Sql Optimization Patterns

This walks you through the core SQL optimization techniques that actually move the needle on query performance. It covers reading EXPLAIN plans, building the right indexes (including partial and covering indexes), eliminating N+1 queries, and fixing slow pagination with cursor-based approaches. The examples show real before/after query patterns for common problems like correlated subqueries and inefficient JOINs. What I like is that it focuses on systematic debugging rather than random performance tweaks. Use this when you're staring at slow queries in production or designing schemas that need to scale.

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Install

$ npx -y skills add wshobson/agents --skill sql-optimization-patterns --agent claude-code

Installs into .claude/skills of the current project.

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SQL Optimization Patterns

Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis.

When to Use This Skill

Debugging slow-running queries
Designing performant database schemas
Optimizing application response times
Reducing database load and costs
Improving scalability for growing datasets
Analyzing EXPLAIN query plans
Implementing efficient indexes
Resolving N+1 query problems

Core Concepts

1. Query Execution Plans (EXPLAIN)

Understanding EXPLAIN output is fundamental to optimization.

PostgreSQL EXPLAIN:

-- Basic explain
EXPLAIN SELECT * FROM users WHERE email = 'user@example.com';

-- With actual execution stats
EXPLAIN ANALYZE
SELECT * FROM users WHERE email = 'user@example.com';

-- Verbose output with more details
EXPLAIN (ANALYZE, BUFFERS, VERBOSE)
SELECT u.*, o.order_total
FROM users u
JOIN orders o ON u.id = o.user_id
WHERE u.created_at > NOW() - INTERVAL '30 days';

Key Metrics to Watch:

SKILL.md on GitHub