name: lighthouse-audit
description: "Run automated Lighthouse audits for Core Web Vitals and SEO. Use when: checking page performance; auditing SEO technical issues; monitoring Core Web Vitals; comparing before/after optimization; batch auditing multiple URLs"
license: MIT
metadata:
author: ClawFu
version: 1.0.0
mcp-server: "@clawfu/mcp-skills"
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
category: seo-tools
subcategory: performance
dependencies: [lighthouse, click, pandas]
difficulty: beginner
time_saved: 3+ hours/week