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Agent skill

Geo Audit

by sickn33 in sickn33/agentic-awesome-skills

Full website GEO+SEO audit with parallel subagent delegation.

MITAuto-check: notesMarketing & SEO

Install Geo Audit

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill geo-audit -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills geo-audit --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/geo-audit .claude/skills/geo-audit && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
geo-audit
GitHub stars
47k
Used in
1 other repo
Token cost
~3.4k tokens
SKILL.md length
1,318 words
Files
1
Skills in repo
1,497
Repo updated
First seen
Licence
MIT

At a glance

Full website GEO+SEO audit with parallel subagent delegation.

  • Works in 3 steps: Discovery and Reconnaissance → Parallel Subagent Delegation → Score Aggregation and Report Generation
  • Tasks that involve Subagents
  • SKILL.md covers Purpose, Key Insight, Audit Workflow and Issue Severity Classification, plus 5 more sections
  • Calls curl

What it does

Geo Audit is an agent skill from sickn33/agentic-awesome-skills. Full website GEO+SEO audit with parallel subagent delegation.

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Docs-only; upstream helper scripts and templates are not bundled. Site audits need network access to the target site; PDF reports need pandoc and headless…

It sits in Marketing & SEO, covering Subagents, AI search optimization and SEO audit. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Tasks that involve Subagents
  • Tasks that involve AI search optimization
  • Tasks that involve SEO audit

Example prompts

  • “/geo-audit”

Requirements

  • Compatibility (from SKILL.md): Docs-only; upstream helper scripts and templates are not bundled. Site audits need network access to the target site; PDF reports need pandoc and headless Chrome.
  • Pre-approved tools (allowed-tools): Read, Grep, Glob, Bash, WebFetch, Write

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Discovery and Reconnaissance
  2. Parallel Subagent Delegation
  3. Score Aggregation and Report Generation

What it can do on your machine

Read from SKILL.md and the folder at commit b84d35a. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Grep
    • Glob
    • Bash
    • WebFetch
    • Write

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • curl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Docs-only; upstream helper scripts and templates are not bundled. Site audits need network access to the target site; PDF reports need pandoc and headless Chrome.

    From compatibility in the SKILL.md frontmatter.

Context cost

Geo Audit loads about 3.4k tokens when it runs. Until then it costs about 18 tokens; SKILL.md has 1,318 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~18
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Grep, Glob, Bash, WebFetch, Write

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sickn33/agentic-awesome-skills at commit b84d35a, republished under its MIT licence (© sickn33). 1,318 words, ~3,377 tokens.

Download SKILL.mdSave it as .claude/skills/geo-audit/SKILL.md (or your agent's skills folder).
name
geo-audit
description
Full website GEO+SEO audit with parallel subagent delegation.
allowed-tools
Read, Grep, Glob, Bash, WebFetch, Write
compatibility
Docs-only; upstream helper scripts and templates are not bundled. Site audits need network access to the target site; PDF reports need pandoc and headless Chrome.
category
seo
risk
safe
source
https://github.com/zubair-trabzada/geo-seo-claude
source_repo
zubair-trabzada/geo-seo-claude
source_type
community
date_added
2026-09-20
license
MIT
license_source
https://github.com/zubair-trabzada/geo-seo-claude/blob/main/LICENSE

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 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 (invoke skill geo-citability)

  • 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 (invoke skill geo-platform-optimizer)

  • Assess readiness for Google AI Overviews, ChatGPT, Perplexity, Gemini, Bing Copilot
  • Check platform-specific ranking factors and optimization opportunities

Subagent 3: Technical GEO Infrastructure (invoke 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

Subagent 4: Content E-E-A-T Quality (invoke 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

Subagent 5: Schema & Structured Data (invoke 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
Show full SKILL.md (530 more words)Show less

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:

markdown
# 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

When to Use

  • You need a Generative Engine Optimization task for a website: audit, citability, crawlers, schema, llms.txt, content, platform tuning, or client reporting.
  • Run read-only analysis first; propose site changes before making any.

Limitations

  • Audits are read-only analysis; never publish, deploy, or modify the target site without explicit approval.
  • Scores and citation likelihoods are heuristics, not guarantees from AI search platforms.
  • Docs-only import: upstream scripts, agents, hooks, and schema templates are not bundled.
Example
bash
curl -s https://example.com/robots.txt
curl -s https://example.com/llms.txt

Adapted from zubair-trabzada/geo-seo-claude (MIT); frontmatter, When to Use/Limitations, and safety boundaries added for upstream compliance. Docs-only import: upstream runtime helpers not bundled.

© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/geo-audit of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit b84d35a

Used in 1 other repository

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Geo Audit next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Geo Audit compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Geo Audit this skillsickn33/agentic-awesome-skills47k1 repos~3.4kAutomated safety check: NotesMIT
SEO AuditAgriciDaniel/codex-seo7992 repos~1.9kAutomated safety check: PassMIT
Geo Auditzubair-trabzada/geo-seo-claude11k—~3.1kAutomated safety check: NotesMIT
Blog AuditInfrasity-Labs/dev-gtm-claude-skills136—~1.8kAutomated safety check: PassMIT
GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude11k—~2.8kAutomated safety check: NotesMIT
GEO Monthly Delta Reportzubair-trabzada/geo-seo-claude11k—~2.4kAutomated safety check: NotesMIT

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Categories

Questions about Geo Audit

What does Geo Audit do?

Full website GEO+SEO audit with parallel subagent delegation. Geo Audit is an agent skill from sickn33/agentic-awesome-skills. Full website GEO+SEO audit with parallel subagent delegation.

When should I use Geo Audit?

Geo Audit fits situations like: tasks that involve Subagents; tasks that involve AI search optimization; tasks that involve SEO audit.

How do I install Geo Audit in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill geo-audit -a claude-code`. Or copy the skill folder (skills/geo-audit in sickn33/agentic-awesome-skills) into .claude/skills/geo-audit in your project. Claude Code loads it when a task matches its description.

How do I install Geo Audit in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill geo-audit -a codex`. Or copy the skill folder (skills/geo-audit in sickn33/agentic-awesome-skills) into .agents/skills/geo-audit in your project. Codex loads it when a task matches its description.

Can I use Geo Audit in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill geo-audit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/geo-audit, .gemini/skills/geo-audit, .github/skills/geo-audit and .opencode/skills/geo-audit in your project.

What does Geo Audit need to run?

Going by SKILL.md and its folder, Geo Audit needs the command-line tools its instructions call (curl). Its frontmatter pre-approves these tools: Read, Grep, Glob, Bash, WebFetch, Write. Compatibility (from SKILL.md): Docs-only; upstream helper scripts and templates are not bundled. Site audits need network access to the target site; PDF reports need pandoc and headless Chrome..

Does Geo Audit access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Geo Audit safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Geo Audit use?

Geo Audit is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Geo Audit use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Geo Audit?

Skills that share tags, products or a category with Geo Audit: SEO Audit (AgriciDaniel/codex-seo, 799 stars), Geo Audit (zubair-trabzada/geo-seo-claude, 11k stars), Blog Audit (Infrasity-Labs/dev-gtm-claude-skills, 136 stars) and GEO-First SEO Audit Tool (zubair-trabzada/geo-seo-claude, 11k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Geo Audit?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,405 GitHub stars. The repository holds 1,497 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.