geo-audit
Full website GEO+SEO audit with parallel subagent delegation. Orchestrates a comprehensive Generative Engine Optimization audit across AI citability, platform analysis, technical infrastructure, content quality, and schema markup. Produces a composite GEO Score (0-100) with prioritized action plan.
By zubair-trabzada · 640 installs
npx skills add zubair-trabzada/geo-seo-claude --skill geo-audit
Source repository · Upstream listing
GEO Audit Orchestration Skill
Purpose
This skill performs a comprehensive Generative Engine Optimization (GEO) audit of any website. GEO is the practice of optimizing web content so that AI systems (ChatGPT, Claude, Perplexity, Gemini, etc.) can discover, understand, cite, and recommend it. This audit measures how well a site performs across all GEO dimensions and produces an actionable improvement plan.
Key Insight
Traditional SEO optimizes for search engine rankings. GEO optimizes for AI citation and recommendation. Sites that score high on GEO metrics see 30 115% more visibility in AI generated responses (Georgia Tech / Princeton / IIT Delhi 2024 study). The two disciplines overlap but have distinct requirements.
Audit Workflow
Phase 1: Discovery and Reconnaissance
Step 1: Fetch Homepage and Detect Business Type
1. Use WebFetch to retrieve the homepage at the provided URL.
2. Extract the following signals:
Page title, meta description, H1 heading
Navigation menu items (reveals site structure)
Footer content (reveals business info, location, legal pages)
Schema.org markup on homepage (Organization, LocalBusiness, etc.)
Pricing page link (SaaS indicator)
Product listing patterns (E commerce indicator)
Blog/resource section (Publisher indicator)
Service pages (Agency indicator)
Address/phone/Google Maps embed (Local business indicator)
3. Classify the business type using these patterns:
Business Type Detection Signals
SaaS Pricing page, "Sign up" / "Free trial" CTAs, app.domain.com subdomain, feature comparison tables, integration pages
Local Business Physical address on homepage, Google Maps embed, "Near me" content, LocalBusiness schema, service area pages
E commerce Product listings, shopping cart, product schema, category pages, price displays, "Add to cart" buttons
Publisher Blog heavy navigation, article schema, author pages, date based archives, RSS feeds, high content volume
Agency/Services Case studies, portfolio, "Our Work" section, team page, client logos, service descriptions
Hybrid Combination of above signals classify by dominant pattern
Step 2: Crawl Sitemap and Internal Links
1. Attempt to fetch /sitemap.xml and /sitemap index.xml .
2. If sitemap exists, extract up to 50 unique page URLs prioritized by:
Homepage (always include)
Top level navigation pages
High value pages (pricing, about, contact, key service/product pages)
Blog posts (sample 5 10 most recent)
Category/landing pages
3. If no sitemap exists, crawl internal links from the homepage:
Extract all <a href links pointing to the same domain
Follow up to 2 levels deep
Prioritize pages linked from main navigation
4. Respect robots.txt directives do not fetch disallowed paths.
5. Enforce a maximum of 50 pages and a 30 second timeout per fetch.
Step 3: Collect Page Level Data
For each page in the crawl set, record:
URL, title, meta description, canonical URL
H1 H6 heading structure
Word count of main content
Schema.org types present
Internal/external link counts
Images with/without alt text
Open Graph and Twitter Card meta tags
Response status code
Whether the page has structured data
Phase 2: Parallel Subagent Delegation
Delegate analysis to 5 specialized subagents. Each subagent operates on the collected page data and produces a category score (0 100) plus findings.
Subagent 1: AI Visibility Analysis (geo ai visibility)
Analyze content blocks for quotability by AI systems (citability scoring)
Check AI crawler access via robots.txt and llms.txt presence
Scan brand presence across YouTube, Reddit, Wikipedia, LinkedIn
Score brand authority signals that AI models use for entity recognition
Subagent 2: Platform Optimization (geo platform analysis)
Assess readiness for Google AI Overviews, ChatGPT, Perplexity, Gemini, Bing Copilot
Check platform specific ranking factors and optimization opportunities
Subagent 3: Technical GEO Infrastructure (geo technical)
Analyze robots.txt for AI crawler access
Verify meta tags, headers, and technical accessibility for AI systems
Check page speed, server side rendering, and Core Web Vitals
Assess security headers and mobile optimization
Subagent 4: Content E E A T Quality (geo content)
Evaluate Experience, Expertise, Authoritativeness, Trustworthiness signals
Check author bios, credentials, source citations
Assess content freshness, depth, and originality
Verify "About" page quality and team credentials
Subagent 5: Schema & Structured Data (geo schema)
Validate all schema.org markup
Check for GEO critical schema types (FAQ, HowTo, Organization, Product, Article)
Assess schema completeness and accuracy
Identify missing schema opportunities
Phase 3: Score Aggregation and Report Generation
Composite GEO Score Calculation
The overall GEO Score (0 100) is a weighted average of six category scores:
Category Weight What It Measures
AI Citability 25% How quotable/extractable content is for AI systems
Brand Authority 20% Third party mentions, entity recognition signals
Content E E A T 20% Experience, Expertise, Authoritativeness, Trustworthiness
Technical GEO 15% AI crawler access, llms.txt, rendering, speed
Schema & Structured Data 10% Schema.org markup quality and completeness
Platform Optimization 10% Presence on platforms AI models train on and cite
Formula:
Score Interpretation
Score Range Rating Interpretation
90 100 Excellent Top tier GEO optimization; site is highly likely to be cited by AI
75 89 Good Strong GEO foundation with room for improvement
60 74 Fair Moderate GEO presence; significant optimization opportunities exist
40 59 Poor Weak GEO signals; AI systems may struggle to cite or recommend
0 39 Critical Minimal GEO optimization; site is largely invisible to AI systems
Issue Severity Classification
Every issue found during the audit is classified by severity:
Critical (Fix Immediately)
All AI crawlers blocked in robots.txt
No indexable content (JavaScript rendered only with no SSR)
Domain level noindex directive
Site returns 5xx errors on key pages
Complete absence of any structured data
Brand not recognized as an entity by any AI system
High (Fix Within 1 Week)
Key AI crawlers (GPTBot, ClaudeBot, PerplexityBot) blocked
No llms.txt file present
Zero question answering content blocks on key pages
Missing Organization or LocalBusiness schema
No author attribution on content pages
All content behind login/paywall with no preview
Medium (Fix Within 1 Month)
Partial AI crawler blocking (some allowed, some blocked)
llms.txt exists but is incomplete or malformed
Content blocks average under 50 citability score
Missing FAQ schema on pages with FAQ content
Thin author bios without credentials
No Wikipedia or Reddit brand presence
Low (Optimize When Possible)
Minor schema validation errors
Some images missing alt text
Content freshness issues on non critical pages
Missing Open Graph tags
Suboptimal heading hierarchy on some pages
LinkedIn company page exists but is incomplete
Output Format
Generate a file called GEO AUDIT REPORT.md with the following structure:
Quality Gates
Page Limit: Never crawl more than 50 pages per audit. Prioritize high value pages.
Timeout: 30 second maximum per page fetch. Skip pages that exceed this.
Robots.txt: Always check and respect robots.txt before crawling. Note any AI specific directives.
Rate Limiting: Wait at least 1 second between page fetches to avoid overloading the server.
Error Handling: Log failed fetches but continue the audit. Report fetch failures in the appendix.
Content Type: Only analyze HTML pages. Skip PDFs, images, and other binary content.
Deduplication: Canonicalize URLs before crawling. Skip duplicate content (e.g., HTTP vs HTTPS, www vs non www, trailing slashes).
Business Type Specific Audit Adjustments
SaaS Sites
Extra weight on: Feature comparison tables (high citability), integration pages, documentation quality
Check for: API documentation structure, changelog pages, knowledge base organization
Key schema: SoftwareApplication, FAQPage, HowTo
Local Businesses
Extra weight on: NAP consistency, Google Business Profile signals, local schema
Check for: Service area pages, location specific content, review markup
Key schema: LocalBusiness, GeoCoordinates, OpeningHoursSpecification
E commerce Sites
Extra weight on: Product descriptions (citability), comparison content, buying guides
Check for: Product schema completeness, review aggregation, FAQ sections on product pages
Key schema: Product, AggregateRating, Offer, BreadcrumbList
Publishers
Extra weight on: Article quality, author credentials, source citation practices
Check for: Article schema, author pages, publication date freshness, original research
Key schema: Article, NewsArticle, Person (author), ClaimReview
Agency/Services
Extra weight on: Case studies (citability), expertise demonstration, thought leadership
Check for: Portfolio schema, team credentials, industry specific expertise signals
Key schema: Organization, Service, Person (team), Review