Sql Query Optimization

This handles the mechanical work of SQL optimization: analyzing EXPLAIN plans, spotting missing indexes, and rewriting queries that perform poorly. You'd reach for it when a query is taking too long and you need to understand why, or when you're trying to figure out if an index is actually being used. It covers both PostgreSQL and MySQL, focuses on practical patterns like join optimization and subquery flattening, and includes the buffer analysis you need for real diagnostics. The approach is systematic rather than clever, which is exactly right for performance work. If you're comfortable reading query plans yourself, you might not need it, but it's solid for catching the common mistakes that slow down most applications.

skills.sh installs: 527
GitHub stars: 379
last updated: Aug 21, 2026

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Install

$ npx -y skills add aj-geddes/useful-ai-prompts --skill sql-query-optimization --agent claude-code

Installs into .claude/skills of the current project.

Files

Overview

Analyze SQL queries to identify performance bottlenecks and implement optimization techniques. Includes query analysis, indexing strategies, and rewriting patterns for improved performance.

When to Use

Slow query analysis and tuning
Query rewriting and refactoring
Index utilization verification
Join optimization
Subquery optimization
Query plan analysis (EXPLAIN)
Performance baseline establishment

Quick Start

PostgreSQL:

-- Analyze query plan with execution time
EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON)
SELECT u.id, u.email, COUNT(o.id) as order_count
FROM users u
LEFT JOIN orders o ON u.id = o.user_id
WHERE u.created_at > NOW() - INTERVAL '1 year'
GROUP BY u.id, u.email;

-- Check table statistics
SELECT * FROM pg_stats
WHERE tablename = 'users' AND attname = 'created_at';