How does this skill help with slow queries?

It analyzes query execution plans and recommends specific indexing or query restructuring to minimize sequential scans and reduce execution costs.

Can it identify N+1 query problems?

Yes, it provides specific code patterns to detect N+1 anti-patterns and replace them with efficient JOINs or batch loading strategies.

Which database engines are supported?

While focusing on PostgreSQL and MySQL, the skill covers fundamental SQL optimization principles applicable to most relational database management systems.

How do I use the EXPLAIN analysis feature?

By providing your SQL query and its EXPLAIN output to Claude, the skill will interpret metrics like cost, actual time, and scan types to suggest optimizations.

SQL Optimization Patterns

Name: SQL Optimization Patterns
Author: HermeticOrmus

byHermeticOrmus

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データベース管理

Optimizes database performance through advanced indexing strategies, query plan analysis, and efficient SQL design patterns.

概要

This skill empowers Claude to transform sluggish database operations into high-performance queries by applying systematic optimization techniques. It provides expert guidance on interpreting EXPLAIN plans, implementing various indexing types such as B-Tree, GIN, and GiST, and eliminating common bottlenecks like N+1 query anti-patterns. Whether you are debugging slow application response times, reducing database costs, or architecting a scalable schema for massive datasets, this skill provides the implementation patterns needed to ensure a performant and efficient database layer.

主な機能

2 GitHub stars
Deep EXPLAIN plan analysis and query cost reduction
High-performance pagination and efficient aggregation techniques
Advanced indexing strategies including composite, partial, and covering indexes
Systematic N+1 query detection and elimination patterns
Advanced tuning with CTEs, batch operations, and table partitioning

ユースケース

Optimizing application response times by reducing database latency and load
Designing high-performance schemas for scalable web applications
Debugging and fixing slow-running production database queries

概要

主な機能

2 GitHub stars
Deep EXPLAIN plan analysis and query cost reduction
High-performance pagination and efficient aggregation techniques
Advanced indexing strategies including composite, partial, and covering indexes
Systematic N+1 query detection and elimination patterns
Advanced tuning with CTEs, batch operations, and table partitioning

ユースケース

Optimizing application response times by reducing database latency and load
Designing high-performance schemas for scalable web applications
Debugging and fixing slow-running production database queries