Does it provide code examples for ORMs?

Yes, it includes practical examples for detecting and fixing N+1 query issues in popular frameworks like SQLAlchemy (Python) and Sequelize (JavaScript).

Which databases are supported by this skill?

This skill provides specialized optimization strategies and syntax for both PostgreSQL and MySQL, the two most popular open-source relational databases.

Can this skill help with scaling high-traffic applications?

Yes, it includes advanced patterns for connection pooling (like PgBouncer), read-replica routing, and range/hash partitioning for large datasets.

How does this skill assist with query analysis?

It provides a framework for interpreting EXPLAIN ANALYZE output, helping you identify sequential scans, expensive sorts, and row estimation divergences.

Database Optimization

Name: Database Optimization
Author: rohitg00

byrohitg00

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604

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Database Management

Optimizes database performance through query analysis, advanced indexing strategies, and architectural best practices for PostgreSQL and MySQL.

The Database Optimization skill transforms Claude into a high-performance Database Administrator, providing deep technical guidance for tuning PostgreSQL and MySQL environments. It offers a structured approach to diagnosing slow queries via EXPLAIN ANALYZE, implementing sophisticated indexing patterns like GIN and GiST, and eliminating architectural bottlenecks such as N+1 query patterns. By integrating best practices for connection pooling, read replicas, and table partitioning, this skill ensures that developers can scale their data layer efficiently while maintaining sub-second query response times in production environments.

Key Features

01In-depth query plan analysis using EXPLAIN ANALYZE for PostgreSQL and MySQL

02Automated N+1 query pattern detection and ORM remediation patterns

03604 GitHub stars

04Scalability guidance for connection pooling and read replica routing

05Comprehensive 10-point query optimization and dangerous pattern checklist

06Advanced indexing strategies including Partial, GIN, GiST, and Covering indexes

Use Cases

01Designing partitioning strategies for time-series data or massive multi-tenant tables

02Identifying and fixing performance regressions in slow-running production SQL queries

03Architecting efficient indexing for specialized data types like JSONB and geospatial coordinates

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add rohitg00/awesome-claude-code-toolkit database-optimization

For use in Claude.ai and ChatGPT

Download Skill