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Performance Profiling

A systematic approach to finding and fixing performance bottlenecks without guessing. You get a clear four-step workflow (baseline, identify, fix, validate), concrete Core Web Vitals targets, and tool recommendations mapped to specific problems. The included Lighthouse audit script handles automated profiling, while lookup tables help you interpret DevTools output and prioritize fixes. What I like here is the anti-patterns section that pushes back on premature optimization and reminds you to profile before you optimize. Best used when you're staring at slow page loads or janky interactions and need a methodical way to diagnose what's actually wrong rather than throwing random performance tricks at the wall.

skills.sh installs
349
GitHub stars
33.2K
last updated
Aug 21, 2026

Install

$ npx -y skills add davila7/claude-code-templates --skill performance-profiling --agent claude-code

Installs into .claude/skills of the current project.

Files

Performance Profiling

Measure, analyze, optimize - in that order.

πŸ”§ Runtime Scripts

Execute these for automated profiling:

ScriptPurposeUsage
scripts/lighthouse_audit.pyLighthouse performance auditpython scripts/lighthouse_audit.py https://example.com

1. Core Web Vitals

Targets

MetricGoodPoorMeasures
LCP< 2.5s> 4.0sLoading
INP< 200ms> 500msInteractivity
CLS< 0.1> 0.25Stability

When to Measure

StageTool
DevelopmentLocal Lighthouse
CI/CDLighthouse CI
ProductionRUM (Real User Monitoring)

2. Profiling Workflow

The 4-Step Process

1. BASELINE β†’ Measure current state
2. IDENTIFY β†’ Find the bottleneck
3. FIX β†’ Make targeted change
4. VALIDATE β†’ Confirm improvement

Profiling Tool Selection

ProblemTool
Page loadLighthouse
Bundle sizeBundle analyzer
RuntimeDevTools Performance
MemoryDevTools Memory
NetworkDevTools Network

3. Bundle Analysis

What to Look For

Sponsors

Details

Repository
github.com/davila7/claude-code-templates
Category
Debugging
First seen
Jun 3, 2026

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