skills/j0kz/mcp-agents/performance-profiler

performance-profiler

SKILL.md

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
Weekly Installs
3
Repository
j0kz/mcp-agents
First Seen
Jan 26, 2026
Installed on
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