Preparing Archive
database-design
Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.
Architectural Overview
"This module is grounded in ai engineering patterns and exposes 1 core capabilities across 1 execution phases."
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.
Validation Signals
1 runnable scripts
Primary Stack
Python
Tooling Surface
Scripts
Workspace Path
.agents/skills/database-design
Operational Ecosystem
The complete hardware and software toolchain required.
Scripts
Discovered in workspace
Module Topology
Antigravity Core
Principal Engineering Agent
Validation signal
6d 1h ago
1 runnable scripts
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