{
  "name": "db-schema-design",
  "version": "0.1.0",
  "description": "Design a database schema from access patterns — paradigm chosen deliberately (relational/document/key-value/wide-column/graph), keys and partitioning driven by the actual queries, indexes mapped to predicates, money/time types right, and every read path verified to have a supporting access path. Use when the user is designing a data model, schema, or tables for a feature, choosing a database, or asks how to structure/store data.",
  "entrypoint": "SKILL.md",
  "deps": { "npm": [], "pip": [] },
  "env": { "required": [], "optional": [] },
  "related": ["api-contract-draft", "data-contract", "migration-plan", "tech-comparison-matrix"],
  "tags": ["database", "schema-design", "data-model", "indexing", "sql", "nosql"],
  "model": { "tier": "standard", "rationale": "Design synthesis from access patterns against a fixed paradigm/indexing/anti-pattern reference. Paradigm and denormalization judgment is bounded; escalate via ambiguous-input on contested scale/consistency tradeoffs." }
}