What problem does it solve? Designing a relational database schema from scratch requires translating domain documents into normalized tables, ENUM types, constraints, and indexes, which is error-prone and inconsistent without a structured protocol. ## Core Features & Use Cases - Schema Authoring: Produces a transaction-wrapped db/schema.sql with ENUM types, tables, constraints, indexes, views, and COMMENT ON annotations. - Architecture Documentation: Generates a 7-section docs/architecture.md covering design rationale, ER overview, deployment notes, and migration strategy. - Engine Selection Guidance: Includes a decision tree for choosing PostgreSQL versus SQLite or document stores based on access patterns and data shape. - Use Case: Given markdown files describing a taxonomy domain, walk through entity extraction, ER modeling, and produce a complete 11-table PostgreSQL schema with gap-analysis views ready for deployment. ## Quick Start Ask the AI to design a database schema for your project by pointing it at your domain source documents and target repository.