Design and implement database indexing strategies. Use when creating indexes, choosing index types, or optimizing index performance in PostgreSQL and MySQL.
Install
npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill database-indexing-strategySKILL.md
Database Indexing Strategy
Table of Contents
Overview
Design comprehensive indexing strategies to improve query performance, reduce lock contention, and maintain data integrity. Covers index types, design patterns, and maintenance procedures.
When to Use
- Index creation and planning
- Query performance optimization through indexing
- Index type selection (B-tree, Hash, GiST, BRIN)
- Composite and partial index design
- Index maintenance and monitoring
- Storage optimization with indexes
- Full-text search index design
Quick Start
B-tree Indexes (Default):
-- Standard equality and range queries
CREATE INDEX idx_users_email ON users(email);
CREATE INDEX idx_orders_created_at ON orders(created_at DESC);
-- Composite indexes for multi-column queries
CREATE INDEX idx_orders_user_status
ON orders(user_id, status)
WHERE cancelled_at IS NULL;
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| PostgreSQL Index Types | PostgreSQL Index Types |
| MySQL Index Types | MySQL Index Types |
| Single Column Indexes | Single Column Indexes, Composite Indexes, Partial/Filtered Indexes, Expression Indexes |
Best Practices
✅ DO
- Follow established patterns and conventions
- Write clean, maintainable code
- Add appropriate documentation
- Test thoroughly before deploying
❌ DON'T
- Skip testing or validation
- Ignore error handling
- Hard-code configuration values
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