Performance Profiling
This is your systematic approach to finding and fixing performance problems. It walks you through the measure-identify-fix-validate cycle with clear tool recommendations for each scenario: Lighthouse for page loads, bundle analyzer for bloat, DevTools Performance for runtime issues. The Core Web Vitals targets and bottleneck symptom table are solid quick references. What I appreciate here is the anti-pattern section reminding you to profile before optimizing, because guessing wastes more time than the performance gains you're chasing. Includes a Lighthouse audit script you can run directly.
- skills.sh installs
- 118
- GitHub stars
- 7.6K
- last updated
- Jun 3, 2026
Install
$ npx -y skills add vudovn/antigravity-kit --skill performance-profiling --agent claude-codeInstalls into .claude/skills of the current project.
Files
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
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- Repository
- github.com/vudovn/antigravity-kit
- Category
- Debugging
- First seen
- Jun 3, 2026
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