Which database engines does this skill support?

The Query Performance Analyzer supports major database systems including PostgreSQL, MySQL, and MongoDB using standard shell utilities like psql, mysql, and mongosh.

Does this skill provide safety measures for production changes?

Yes, it follows a strict protocol including prerequisite validation, non-production testing, rollback plan creation, and real-time monitoring during deployment.

How do I trigger the performance analysis?

You can activate the skill by asking Claude to 'optimize queries', 'analyze performance', or 'improve query speed' within your project environment.

What kind of outputs does the skill generate?

It produces implementation artifacts like scripts and config files, detailed documentation, test results, and monitoring configurations such as dashboard JSON files.

Query Performance Analyzer

Name: Query Performance Analyzer
Author: BbgnsurfTech

byBbgnsurfTech

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데이터베이스 관리

Optimizes database query performance using automated analysis and structured implementation workflows for SQL and NoSQL systems.

소개

The Query Performance Analyzer is a specialized Claude Code skill designed to identify bottlenecks and enhance the efficiency of database operations. It provides a rigorous five-step framework for assessing query health, designing optimization strategies, and safely implementing changes across PostgreSQL, MySQL, and MongoDB environments. By integrating deep performance diagnostics with automated monitoring and rollback procedures, this skill helps developers eliminate slow-running queries and ensure high-scale database reliability.

주요 기능

Built-in error handling for permissions, connectivity, and resource constraints
3 GitHub stars
Comprehensive query analysis for PostgreSQL, MySQL, and MongoDB
Structured optimization workflow from baseline assessment to production deployment
Automated generation of implementation scripts and configuration files
Customizable monitoring dashboards and observability alerts

사용 사례

Identifying and refactoring slow-running SQL queries in production environments
Benchmarking database latency and throughput during architectural migrations
Automating the deployment of performance-tuning indexes and configurations

소개

주요 기능

Built-in error handling for permissions, connectivity, and resource constraints
3 GitHub stars
Comprehensive query analysis for PostgreSQL, MySQL, and MongoDB
Structured optimization workflow from baseline assessment to production deployment
Automated generation of implementation scripts and configuration files
Customizable monitoring dashboards and observability alerts

사용 사례

Identifying and refactoring slow-running SQL queries in production environments
Benchmarking database latency and throughput during architectural migrations
Automating the deployment of performance-tuning indexes and configurations