database-design
Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.
By sickn33 · 2,062 installs
npx skills add sickn33/agentic-awesome-skills --skill database-design
Source repository · Upstream listing
Database Design
Learn to THINK, not copy SQL patterns.
🎯 Selective Reading Rule
Read ONLY files relevant to the request! Check the content map, find what you need.
File Description When to Read
database selection.md PostgreSQL vs Neon vs Turso vs SQLite Choosing database
orm selection.md Drizzle vs Prisma vs Kysely Choosing ORM
schema design.md Normalization, PKs, relationships Designing schema
indexing.md Index types, composite indexes Performance tuning
optimization.md N+1, EXPLAIN ANALYZE Query optimization
migrations.md Safe migrations, serverless DBs Schema changes
⚠️ Core Principle
ASK user for database preferences when unclear
Choose database/ORM based on CONTEXT
Don't default to PostgreSQL for everything
Decision Checklist
Before designing schema:
[ ] Asked user about database preference?
[ ] Chosen database for THIS context?
[ ] Considered deployment environment?
[ ] Planned index strategy?
[ ] Defined relationship types?
Anti Patterns
❌ Default to PostgreSQL for simple apps (SQLite may suffice)
❌ Skip indexing
❌ Use SELECT in production
❌ Store JSON when structured data is better
❌ Ignore N+1 queries
When to Use
Use when selecting a database model, reviewing schema relationships and indexes, or assessing a proposed schema with the bundled advisory tools.
Schema helper
scripts/schema validator.py is a read only heuristic inventory, not a Prisma or Drizzle parser. Missing schemas, unsupported formats and heuristic only results return nonzero with passed: false and analysis complete: false . Use the project local ORM validator for syntax and type checks; review migration and constraint semantics separately.
Limitations
Use this skill only when the task clearly matches the scope described above.
Do not treat the output as a substitute for environment specific validation, testing, or expert review.
Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.