Does it provide help with specific index types?

Yes, it covers a wide range of indexes including B-Tree, GIN for JSONB/Search, GiST for geometric data, and BRIN for very large datasets.

What databases does this skill support?

While many patterns are universal, this skill features specialized optimization techniques for PostgreSQL and MySQL, including specific EXPLAIN syntax and advanced index types.

How does it help with large table performance?

It provides strategies for managing scale, such as replacing slow OFFSET pagination with cursor-based logic, implementing table partitioning, and using materialized views for expensive aggregations.

Can this skill help fix N+1 query issues in my code?

Yes, it identifies N+1 query anti-patterns in application logic and provides specific refactoring patterns using JOINs or batch loading to consolidate database hits.

SQL Optimization Patterns

Name: SQL Optimization Patterns
Author: wshobson

bywshobson

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23,194

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Database Management

Optimizes SQL queries and database schemas through advanced indexing strategies and systematic execution plan analysis.

This skill empowers developers to transform sluggish database operations into high-performance queries by applying industry-standard optimization patterns. It provides Claude with specialized knowledge in interpreting PostgreSQL EXPLAIN plans, implementing sophisticated indexing (B-Tree, GIN, GiST), eliminating N+1 query anti-patterns, and managing large-scale data through partitioning and materialized views. Whether you're debugging production bottlenecks or architecting a new schema, this skill ensures your database layer remains scalable, cost-effective, and responsive by focusing on execution efficiency and reduced resource consumption.

Key Features

01High-performance pagination patterns using cursor-based navigation

0223,194 GitHub stars

03Remediation of N+1 query anti-patterns through JOINs and batch loading techniques

04In-depth analysis of EXPLAIN and EXPLAIN ANALYZE query plans to identify bottlenecks

05Database architecture guidance for partitioning, materialized views, and subquery optimization

06Implementation of advanced indexing strategies including composite, partial, and covering indexes

Use Cases

01Detecting and fixing inefficient query patterns in application code during the development cycle

02Designing high-performance database schemas for applications with rapidly growing datasets

03Refactoring slow-running production queries to reduce latency and database server load

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add wshobson/agents sql-optimization-patterns

For use in Claude.ai and ChatGPT

Download Skill