lighthouse-audit
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
What this skill does
# 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 ```bash 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 ```bash 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 ```bash python scripts/main.py batch urls.txt --output results/ python scripts/main.py batch urls.txt --categories performance --format csv ``` ### Compare Before/After ```bash 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 ```bash 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 ```bash # 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 ```bash # 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 ```bash # 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 ```yaml category: seo-tools subcategory: performance dependencies: [lighthouse, click, pandas] difficulty: beginner time_saved: 3+ hours/week ```
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