.1f%% vs. no cache (%.2f ms saved)\n",
-               savings,
-               (timeWithoutCache - timeWithCache) / 1000.0);
-    }
-}
-
-void ShardokGameEngine::resetCacheStatistics() {
-    cacheHits_.store(0, std::memory_order_relaxed);
-    cacheMisses_.store(0, std::memory_order_relaxed);
-    timeInHashComputation_.store(0, std::memory_order_relaxed);
-    timeInLegalActionsComputation_.store(0, std::memory_order_relaxed);
-}
-
-ChanceOutcomeInfo ShardokGameEngine::getBinaryOutcomeInfo(
-        const MCTSGameState& state,
-        const MCTSAction& action) const {
-    const auto* shardokState = dynamic_cast<const ShardokGameState*>(&state);
-    const auto* shardokAction = dynamic_cast<const ShardokAction*>(&action);
-
-    if (!shardokState || !shardokAction) {
-        throw ShardokInternalErrorException("Invalid state or action type in getBinaryOutcomeInfo");
-    }
-
-    // Check for multi-outcome commands (roll affects outcome quality, not just success/failure)
-    // These use multiOutcome() with fixed seeds to sample the range of possible results
-    using namespace net::eagle0::shardok::common;
-    const auto commandType = static_cast<CommandType>(shardokAction->getType());
-
-    switch (commandType) {
-        case END_TURN_COMMAND:
-            // END_TURN has random effects (fire spread, weather changes)
-            return ChanceOutcomeInfo::multiOutcome(5);
-
-        case MELEE_COMMAND:
-        case ARCHERY_COMMAND:
-        case CHARGE_COMMAND:
-        case REDUCE_COMMAND:
-            // Combat/siege commands: OpenEndedPercentile roll affects damage dealt
-            // Use 5 outcomes to sample the roll distribution
-            return ChanceOutcomeInfo::multiOutcome(5);
-
-        case CHALLENGE_DUEL_COMMAND:
-            // Duels have multiple combat rounds with rolls, so outcomes vary significantly
-            return ChanceOutcomeInfo::multiOutcome(5);
-
-        default:
-            // Continue to binary outcome handling below
-            break;
-    }
-
-    const auto currentPlayer = static_cast<PlayerId>(state.currentPlayerId());
-
-    // Get or create the engine for this state
-    std::shared_ptr<ShardokEngine> engine;
-    if (auto cachedEngine = shardokState->getCachedEngine()) {
-        engine = cachedEngine;
-    } else {
-        engine = std::make_shared<ShardokEngine>(
-                gameSettings_,
-                shardokState->getShardokState(),
-                criticalTileCoords_,
-                0,
-                false);
-        // Populate command cache
-        [[maybe_unused]] const auto commands =
-                engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-        shardokState->setCachedEngine(engine);
-    }
-
-    // Get command descriptors
-    const auto descriptors = engine->GetAvailableCommandsForAIPlayer(currentPlayer);
-    const size_t actionIndex = shardokAction->getIndex();
-
-    if (actionIndex >= descriptors->size()) {
-        throw ShardokInternalErrorException("Action index out of range in getBinaryOutcomeInfo");
-    }
-
-    const auto& descriptor = descriptors->at(actionIndex);
-
-    // Get success probability for binary outcome actions
-    if (!descriptor->HasOdds()) {
-        throw ShardokInternalErrorException("Action does not have odds in getBinaryOutcomeInfo");
-    }
-
-    const auto successChancePercentile = descriptor->GetOddsPercentile();
-    const double successProbability = static_cast<double>(successChancePercentile) / 100.0;
-
-    return ChanceOutcomeInfo::binary(successProbability);
-}
-
-void ShardokGameEngine::clearLegalActionsCache() { legalActionsCache_.clear(); }
-
-// Extern-linkage function for testing
-void clearLegalActionsCache_ForTesting() { ShardokGameEngine::clearLegalActionsCache(); }
-
-}  // namespace shardok::mcts
@@ -1,144 +0,0 @@
-//
-// Shardok-specific game engine adapter for MCTS
-//
-
-#ifndef EAGLE0_SHARDOK_GAME_ENGINE_HPP
-#define EAGLE0_SHARDOK_GAME_ENGINE_HPP
-
-#include <atomic>
-#include <functional>
-#include <gtl/phmap.hpp>
-#include <memory>
-#include <vector>
-
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSGameEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-// Forward declarations
-class AICommandFilter;
-class AIScoreCalculator;
-class RandomGenerator;
-
-// Use existing type definitions from the Shardok codebase
-// GameSettingsSPtr and SettingsGetter are defined in GameSettings.hpp
-
-namespace mcts {
-
-class ShardokGameEngine : public MCTSGameEngine {
-public:
-    ShardokGameEngine(
-            const ShardokEngine* engine,
-            const AIScoreCalculator* scoreCalculator,
-            const GameSettingsSPtr& gameSettings,
-            const APDCache* apdCache,
-            const ALCache* alCache,
-            bool isDefender,
-            const AIStrategy& strategy,
-            const CoordsSet& castleCoords,
-            const CoordsSet& criticalTileCoords);
-
-    // MCTSGameEngine interface implementation
-    [[nodiscard]] std::unique_ptr<MCTSGameState> applyAction(
-            const MCTSGameState& state,
-            const MCTSAction& action,
-            double deterministicRoll = -1.0) const override;
-
-    void applyActionMutable(std::unique_ptr<MCTSGameState>& state, const MCTSAction& action)
-            const override;
-
-    [[nodiscard]] std::vector<std::unique_ptr<MCTSAction>> getLegalActions(
-            const MCTSGameState& state,
-            MCTSPlayerId rootPlayerId,
-            int currentPlayerFlips,
-            int maxPlayerFlips) const override;
-
-    [[nodiscard]] bool isTerminal(const MCTSGameState& state) const override;
-
-    [[nodiscard]] double evaluateState(const MCTSGameState& state, MCTSPlayerId playerId)
-            const override;
-
-    [[nodiscard]] std::vector<size_t> filterActions(
-            const std::vector<std::unique_ptr<MCTSAction>>& actions,
-            const MCTSGameState& state) const override;
-
-    [[nodiscard]] std::vector<double> getActionWeights(
-            const std::vector<std::unique_ptr<MCTSAction>>& actions,
-            const MCTSGameState& state) const override;
-
-    [[nodiscard]] double getActionScore(
-            const MCTSGameState& state,
-            const MCTSAction& action,
-            MCTSPlayerId playerId) const override;
-
-    [[nodiscard]] bool shouldStopSearch(
-            const MCTSGameState& state,
-            int iterations,
-            std::chrono::steady_clock::time_point startTime) const override;
-
-    [[nodiscard]] size_t mapFilteredIndexToOriginal(
-            size_t filteredIndex,
-            const MCTSGameState& state) const override;
-
-    [[nodiscard]] BinaryOutcomeInfo getBinaryOutcomeInfo(
-            const MCTSGameState& state,
-            const MCTSAction& action) const override;
-
-    // Report transposition table statistics
-    void reportCacheStatistics() const;
-
-    // Reset cache statistics
-    void resetCacheStatistics();
-
-private:
-    // Transposition table entry for caching legal actions
-    // Note: We don't store command protos since the Engine already caches them
-    struct LegalActionsCache {
-        std::vector<size_t> filteredIndices;
-        std::shared_ptr<ShardokEngine> engine;  // Engine with populated command cache
-    };
-
-    const AIScoreCalculator* scoreCalculator_;
-    const GameSettingsSPtr gameSettings_;
-    const APDCache* apdCache_;
-    const ALCache* alCache_;
-    bool isDefender_;
-    AIStrategy strategy_;
-    const CoordsSet castleCoords_;  // Own the data to avoid dangling references
-    // Computed once to avoid 8.5% overhead per engine construction
-    const CoordsSet criticalTileCoords_;  // Own the data to avoid dangling references
-
-    // Transposition table for legal actions (shared across threads with lock-free hash map)
-    // parallel_flat_hash_map provides thread-safe concurrent access without explicit locking
-    // Using 8 submaps (N=8) to reduce contention with default 16 MCTS threads
-    static gtl::parallel_flat_hash_map<
-            uint64_t,
-            LegalActionsCache,
-            std::hash<uint64_t>,
-            std::equal_to<uint64_t>,
-            std::allocator<std::pair<const uint64_t, LegalActionsCache>>,
-            8,
-            std::mutex>
-            legalActionsCache_;
-    static std::atomic<uint64_t> cacheHits_;
-    static std::atomic<uint64_t> cacheMisses_;
-
-    // Performance timing (in microseconds)
-    static std::atomic<uint64_t> timeInHashComputation_;
-    static std::atomic<uint64_t> timeInLegalActionsComputation_;
-
-public:
-    // Clear the static legal actions cache (useful for tests)
-    static void clearLegalActionsCache();
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_GAME_ENGINE_HPP
@@ -1,125 +0,0 @@
-//
-// Shardok-specific game state adapter implementation
-//
-
-#include "ShardokGameState.hpp"
-
-#include <sstream>
-#include <string>
-#include <utility>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/score/AIScoreCalculator.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok::mcts {
-
-ShardokGameState::ShardokGameState(
-        GameStateW state,
-        const AIScoreCalculator* calculator,
-        const GameSettings* settings,
-        const bool isDefender,
-        AIStrategy strategy,
-        const CoordsSet& castleCoords,
-        const APDCache& apdCache,
-        const ALCache& alCache,
-        const CoordsSet& criticalTileCoords)
-    : state_(std::move(state)),
-      scoreCalculator_(calculator),
-      settings_(settings),
-      isDefender_(isDefender),
-      strategy_(std::move(strategy)),
-      castleCoords_(castleCoords),
-      apdCache_(apdCache),
-      alCache_(alCache),
-      criticalTileCoords_(criticalTileCoords) {}
-
-uint64_t ShardokGameState::hash() const {
-    if (!hashCached_) {
-        cachedHash_ = state_.ComputeFNV1aHash();
-        hashCached_ = true;
-    }
-    return cachedHash_;
-}
-
-double ShardokGameState::score(MCTSPlayerId playerId) const {
-    // Honor the interface contract: score() should return evaluation from playerId's perspective.
-    // Map the requested playerId to defender/attacker role to determine scoring perspective.
-
-    // Look up which player ID is the defender from game state
-    bool foundDefender = false;
-    bool requestedPlayerIsDefender = false;
-
-    if (state_->player_infos()) {
-        for (const auto* pi : *state_->player_infos()) {
-            if (pi && pi->is_defender()) {
-                foundDefender = true;
-                requestedPlayerIsDefender = (static_cast<PlayerId>(playerId) == pi->player_id());
-                break;
-            }
-        }
-    }
-
-    // Fallback: if we can't determine from game state, use isDefender_ which represents
-    // the root player's role (and playerId is always the root player in practice)
-    const bool scoreFromDefenderPerspective =
-            foundDefender ? requestedPlayerIsDefender : isDefender_;
-
-    // Score the current state directly
-    return scoreCalculator_
-            ->GuessedStateScore(scoreFromDefenderPerspective, state_, strategy_, castleCoords_);
-}
-
-MCTSPlayerId ShardokGameState::currentPlayerId() const { return state_->current_player(); }
-
-bool ShardokGameState::isTerminal() const {
-    // Check if game status indicates the game is over
-    if (state_->status()) {
-        const auto gameStatus = state_->status()->state();
-        if (gameStatus == net::eagle0::shardok::storage::fb::GameStatus_::State_VICTORY ||
-            gameStatus == net::eagle0::shardok::storage::fb::GameStatus_::State_DRAW) {
-            return true;
-        }
-    }
-
-    // Check max rounds
-    if (state_->current_round() >= settings_->GetGetter().Backing().max_rounds()) { return true; }
-
-    return false;
-}
-
-std::unique_ptr<MCTSGameState> ShardokGameState::clone() const {
-    auto cloned = std::make_unique<ShardokGameState>(
-            state_,
-            scoreCalculator_,
-            settings_,
-            isDefender_,
-            strategy_,
-            castleCoords_,
-            apdCache_,
-            alCache_,
-            criticalTileCoords_);
-    // Don't copy the cached engine - each state needs its own
-    return cloned;
-}
-
-bool ShardokGameState::equals(const MCTSGameState& other) const {
-    const auto* shardokOther = dynamic_cast<const ShardokGameState*>(&other);
-    if (!shardokOther) { return false; }
-
-    return hash() == shardokOther->hash();
-}
-
-MCTSPlayerId ShardokGameState::getWinner() const {
-    // Note: FlatBuffer doesn't have a winner field
-    // In practice, this would need to determine winner from victory conditions
-    return -1;  // No winner
-}
-
-std::string ShardokGameState::toString() const {
-    std::stringstream ss;
-    ss << "ShardokGameState[Round:" << static_cast<int>(state_->current_round())
-       << " Player:" << currentPlayerId() << " Hash:" << hash() << "]";
-    return ss.str();
-}
-
-}  // namespace shardok::mcts
@@ -1,83 +0,0 @@
-//
-// Shardok-specific game state adapter for MCTS
-//
-
-#ifndef EAGLE0_SHARDOK_GAME_STATE_HPP
-#define EAGLE0_SHARDOK_GAME_STATE_HPP
-
-#include <memory>
-
-#include "src/main/cpp/net/eagle0/common/mcts/abstract/MCTSGameState.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-// Forward declarations
-class AIScoreCalculator;
-
-namespace mcts {
-
-class ShardokGameState : public MCTSGameState {
-public:
-    ShardokGameState(
-            GameStateW state,
-            const AIScoreCalculator* calculator,
-            const GameSettings* settings,
-            bool isDefender,
-            AIStrategy strategy,
-            const CoordsSet& castleCoords,
-            const APDCache& apdCache,
-            const ALCache& alCache,
-            const CoordsSet& criticalTileCoords);
-
-    // MCTSGameState interface implementation
-    [[nodiscard]] uint64_t hash() const override;
-    [[nodiscard]] double score(MCTSPlayerId playerId) const override;
-    [[nodiscard]] MCTSPlayerId currentPlayerId() const override;
-    [[nodiscard]] bool isTerminal() const override;
-    [[nodiscard]] std::unique_ptr<MCTSGameState> clone() const override;
-    [[nodiscard]] bool equals(const MCTSGameState& other) const override;
-    [[nodiscard]] MCTSPlayerId getWinner() const override;
-    [[nodiscard]] std::string toString() const override;
-
-    // Shardok-specific accessors
-    [[nodiscard]] const GameStateW& getShardokState() const { return state_; }
-    [[nodiscard]] GameStateW& getMutableShardokState() { return state_; }
-    [[nodiscard]] bool isDefender() const { return isDefender_; }
-    [[nodiscard]] const GameSettings* getSettings() const { return settings_; }
-    [[nodiscard]] const CoordsSet& getCriticalTileCoords() const { return criticalTileCoords_; }
-
-    // Engine caching for performance (avoids recomputing available commands)
-    void setCachedEngine(std::shared_ptr<ShardokEngine> engine) const { cachedEngine_ = engine; }
-    [[nodiscard]] std::shared_ptr<ShardokEngine> getCachedEngine() const { return cachedEngine_; }
-
-    // Invalidate hash cache when state is mutated
-    void invalidateHashCache() const {
-        hashCached_ = false;
-        cachedHash_ = 0;
-    }
-
-private:
-    GameStateW state_;
-    const AIScoreCalculator* scoreCalculator_;
-    const GameSettings* settings_;
-    bool isDefender_;
-    AIStrategy strategy_;
-    const CoordsSet castleCoords_;  // Own the data to avoid dangling references
-    const APDCache& apdCache_;
-    const ALCache& alCache_;
-    mutable uint64_t cachedHash_ = 0;
-    mutable bool hashCached_ = false;
-    const CoordsSet criticalTileCoords_;  // Own the data to avoid dangling references
-    mutable std::shared_ptr<ShardokEngine> cachedEngine_;  // Engine with cached available commands
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_GAME_STATE_HPP
@@ -1,82 +0,0 @@
-//
-// Factory implementation for creating Shardok-specific MCTS components
-//
-
-#include "ShardokMCTSFactory.hpp"
-
-#include "ShardokAction.hpp"
-#include "ShardokGameEngine.hpp"
-#include "ShardokGameState.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokEngine.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok::mcts {
-
-std::unique_ptr<MCTSGameEngine> ShardokMCTSFactory::createGameEngine(
-        const ShardokEngine& engine,
-        const AIScoreCalculator* scoreCalculator,
-        const GameSettingsSPtr& gameSettings,
-        const APDCache& apdCache,
-        const ALCache& alCache,
-        bool isDefender,
-        const AIStrategy& strategy,
-        const CoordsSet& castleCoords,
-        const CoordsSet& criticalTileCoords) {
-    return std::make_unique<ShardokGameEngine>(
-            &engine,
-            scoreCalculator,
-            gameSettings,
-            &apdCache,
-            &alCache,
-            isDefender,
-            strategy,
-            castleCoords,
-            criticalTileCoords);
-}
-
-std::unique_ptr<MCTSGameState> ShardokMCTSFactory::createGameState(
-        const GameStateW& state,
-        const AIScoreCalculator* scoreCalculator,
-        const GameSettingsSPtr& settings,
-        bool isDefender,
-        const AIStrategy& strategy,
-        const CoordsSet& castleCoords,
-        const APDCache& apdCache,
-        const ALCache& alCache,
-        const CoordsSet& criticalTileCoords) {
-    return std::make_unique<ShardokGameState>(
-            state,
-            scoreCalculator,
-            settings.get(),  // Get raw pointer from shared_ptr
-            isDefender,
-            strategy,
-            castleCoords,
-            apdCache,
-            alCache,
-            criticalTileCoords);
-}
-
-std::vector<std::unique_ptr<MCTSAction>> ShardokMCTSFactory::createActionsFromCommandList(
-        const CommandListSPtr& commands) {
-    std::vector<std::unique_ptr<MCTSAction>> actions;
-    if (!commands) { return actions; }
-
-    actions.reserve(commands->size());
-    for (size_t i = 0; i < commands->size(); ++i) {
-        const auto& cmd = (*commands)[i];
-
-        // Extract essential fields directly from command (no proto conversion!)
-        actions.push_back(std::make_unique<ShardokAction>(
-                i,
-                cmd->GetCommandType(),
-                cmd->GetPlayerId(),
-                cmd->GetActorUnitId(),
-                cmd->GetTargetRow(),
-                cmd->GetTargetColumn(),
-                cmd->HasOdds()));
-    }
-
-    return actions;
-}
-
-}  // namespace shardok::mcts
@@ -1,70 +0,0 @@
-//
-// Factory for creating Shardok-specific MCTS components
-//
-
-#ifndef EAGLE0_SHARDOK_MCTS_FACTORY_HPP
-#define EAGLE0_SHARDOK_MCTS_FACTORY_HPP
-
-#include <functional>
-#include <memory>
-#include <vector>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/ai/AIStrategy.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCommand.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/settings/GameSettings.hpp"
-
-namespace shardok {
-
-// Forward declarations
-class ShardokEngine;
-class AICommandFilter;
-class AIScoreCalculator;
-class GameStateW;
-class GameSettings;
-
-namespace mcts {
-
-// Forward declarations
-class MCTSGameEngine;
-class MCTSGameState;
-class MCTSAction;
-
-class ShardokMCTSFactory {
-public:
-    // Create a Shardok game engine adapter
-    [[nodiscard]] static std::unique_ptr<MCTSGameEngine> createGameEngine(
-            const ShardokEngine& engine,
-            const AIScoreCalculator* scoreCalculator,
-            const GameSettingsSPtr& gameSettings,
-            const APDCache& apdCache,
-            const ALCache& alCache,
-            bool isDefender,
-            const AIStrategy& strategy,
-            const CoordsSet& castleCoords,
-            const CoordsSet& criticalTileCoords);
-
-    // Create a Shardok game state adapter
-    [[nodiscard]] static std::unique_ptr<MCTSGameState> createGameState(
-            const GameStateW& state,
-            const AIScoreCalculator* scoreCalculator,
-            const GameSettingsSPtr& settings,
-            bool isDefender,
-            const AIStrategy& strategy,
-            const CoordsSet& castleCoords,
-            const APDCache& apdCache,
-            const ALCache& alCache,
-            const CoordsSet& criticalTileCoords);
-
-    // Convert from command list to MCTS actions
-    [[nodiscard]] static std::vector<std::unique_ptr<MCTSAction>> createActionsFromCommandList(
-            const CommandListSPtr& commands);
-};
-
-}  // namespace mcts
-}  // namespace shardok
-
-#endif  // EAGLE0_SHARDOK_MCTS_FACTORY_HPP
@@ -1,56 +0,0 @@
-//
-// Created by dancrosby on 3/4/20.
-//
-
-#ifndef EAGLE0_AISCORECALCULATOR_HPP
-#define EAGLE0_AISCORECALCULATOR_HPP
-
-#include <future>
-
-#include "src/main/cpp/net/eagle0/shardok/ai/AIAttackLocations.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/GameStateW.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/ShardokCTypes.h"
-#include "src/main/cpp/net/eagle0/shardok/library/action_point_distances/ActionPointDistancesCache.hpp"
-#include "src/main/cpp/net/eagle0/shardok/library/map/CoordsSet.hpp"
-
-namespace shardok {
-
-using shardok::PlayerId;
-using std::future;
-using std::vector;
-
-using ScoreValue = double;
-
-// Forward declarations
-class ShardokEngine;
-struct AIStrategy;
-
-/// Abstract base class for AI scoring algorithms.
-/// Allows testing different scoring strategies by implementing different scorers.
-class AIScoreCalculator {
-public:
-    virtual ~AIScoreCalculator() = default;
-
-    // Rule of five: explicitly default or delete copy/move operations
-    AIScoreCalculator(const AIScoreCalculator &) = default;
-    AIScoreCalculator &operator=(const AIScoreCalculator &) = default;
-    AIScoreCalculator(AIScoreCalculator &&) = default;
-    AIScoreCalculator &operator=(AIScoreCalculator &&) = default;
-
-protected:
-    AIScoreCalculator() = default;
-
-public:
-    /// Evaluate the score of a guessed game state based on the current AI strategy.
-    /// DOES NOT perform lookahead - this is pure state evaluation.
-    /// For lookahead search, use AICommandEvaluator which depends on this interface.
-    [[nodiscard]] virtual auto GuessedStateScore(
-            bool isDefender,
-            const GameStateW &state,
-            const AIStrategy &aiStrategy,
-            const CoordsSet &allCastleCoords) const -> ScoreValue = 0;
-};
-
-}  // namespace shardok
-
-#endif  // EAGLE0_AISCORECALCULATOR_HPP
@@ -1,112 +0,0 @@
-load("//tools:copts.bzl", "COPTS")
-
-cc_library(
-    name = "ai_score_calculator_interface",
-    hdrs = ["AIScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_attack_locations",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library:shardok_c_types",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
-    ],
-)
-
-cc_library(
-    name = "ai_victory_condition_score_calculator",
-    srcs = ["AIVictoryConditionScoreCalculator.cpp"],
-    hdrs = ["AIVictoryConditionScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:__pkg__",  # Needed by abstract base class
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_attack_groups",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_attack_locations",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_common_types",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_distance_debuf",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_score_utilities",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances",
-        "//src/main/cpp/net/eagle0/shardok/library/action_point_distances:action_point_distances_cache",
-        "//src/main/flatbuffer/net/eagle0/shardok/storage:game_state_cc_fbs",
-    ],
-)
-
-cc_library(
-    name = "normalized_ai_score_calculator",
-    srcs = ["NormalizedAIScoreCalculator.cpp"],
-    hdrs = ["NormalizedAIScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        ":ai_score_calculator_interface",
-        ":ai_victory_condition_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_unit_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_water_crossing_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:abstract_ai_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:ai_score_calculator_shared_utilities",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-        "//src/main/cpp/net/eagle0/shardok/library/map:coords_set",
-        "//src/main/cpp/net/eagle0/shardok/library/settings:game_settings",
-    ],
-)
-
-cc_library(
-    name = "standard_ai_score_calculator",
-    srcs = ["StandardAIScoreCalculator.cpp"],
-    hdrs = ["StandardAIScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        ":ai_score_calculator_interface",
-        ":ai_victory_condition_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_unit_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_water_crossing_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:abstract_ai_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-    ],
-)
-
-cc_library(
-    name = "mcts_optimized_ai_score_calculator",
-    srcs = ["MCTSOptimizedAIScoreCalculator.cpp"],
-    hdrs = ["MCTSOptimizedAIScoreCalculator.hpp"],
-    copts = COPTS,
-    visibility = [
-        "//src/main/cpp/net/eagle0/shardok/ai:__subpackages__",
-        "//src/main/cpp/net/eagle0/shardok/ai_performance_runner:__pkg__",
-        "//src/test/cpp/net/eagle0/shardok/ai:__subpackages__",
-    ],
-    deps = [
-        ":ai_score_calculator_interface",
-        ":ai_victory_condition_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_strategy",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_unit_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai:ai_water_crossing_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:abstract_ai_score_calculator",
-        "//src/main/cpp/net/eagle0/shardok/ai/score/private:ai_score_calculator_shared_utilities",
-        "//src/main/cpp/net/eagle0/shardok/library:engine",
-        "//src/main/cpp/net/eagle0/shardok/library:game_state_w",
-    ],
-)
--- a/Show More
+++ b/Show More