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