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performance-profiling

@xenitV1/claude-code-maestro
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Performance profiling techniques for web applications including Core Web Vitals, bundle analysis, and runtime profiling.

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SKILL.md

name performance-profiling
description Performance profiling principles. Measurement, analysis, and optimization techniques.

Performance Profiling

Measure, analyze, optimize - in that order.


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.