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geo-audit

Full website GEO+SEO audit with parallel agents first and skills fallback. 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.

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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 TypeDetection Signals
SaaSPricing page, "Sign up" / "Free trial" CTAs, app.domain.com subdomain, feature comparison tables, integration pages
Local BusinessPhysical address on homepage, Google Maps embed, "Near me" content, LocalBusiness schema, service area pages
E-commerceProduct listings, shopping cart, product schema, category pages, price displays, "Add to cart" buttons
PublisherBlog-heavy navigation, article schema, author pages, date-based archives, RSS feeds, high content volume
Agency/ServicesCase studies, portfolio, "Our Work" section, team page, client logos, service descriptions
HybridCombination 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 Agents First, Skills Fallback

Run 5 specialized analysis tracks. Each track operates on the collected page data and produces a category score (0-100) plus findings.

Prefer parallel agent delegation when the matching agents are available. This preserves the fastest full-audit path by running the five tracks concurrently. If any agent is missing or unavailable, run that track directly through the listed skills and rubrics instead. Do not fail a plugin-only audit because external TOML agents are missing.

The output contract is identical in both modes: each track must return a score from 0-100, findings grouped by severity, and recommendations suitable for the final GEO-AUDIT-REPORT.md.

Track 1: AI Visibility Analysis

  • Preferred agent: geo-ai-visibility
  • Fallback skills: geo-citability, geo-crawlers, geo-llmstxt, geo-brand-mentions
  • 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

Track 2: Platform Optimization

  • Preferred agent: geo-platform-analysis
  • Fallback skill: geo-platform-optimizer
  • Assess readiness for Google AI Overviews, ChatGPT, Perplexity, Gemini, Bing Copilot
  • Check platform-specific ranking factors and optimization opportunities

Track 3: Technical GEO Infrastructure

  • Preferred agent: geo-technical
  • Fallback skill: 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

Track 4: Content E-E-A-T Quality

  • Preferred agent: geo-content
  • Fallback skill: 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

Track 5: Schema & Structured Data

  • Preferred agent: geo-schema
  • Fallback skill: 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:

CategoryWeightWhat It Measures
AI Citability25%How quotable/extractable content is for AI systems
Brand Authority20%Third-party mentions, entity recognition signals
Content E-E-A-T20%Experience, Expertise, Authoritativeness, Trustworthiness
Technical GEO15%AI crawler access, llms.txt, rendering, speed
Schema & Structured Data10%Schema.org markup quality and completeness
Platform Optimization10%Presence on platforms AI models train on and cite

Formula:

GEO_Score = (Citability * 0.25) + (Brand * 0.20) + (EEAT * 0.20) + (Technical * 0.15) + (Schema * 0.10) + (Platform * 0.10)

Score Interpretation

Score RangeRatingInterpretation
90-100ExcellentTop-tier GEO optimization; site is highly likely to be cited by AI
75-89GoodStrong GEO foundation with room for improvement
60-74FairModerate GEO presence; significant optimization opportunities exist
40-59PoorWeak GEO signals; AI systems may struggle to cite or recommend
0-39CriticalMinimal 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:

# GEO Audit Report: [Site Name]

**Audit Date:** [Date]
**URL:** [URL]
**Business Type:** [Detected Type]
**Pages Analyzed:** [Count]

---

## Executive Summary

**Overall GEO Score: [X]/100 ([Rating])**

[2-3 sentence summary of the site's GEO health, biggest strengths, and most critical gaps.]

### Score Breakdown

| Category | Score | Weight | Weighted Score |
|---|---|---|---|
| AI Citability | [X]/100 | 25% | [X] |
| Brand Authority | [X]/100 | 20% | [X] |
| Content E-E-A-T | [X]/100 | 20% | [X] |
| Technical GEO | [X]/100 | 15% | [X] |
| Schema & Structured Data | [X]/100 | 10% | [X] |
| Platform Optimization | [X]/100 | 10% | [X] |
| **Overall GEO Score** | | | **[X]/100** |

---

## Critical Issues (Fix Immediately)

[List each critical issue with specific page URLs and recommended fix]

## High Priority Issues

[List each high-priority issue with details]

## Medium Priority Issues

[List each medium-priority issue]

## Low Priority Issues

[List each low-priority issue]

---

## Category Deep Dives

### AI Citability ([X]/100)
[Detailed findings, examples of good/bad passages, rewrite suggestions]

### Brand Authority ([X]/100)
[Platform presence map, mention volume, sentiment]

### Content E-E-A-T ([X]/100)
[Author quality, source citations, freshness, depth]

### Technical GEO ([X]/100)
[Crawler access, llms.txt, rendering, headers]

### Schema & Structured Data ([X]/100)
[Schema types found, validation results, missing opportunities]

### Platform Optimization ([X]/100)
[Presence on YouTube, Reddit, Wikipedia, etc.]

---

## Quick Wins (Implement This Week)

1. [Specific, actionable quick win with expected impact]
2. [Another quick win]
3. [Another quick win]
4. [Another quick win]
5. [Another quick win]

## 30-Day Action Plan

### Week 1: [Theme]
- [ ] Action item 1
- [ ] Action item 2

### Week 2: [Theme]
- [ ] Action item 1
- [ ] Action item 2

### Week 3: [Theme]
- [ ] Action item 1
- [ ] Action item 2

### Week 4: [Theme]
- [ ] Action item 1
- [ ] Action item 2

---

## Appendix: Pages Analyzed

| URL | Title | GEO Issues |
|---|---|---|
| [url] | [title] | [issue count] |

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

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