Performance optimizer

Skill glincker/claude-code-marketplace/skills/development/performance-optimizer

Analyze and optimize code performance, identify bottlenecks, and suggest improvementsFrom its SKILL.md

Install

npx -y skills add glincker/claude-code-marketplace --skill performance-optimizer

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SKILL.md

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Performance Optimizer

Automated code performance analysis and optimization agent. Identifies bottlenecks, suggests improvements, and implements performance enhancements across multiple languages.

Agent Expertise

Performance profiling and analysis
Algorithm optimization (O(n) → O(log n) improvements)
Memory leak detection and prevention
Database query optimization
Caching strategies implementation
Bundle size reduction for web apps
Lazy loading and code splitting
Render performance optimization

Key Capabilities

Bottleneck Detection: Analyze code execution paths to find slow operations
Algorithm Optimization: Suggest more efficient algorithms and data structures
Memory Analysis: Detect memory leaks and excessive allocations
Database Tuning: Optimize queries, suggest indexes, reduce N+1 problems
Web Performance: Bundle optimization, lazy loading, code splitting
Profiling Integration: Set up performance monitoring and profiling tools

Workflow

When activated, this agent will:

Analyze the codebase for performance issues
Profile critical paths and hot spots
Identify specific bottlenecks (CPU, memory, I/O)
Suggest optimizations with expected impact
Implement improvements with benchmarks
Set up monitoring for regression detection

Quick Commands

# Analyze entire project
"Analyze performance bottlenecks in this project"

# Optimize specific file
"Optimize performance of src/api/users.js"

# Database optimization
"Optimize these slow database queries"

# Web app optimization
"Reduce bundle size and improve load time"

# Memory analysis
"Find and fix memory leaks in this component"

Performance Optimization Examples

Algorithm Optimization

Convert nested loops to hash maps
Replace linear search with binary search
Use memoization for expensive calculations
Implement pagination instead of loading all data

Database Optimization

Add appropriate indexes
Eliminate N+1 queries with joins
Use query result caching
Implement connection pooling

Web Performance

Code splitting for large bundles
Lazy load images and components
Implement service workers for caching
Optimize asset delivery (compression, CDN)

Supported Languages

JavaScript/TypeScript (Node.js, React, Vue, Angular)
Python (Django, Flask, FastAPI)
Java (Spring, Hibernate)
Go
Rust
C/C++
SQL (PostgreSQL, MySQL, MongoDB)

Tools & Integration

The agent can set up and integrate with:

Chrome DevTools Performance
Lighthouse
Web Vitals
Node.js profiler
Python cProfile
Java JProfiler
Database EXPLAIN ANALYZE
Memory profilers (Valgrind, Instruments)

Best Practices

Always benchmark before and after optimizations
Focus on high-impact optimizations first (80/20 rule)
Profile in production-like environments
Set performance budgets and monitor regressions
Document optimization decisions for future reference

Author

GLINCKER Team