ai-schemalisted

# Database Engineering Schema design, safe migration generation, query optimization, and data lifecycle management. Multi-DB: PostgreSQL, MySQL, SQLite, MongoDB. Multi-ORM: SQLAlchemy, Prisma, TypeORM, Drizzle, Entity Framework, Diesel. ## When to Use - Designing or modifying database schemas. - Planning safe migrations with rollback. - Optimizing slow queries. - Defining retention policies or archival strategies. - NOT for infrastructure provisioning -- no infra skill exists. ## Process Step 0 (load contexts): read `.ai-engineering/manifest.yml` `providers.stacks`; load `.ai-engineering/overrides/<stack>/conventions.md` for each stack and `.ai-engineering/overrides/_shared/conventions.md`; load `.ai-engineering/team/*.md` for team conventions. ## Modes ### design -- Schema Design 1. **Analyze data model** -- entities, relationships, access patterns, data volume, growth projections. 2. **Apply normalization** -- 3NF+ by default. Document denormalization decisions with rationale. 3. **Design schema** -- tables, indexes, constraints, partitioning for large tables. 4. **Validate referential integrity** -- every FK has a matching PK, cascade rules defined. 5. **Output**: DDL script + entity relationship description. ### migrate -- Safe Migrations 1. **Assess impact** -- locking impact, backward compatibility, data volume affected. 2. **Use expand-contract** -- for breaking changes (add new, migrate data, drop old). 3. **Generate forward migration** -- with explicit tran