When should I use grey-haven-performance-optimization?

grey-haven-performance-optimization is useful in the following scenarios: • Algorithm Refinement: Refactoring inefficient O(n²) logic into O(n) solutions to improve computational speed and scalability. • Database Tuning: Identifying and eliminating N+1 query patterns and implementing strategic indexing to reduce API response times. • Frontend Optimization: Enhancing React application responsiveness using memoization, virtualized lists, and asset code-splitting. • Resource Management: Diagnosing and resolving complex memory leaks and high CPU/memory usage in production environments. • Latency Reduction: Implementing effective API caching strategies and asynchronous processing to meet strict SLA performance targets.

grey-haven-performance-optimization

from greyhaven-ai

Comprehensive performance analysis and optimization for algorithms (O(n²)→O(n)), databases (N+1 queries, indexes), React (memoization, virtual lists), bundles (code splitting), API caching, and memory leaks. 85%+ improvement rate. Use when application is slow, response times exceed SLA, high CPU/memory usage, performance budgets needed, or when user mentions 'performance', 'slow', 'optimization', 'bottleneck', 'speed up', 'latency', 'memory leak', or 'performance tuning'.

⭐15stars🔀2forks📁View on GitHub🕐Updated Dec 27, 2025

When & Why to Use This Skill

This Claude skill provides a comprehensive framework for full-stack performance optimization, targeting critical bottlenecks in algorithms, databases, and frontend frameworks like React. It offers production-ready patterns and profiling templates to reduce latency, fix memory leaks, and optimize resource usage, helping developers achieve an 85%+ improvement rate in application speed and efficiency.

Use Cases

Algorithm Refinement: Refactoring inefficient O(n²) logic into O(n) solutions to improve computational speed and scalability.
Database Tuning: Identifying and eliminating N+1 query patterns and implementing strategic indexing to reduce API response times.
Frontend Optimization: Enhancing React application responsiveness using memoization, virtualized lists, and asset code-splitting.
Resource Management: Diagnosing and resolving complex memory leaks and high CPU/memory usage in production environments.
Latency Reduction: Implementing effective API caching strategies and asynchronous processing to meet strict SLA performance targets.

name	grey-haven-performance-optimization
description	"Comprehensive performance analysis and optimization for algorithms (O(n²)→O(n)), databases (N+1 queries, indexes), React (memoization, virtual lists), bundles (code splitting), API caching, and memory leaks. 85%+ improvement rate. Use when application is slow, response times exceed SLA, high CPU/memory usage, performance budgets needed, or when user mentions 'performance', 'slow', 'optimization', 'bottleneck', 'speed up', 'latency', 'memory leak', or 'performance tuning'."
# v2.0.43	Skills to auto-load for performance work
# v2.0.74	Tools for performance optimization

name

grey-haven-performance-optimization

description

"Comprehensive performance analysis and optimization for algorithms (O(n²)→O(n)), databases (N+1 queries, indexes), React (memoization, virtual lists), bundles (code splitting), API caching, and memory leaks. 85%+ improvement rate. Use when application is slow, response times exceed SLA, high CPU/memory usage, performance budgets needed, or when user mentions 'performance', 'slow', 'optimization', 'bottleneck', 'speed up', 'latency', 'memory leak', or 'performance tuning'."

# v2.0.43

Skills to auto-load for performance work

# v2.0.74

Tools for performance optimization

Performance Optimization Skill

Comprehensive performance analysis and optimization techniques for identifying bottlenecks and improving application speed.

Description

This skill provides production-ready patterns, examples, and checklists for optimizing application performance across algorithms, databases, infrastructure, and code structure.

What's Included

Examples (`examples/`)

Algorithm optimization - Improve time complexity (O(n²) → O(n))
Database optimization - Eliminate N+1 queries, add indexes
Bundle size reduction - Code splitting, tree shaking
React performance - Memoization, virtual lists
API response time - Caching strategies, async processing
Memory optimization - Reduce allocations, fix leaks

Reference Guides (`reference/`)

Performance profiling tools and techniques
Benchmarking best practices
Optimization decision frameworks
Performance budget guidelines
Monitoring and alerting strategies

Templates (`templates/`)

Performance test templates (Lighthouse, Web Vitals)
Benchmark comparison templates
Optimization report structures
Performance budget definitions

Use This Skill When

Application is slow or unresponsive
Response times exceed SLA targets
High CPU/memory usage detected
Need to meet performance budgets
Optimizing for production deployment

performance-optimizer - Automated performance analysis and optimization
memory-profiler - Memory leak detection and profiling
observability-engineer - Production monitoring setup

Quick Start

# View optimization examples
ls examples/

# Check reference guides
ls reference/

# Use templates for benchmarking
ls templates/

Metrics

Optimization Success Rate: 85%+ performance improvement
Coverage: Algorithm, database, infrastructure, code structure
Production-Ready: All examples tested in real applications

Skill Version: 1.0 Last Updated: 2025-01-15