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Use when implementing or reviewing football data logic, pitch coordinates, event modeling, or sports vision pipelines.
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Use when designing, reviewing, or modifying backend API endpoints, schemas, validation, and API documentation.
Use when reviewing architecture boundaries, dependency direction, or multi-layer design decisions across modules.
Use when shaping new features or behavior changes that need requirements clarification and option tradeoff exploration before implementation.
Use when React components are too large or complex and need extraction, simplification, or separation of concerns.
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Use when modeling domain concepts, aggregates, and bounded contexts or checking DDD alignment in existing code.
Based on SOC occupation classification
| name | football-data-ai |
| description | Use when implementing or reviewing football data logic, pitch coordinates, event modeling, or sports vision pipelines. |
Apply domain-specific logic to football-related features. This includes pitch geometry, industry-standard data formats (Opta, StatsBomb), and computer vision pipelines for sports.
