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AI/MLsickn33

database-design

Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.

Stars
39,227
Source
sickn33/antigravity-awesome-skills
Updated
2026-05-30
Slug
sickn33--antigravity-awesome-skills--database-design
View on GitHubRaw SKILL.md

// install — copy + paste into any project

mkdir -p .claude/skills && curl -fsSL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/HEAD/plugins/antigravity-awesome-skills-claude/skills/database-design/SKILL.md -o .claude/skills/database-design.md

Drops the SKILL.md into .claude/skills/database-design.md. Works with Claude Code, Cursor, and any agent that loads SKILL.md files from .claude/skills/.

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

This skill is applicable to execute the workflow or actions described in the overview.

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.