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performance-profiling

Performance profiling principles. Measurement, analysis, and optimization techniques.

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vudovn/ag-kit
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2026년 7월 18일 12:54
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SKILL.md
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name
performance-profiling
description
Performance profiling principles. Measurement, analysis, and optimization techniques.
when_to_use
When diagnosing performance issues, running Lighthouse audits, analyzing bundle size, or optimizing Core Web Vitals.
allowed-tools
Read, Glob, Grep, Bash
version
1.0.0
# Performance Profiling > Measure, analyze, optimize - in that order. ## 🔧 Runtime Scripts **Execute these for automated profiling:** | Script | Purpose | Usage | |--------|---------|-------| | `scripts/lighthouse_audit.py` | Lighthouse performance audit | `python scripts/lighthouse_audit.py https://example.com` | --- ## 1. Core Web Vitals ### Targets | Metric | Good | Poor | Measures | |--------|------|------|----------| | **LCP** | < 2.5s | > 4.0s | Loading | | **INP** | < 200ms | > 500ms | Interactivity | | **CLS** | < 0.1 | > 0.25 | Stability | ### When to Measure | Stage | Tool | |-------|------| | Development | Local Lighthouse | | CI/CD | Lighthouse CI | | Production | RUM (Real User Monitoring) | --- ## 2. Profiling Workflow ### The 4-Step Process ``` 1. BASELINE → Measure current state 2. IDENTIFY → Find the bottleneck 3. FIX → Make targeted change 4. VALIDATE → Confirm improvement ``` ### Profiling Tool Selection | Problem | Tool | |---------|------| | Page load | Lighthouse | | Bundle size | Bundle analyzer | | Runtime | DevTools Performance | | Memory | DevTools Memory | | Network | DevTools Network | --- ## 3. Bundle Analysis ### What to Look For | Issue | Indicator | |-------|-----------| | Large dependencies | Top of bundle | | Duplicate code | Multiple chunks | | Unused code | Low coverage | | Missing splits | Single large chunk | ### Optimization Actions | Finding | Action | |---------|--------| | Big library | Import specific modules | | Duplicate deps | Dedupe, update versions | | Route in main | Code split | | Unused exports | Tree shake | --- ## 4. Runtime Profiling ### Performance Tab Analysis | Pattern | Meaning | |---------|---------| | Long tasks (>50ms) | UI blocking | | Many small tasks | Possible batching opportunity | | Layout/paint | Rendering bottleneck | | Script | JavaScript execution | ### Memory Tab Analysis | Pattern | Meaning | |---------|---------| | Growing heap | Possible leak | | Large retained | Check references | | Detached DOM | Not cleaned up | --- ## 5. Common Bottlenecks ### By Symptom | Symptom | Likely Cause | |---------|--------------| | Slow initial load | Large JS, render blocking | | Slow interactions | Heavy event handlers | | Jank during scroll | Layout thrashing | | Growing memory | Leaks, retained refs | --- ## 6. Quick Win Priorities | Priority | Action | Impact | |----------|--------|--------| | 1 | Enable compression | High | | 2 | Lazy load images | High | | 3 | Code split routes | High | | 4 | Cache static assets | Medium | | 5 | Optimize images | Medium | --- ## 7. Anti-Patterns | ❌ Don't | ✅ Do | |----------|-------| | Guess at problems | Profile first | | Micro-optimize | Fix biggest issue | | Optimize early | Optimize when needed | | Ignore real users | Use RUM data | --- > **Remember:** The fastest code is code that doesn't run. Remove before optimizing.
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