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j0KZ

performance-profiler

by j0KZ

8 powerful AI development tools for Claude Code, Cursor, Windsurf - Code review, testing, architecture, security, and more

0🍴 0📅 2025年12月26日
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SKILL.md


name: performance-profiler description: "Profile and optimize application performance. Use when diagnosing slow response times, detecting memory leaks, analyzing CPU hotspots, optimizing bundle size, or measuring Core Web Vitals."

Performance Profiler

Comprehensive performance analysis and optimization toolkit

Quick Commands

# CPU profiling
node --inspect app.js
chrome://inspect

# Memory profiling
node --expose-gc --trace-gc app.js

# Bundle size analysis
npx webpack-bundle-analyzer stats.json

# Runtime performance
npx lighthouse http://localhost:3000

Core Functionality

Key Features

  1. CPU Profiling: Identify performance hotspots
  2. Memory Analysis: Detect leaks and optimize usage
  3. Bundle Optimization: Reduce JavaScript payload
  4. Network Performance: API and asset loading
  5. Rendering Performance: DOM and React optimization

Detailed Information

For comprehensive details, see:

cat .claude/skills/performance-profiler/references/profiling-guide.md
cat .claude/skills/performance-profiler/references/optimization-techniques.md
cat .claude/skills/performance-profiler/references/metrics-explained.md

Usage Examples

Example 1: Profile Application Startup

import { PerformanceProfiler } from '@j0kz/performance-profiler';

const profiler = new PerformanceProfiler();
profiler.start('app-startup');

// Your application initialization
await app.initialize();

const metrics = profiler.stop('app-startup');
console.log(`Startup time: ${metrics.duration}ms`);
console.log(`Memory used: ${metrics.memoryUsed}MB`);

Example 2: Detect Memory Leaks

const leakDetector = profiler.createLeakDetector();

await leakDetector.baseline();
// Perform operations
await leakDetector.snapshot();

const leaks = leakDetector.analyze();
if (leaks.found) {
  console.log('Potential memory leaks:', leaks.suspects);
}

Performance Metrics

Core Web Vitals

  • LCP (Largest Contentful Paint): < 2.5s
  • FID (First Input Delay): < 100ms
  • CLS (Cumulative Layout Shift): < 0.1

Application Metrics

  • Time to Interactive (TTI)
  • First Contentful Paint (FCP)
  • Speed Index
  • Total Blocking Time (TBT)

Configuration

{
  "performance-profiler": {
    "targets": {
      "startupTime": 1000,
      "memoryLimit": "256MB",
      "bundleSize": "200KB"
    },
    "sampling": {
      "cpu": 100,
      "memory": 1000
    },
    "reporting": {
      "format": "html",
      "outputDir": "./performance-reports"
    }
  }
}

Integration with Monitoring

// Send metrics to monitoring service
profiler.on('metric', (metric) => {
  monitoring.track(metric.name, metric.value);
});

Notes

  • Supports Node.js and browser environments
  • Integrates with Chrome DevTools Protocol
  • Can generate flamegraphs and memory snapshots
  • Automated performance regression detection

スコア

総合スコア

70/100

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