About sql-query-optimization
A skill for analyzing and tuning SQL queries, intended for developers working on database performance. It covers query plans, indexing, and rewriting patterns to address bottlenecks.
Key features
- 01Query plan analysis
- 02Index utilization checks
- 03Join optimization
- 04Subquery optimization
- 05Query rewriting patterns
Use cases
- 01Investigating slow queries
- 02Verifying index usage
- 03Tuning joins and subqueries
- 04Establishing performance baselines
Install
Copy the command and run it in a terminal.
$
npx skills add https:/ / github.com/ aj-geddes/ useful-ai-prompts --skill sql-query-optimizationAfter installing, type/sql-query-optimizationin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
references/analyze-current-performance.mdbatch-operations.mdcommon-optimization-patterns.mdquery-rewriting-techniques.mdscripts/validate-schema.shtemplates/migration-template.sqlDetails
From the project READMESQL Query Optimization
Table of Contents
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';
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| Analyze Current Performance | Analyze Current Performance |
| Common Optimization Patterns | Common Optimization Patterns |
| Query Rewriting Techniques | Query Rewriting Techniques |
| Batch Operations | Batch Operations |
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
Comments
Markdown supported