What problem does it solve? Designing a data model without understanding requirements leads to costly redesigns, slow queries, and missing lifecycle policies. This Skill provides a systematic discovery process that captures entities, relationships, query patterns, write volumes, and scale constraints before any schema is written. ## Core Features & Use Cases - Discovery Question Framework: Structured questions covering core entities, read patterns, write patterns, data lifecycle, and scale constraints with follow-up prompts and example answers. - Entity & Relationship Techniques: Noun extraction, use case walkthroughs, event storming, cardinality analysis, and dependency analysis to identify entities and map relationships. - Validation Strategies: Query walkthroughs, normalization checks (1NF-3NF with strategic denormalization), write path testing, and scalability analysis to verify the model against real use cases. - Use Case: Before building an e-commerce backend, walk through the discovery framework to document that orders need 5000 status updates per day, users require soft-delete with 7-year retention, and the orders table will reach 10M rows in two years, then produce a discovery summary that drives ERD and schema design. ## Quick Start Ask me the data model discovery questions for my application so we can document entities, relationships, query patterns, and scale requirements before designing the schema.
