Does it provide guidance on index types?

Yes, it covers general B-tree indexes as well as database-specific types like PostgreSQL GIN/GiST and SQL Server Clustered/Non-clustered indexes.

Can it help fix N+1 query problems?

Yes, it identifies common anti-patterns like N+1 and provides implementation patterns for rewriting them into efficient JOINs or Common Table Expressions (CTEs).

How does this skill help with slow queries?

It guides you through interpreting execution plans (EXPLAIN), identifying performance red flags like sequential scans, and recommending specific index additions or query rewrites.

Which databases are supported by this skill?

This skill provides specialized optimization strategies and syntax for PostgreSQL, MySQL, and SQL Server.

What are SARGable queries?

SARGable (Search ARGumentable) queries are written in a way that allows the database engine to use an index effectively, which this skill helps you achieve by avoiding functions on indexed columns.

SQL Performance Optimizer

Name: SQL Performance Optimizer
Author: ancoleman

byancoleman

•

158

数据库管理

Optimizes SQL query performance across PostgreSQL, MySQL, and SQL Server through execution plan analysis and strategic indexing.

关于

This skill provides comprehensive tactical guidance for identifying and resolving database bottlenecks within Claude Code. It enables developers to analyze complex execution plans, implement efficient indexing strategies—including composite and partial indexes—and refactor inefficient query patterns like N+1 queries or non-sargable functions. By leveraging database-specific optimizations for PostgreSQL, MySQL, and SQL Server, this skill ensures high-performance data access layers and significantly reduced server latency for AI-assisted development.

主要功能

Database-specific performance tuning for GIN, B-tree, and Clustered indexes
Strategic index selection and composite index design patterns
SARGable query rewriting to maximize index utilization and reduce scan times
158 GitHub stars
Execution plan analysis for PostgreSQL, MySQL, and SQL Server
Identification and refactoring of query anti-patterns like N+1 and SELECT *

使用场景

Debugging slow API endpoints caused by inefficient or unindexed database queries
Designing optimal index structures for new schemas during the development phase
Refactoring legacy SQL queries to improve application scalability and resource usage

关于

主要功能

Database-specific performance tuning for GIN, B-tree, and Clustered indexes
Strategic index selection and composite index design patterns
SARGable query rewriting to maximize index utilization and reduce scan times
158 GitHub stars
Execution plan analysis for PostgreSQL, MySQL, and SQL Server
Identification and refactoring of query anti-patterns like N+1 and SELECT *

使用场景

Debugging slow API endpoints caused by inefficient or unindexed database queries
Designing optimal index structures for new schemas during the development phase
Refactoring legacy SQL queries to improve application scalability and resource usage