chore: init unity-commander-gameboard feature branch scaffolding

Adds placeholder structure for all Phase 0-6 modules.
See issues #167-#174 for full implementation details.

commander_ai_lab/ai/__init__.py

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+# Phase 2: Dual-Brain AI Decision Engine

commander_ai_lab/ai/decision_logger.py

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+# Phase 6 - decision_logger.py
+# Logs per-decision: game_id, turn, phase, player_id, personality,
+# brain_used, prompt, raw_response, parsed_action, fallback_used
+# Configurable via LOG_AI_DECISIONS env var
+# See issue #173

commander_ai_lab/ai/game_orchestrator.py

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+# Phase 2 - game_orchestrator.py  *** CORE PRIORITY ***
+# GameAIOrchestrator: select_brain(), assign_personalities(), get_action()
+# Brains: DeepSeek-R1-14B (complex) + GPT-OSS-20B (tactical)
+# ChromaDB RAG for per-player card knowledge
+# See issue #169
+
+PERSONALITY_POOL = [
+    "aggressive -- attack early and often, prioritize players with lowest life totals",
+    "control -- counter key spells, hold mana open, only act when clearly advantageous",
+    "combo -- develop mana and card advantage quietly, avoid conflict until ready to win",
+    "political -- make deals, attack whoever is ahead, never fully commit to one target",
+    "pillowfort -- build defensive pieces, let others fight, win slowly through attrition",
+    "stompy -- play the biggest threats as fast as possible, ignore table politics",
+    "tempo -- disrupt opponents early, trade efficiently, stay ahead on board",
+]

commander_ai_lab/cards/__init__.py

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+# Phase 0: Card image cache and data enrichment

commander_ai_lab/cards/card_data_enricher.py

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+# Phase 0 - card_data_enricher.py
+# Injects art_url and art_url_back into CardDTO before broadcasting to Unity
+# See issue #167

commander_ai_lab/cards/image_cache.py

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+# Phase 0 - image_cache.py
+# SQLite-backed lookup: card name/scryfall_id -> local file path
+# See issue #167

commander_ai_lab/forge/__init__.py

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+# Phase 1: Forge subprocess bridge

commander_ai_lab/forge/game_result_logger.py

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+# Phase 6 - game_result_logger.py
+# Captures winner, turn count, elimination order on Forge game end
+# See issue #173

commander_ai_lab/forge/game_state_parser.py

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+# Phase 1 - game_state_parser.py
+# Converts Forge stdout text -> canonical GameStateDTO JSON
+# See issue #168

commander_ai_lab/forge/subprocess_manager.py

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+# Phase 1 - subprocess_manager.py
+# ForgeGameSession + ForgeSubprocessManager
+# Drives interactive Commander games via Forge stdin/stdout pipe
+# See issue #168

commander_ai_lab/training/__init__.py

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+# Phase 6: ML Training Integration

commander_ai_lab/training/training_data_builder.py

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+# Phase 6 - training_data_builder.py
+# Converts decision_log + game_result -> (state, action, reward) tuples
+# Feeds existing PPO pipeline
+# See issue #173

data/.gitkeep

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+# Runtime data directory
+# card_image_index.db, decision_logs/, game_results.jsonl, training_sets/

scripts/build_image_index.py

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+# Phase 0 - build_image_index.py
+# Builds SQLite card_image_index.db: name/scryfall_id -> file path
+# See issue #167

scripts/download_card_images.py

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+# Phase 0 - download_card_images.py
+# Bulk download card images from Scryfall default_cards export
+# Stores at static/card-images/{scryfall_id}_{front|back}.jpg
+# See issue #167

scripts/run_self_play.py

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+# Phase 6 - run_self_play.py
+# Headless self-play runner: all 4 players AI-driven, no Unity needed
+# Usage: python scripts/run_self_play.py --num-games 500 --deck-pool-path data/decks/
+# See issue #173

static/card-images/.gitkeep

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+# Phase 0: Card images downloaded here by scripts/download_card_images.py
+# ~1.5-2GB at normal size

unity-commander-ui/.gitkeep

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+# Phase 4: Unity TCGEngine project lives here
+# See issue #171