lighthouse-audit
About
This skill automates Google Lighthouse audits to measure Core Web Vitals, SEO, and accessibility metrics. Developers can use it to check page performance, audit technical SEO issues, and compare optimization results. It supports batch auditing multiple URLs for monitoring and reporting.
Quick Install
Claude Code
Recommendednpx skills add guia-matthieu/clawfu-skills -a claude-code/plugin add https://github.com/guia-matthieu/clawfu-skillsgit clone https://github.com/guia-matthieu/clawfu-skills.git ~/.claude/skills/lighthouse-auditCopy and paste this command in Claude Code to install this skill
Documentation
Lighthouse Audit
Automate Google Lighthouse audits to measure and track Core Web Vitals, SEO, and accessibility - the same metrics Google uses for search ranking.
When to Use This Skill
- Performance optimization - Measure LCP, FID, CLS before and after changes
- SEO audits - Check technical SEO issues (meta tags, structured data, etc.)
- Accessibility checks - Identify a11y issues for compliance
- Client reporting - Generate professional performance reports
- Monitoring - Track scores over time across multiple pages
What Claude Does vs What You Decide
| Claude Does | You Decide |
|---|---|
| Structures analysis frameworks | Metric definitions |
| Identifies patterns in data | Business interpretation |
| Creates visualization templates | Dashboard design |
| Suggests optimization areas | Action priorities |
| Calculates statistical measures | Decision thresholds |
Dependencies
pip install click pandas jinja2
# Also requires Chrome and Lighthouse CLI
# npm install -g lighthouse
# Or use Chrome DevTools built-in Lighthouse
Commands
Single URL Audit
python scripts/main.py audit https://example.com --categories performance,seo
python scripts/main.py audit https://example.com --format html --output report.html
Batch Audit
python scripts/main.py batch urls.txt --output results/
python scripts/main.py batch urls.txt --categories performance --format csv
Compare Before/After
python scripts/main.py compare https://example.com --baseline scores.json
python scripts/main.py compare https://example.com --baseline-url https://staging.example.com
Monitor Over Time
python scripts/main.py history https://example.com --days 30
python scripts/main.py history https://example.com --plot
Examples
Example 1: Full Site Performance Audit
# Create URL list
cat > urls.txt << EOF
https://example.com/
https://example.com/pricing
https://example.com/features
https://example.com/blog
EOF
# Run batch audit
python scripts/main.py batch urls.txt --categories performance,seo,accessibility
# Output: results/audit_2024-01-15/
# ├── example.com_.json
# ├── example.com_pricing.json
# ├── example.com_features.json
# ├── example.com_blog.json
# └── summary.csv
Example 2: Before/After Comparison
# Save baseline
python scripts/main.py audit https://example.com --output baseline.json
# Make optimizations...
# Compare
python scripts/main.py compare https://example.com --baseline baseline.json
# Output:
# Core Web Vitals Comparison
# ─────────────────────────────
# Metric Before After Change
# LCP 3.2s 1.8s -44% ✓
# FID 120ms 45ms -63% ✓
# CLS 0.25 0.08 -68% ✓
# Performance 52 89 +37 pts
Example 3: Generate Client Report
# Full audit with HTML report
python scripts/main.py audit https://client-site.com \
--format html \
--output client-report.html \
--include-screenshots
# Output: Professional HTML report with:
# - Executive summary
# - Core Web Vitals scores
# - Screenshots of issues
# - Prioritized recommendations
Audit Categories
| Category | Checks | Impact |
|---|---|---|
performance | LCP, FID, CLS, TTFB, Speed Index | Search ranking |
seo | Meta tags, headings, links, mobile | Search visibility |
accessibility | WCAG compliance, contrast, labels | Compliance |
best-practices | HTTPS, security, modern APIs | Trust |
pwa | Service worker, manifest, offline | App-like experience |
Core Web Vitals Thresholds
| Metric | Good | Needs Improvement | Poor |
|---|---|---|---|
| LCP (Largest Contentful Paint) | ≤2.5s | 2.5s-4.0s | >4.0s |
| FID (First Input Delay) | ≤100ms | 100ms-300ms | >300ms |
| CLS (Cumulative Layout Shift) | ≤0.1 | 0.1-0.25 | >0.25 |
| INP (Interaction to Next Paint) | ≤200ms | 200ms-500ms | >500ms |
Output Formats
| Format | Use Case | Content |
|---|---|---|
json | Automation, storage | Full raw data |
csv | Spreadsheets, analysis | Summary scores |
html | Client reports | Visual report |
md | Documentation | Markdown summary |
Skill Boundaries
What This Skill Does Well
- Structuring data analysis
- Identifying patterns and trends
- Creating visualization frameworks
- Calculating statistical measures
What This Skill Cannot Do
- Access your actual data
- Replace statistical expertise
- Make business decisions
- Guarantee prediction accuracy
Related Skills
- schema-markup - Fix structured data issues
- image-batch - Optimize images for LCP
- link-checker - Find broken links
Skill Metadata
- Mode: centaur
category: seo-tools
subcategory: performance
dependencies: [lighthouse, click, pandas]
difficulty: beginner
time_saved: 3+ hours/week
GitHub Repository
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