/lighthouse-audit

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](../schema-markup/) - Fix structured data issues
• [image-batch](../../automation/image-batch/) - Optimize images for LCP
• [link-checker](../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