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GitHub Skill

performance-profiling

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

whodaniel☆ 2 Repository stars0 Repository forks

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

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Skill instructions

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.

Examples

Read the usage examples in the source repository.

View source ↗

Source history

Indexed on
2026-01-20
Index updated
2026-01-26
Branch
main

Index and sync dates describe this directory. View the source repository for code history.

GitHub ↗

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