Agent skill
performance-profiler
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.
Install this agent skill to your Project
npx add-skill https://github.com/j0KZ/mcp-agents/tree/main/starter-kit/template/.claude/skills/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
- CPU Profiling: Identify performance hotspots
- Memory Analysis: Detect leaks and optimize usage
- Bundle Optimization: Reduce JavaScript payload
- Network Performance: API and asset loading
- 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
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