youneedgreg/chessy

AI Summary: This issue involves implementing a comprehensive tactical pattern detection system for chess. The goal is to create a new module, `logic/tactics.ts`, capable of identifying various common tactical motifs such as hanging pieces, pins, forks, skewers, back rank weaknesses, and discovered attacks. The system must accurately detect these tactics in test positions, provide flags for an explanation system, and strictly avoid any false positives.

AI Summary: This GitHub issue proposes building a comprehensive TypeScript library of over 50 chess principles. It involves defining and categorizing principles for different game phases (opening, middlegame, endgame) and tactical concepts, with each principle requiring a clear explanation template and an example.

AI Summary: This issue involves implementing a move classification system that grades chess moves (e.g., brilliant, blunder) based on engine evaluation deltas. Key features include context-aware classification depending on the game phase, special handling for mate scores, and comprehensive testing. The system must provide correct classifications for various positions, handle edge cases, and execute quickly.

AI Summary: This issue involves building a rule-based system, implemented in `logic/explanations.ts`, to generate principle-based explanations for chess moves or positions. The system will map game state inputs (evaluation delta, tactics, and position) to over 50 context-aware explanation templates. Key requirements include generating clear, helpful, fast, and deterministic explanations without relying on AI, while also ensuring the template system is expandable.

AI Summary: This issue describes the creation of an 'Engine Evaluation Service' responsible for analyzing chess positions. The service needs to implement position evaluation with configurable depth, calculate centipawn loss, support multi-PV for alternative moves, and return the best move(s). A key acceptance criterion is achieving evaluations in under 100ms at depths 15-18 while ensuring accuracy.

AI Summary: This issue aims to integrate Stockfish WASM into the application by setting it up within a Web Worker. The primary goal is to enable non-blocking chess evaluations by implementing the UCI protocol for communication between the main thread and the Stockfish engine, along with robust error handling.

AI Summary: This issue aims to establish strong TypeScript type definitions for all engine-related data structures. It involves creating a dedicated `engine/types.ts` file, defining interfaces such as `EngineEvaluation` and `MoveAnalysis`, and an enum `TacticalFlag`. The core goal is to ensure all types are accurately defined, avoid `any` types, and are well-documented with JSDoc comments.

AI Summary: This issue focuses on configuring Tailwind CSS with a 'dark-mode-first' strategy. It involves setting up custom design tokens for colors and fonts, making them accessible via CSS variables, and ensuring the default theme is dark while maintaining a lean CSS output.

AI Summary: This GitHub issue details the initial setup of a project's directory structure. It requires creating several top-level directories such as `/app`, `/components`, `/engine`, `/logic`, `/state`, and `/lib`. A `README.md` file, explaining the purpose of each directory, must also be added to ensure clarity and maintainability.

AI Summary: This issue focuses on initializing a new chess platform by installing all its core and development dependencies. Key tasks include integrating `chess.js` for game logic, `zustand` for state management, an AI engine like `stockfish`, and a UI library such as `react-chessboard`. Additionally, development tools like ESLint and Prettier must be set up, and `package.json` scripts configured for a robust development workflow, ensuring all installations are secure.