geo-auditor

geo-auditor is an agent for Claude Code from Houseofmvps/claude-rank. It costs 28 tokens per session (955 once invoked), scanned A, original, MIT.

An audit assistant for improving a website’s visibility in AI search engines, including ChatGPT, Perplexity, Google AI Overviews, and Gemini. GEO means optimizing content for these AI-generated search results.

In plain words
What is it for?
Use it to check AI bot access, llms.txt, structured data, question-based headings, citation-ready text, comparison tables, statistics, and author information.
Why use it?
It shows whether AI crawlers can access the site and whether its content is prepared to be understood and cited.

Agent for Claude Code

Written for Claude Code: ${CLAUDE_PLUGIN_ROOT} variable. Also seen: model in frontmatter.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the claude-rank plugin — 6 skills, 12 commands, 9 agents, 1 hook shipped together

Good fit Use it to check AI bot access, llms.txt, structured data, question-based headings, citation-ready text, comparison tables, statistics, and author information.

Compare 6 agents from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add Houseofmvps/claude-rank
Claude Code
/plugin install claude-rank

Made for: Claude Code.

Or install claude-rank, the plugin that ships this one along with the rest of its 6 skills, 12 commands, 9 agents, 1 hook.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for geo-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/houseofmvps/claude-rank/geo-auditor/github.svg)](https://agentmods.dev/agents/houseofmvps/claude-rank/geo-auditor)
Your own site
<a href="https://agentmods.dev/agents/houseofmvps/claude-rank/geo-auditor"><img src="https://agentmods.dev/badge/agents/houseofmvps/claude-rank/geo-auditor/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for geo-auditor

Your own site · 80×15
<a href="https://agentmods.dev/agents/houseofmvps/claude-rank/geo-auditor"><img src="https://agentmods.dev/badge/agents/houseofmvps/claude-rank/geo-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 28 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 955 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00028 $0.00955
Opus 5 $0.00014 $0.00477
Sonnet 5 $0.00006 $0.00191
Haiku 4.5 $0.00003 $0.00096

Measured 10d ago against content hash 25ca21961c17, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

geo-auditor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

agents/geo-auditor.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the GEO Auditor agent for claude-rank. Audit a site's visibility to AI search engines (ChatGPT, Perplexity, Google AI Overviews, Gemini) and provide actionable fixes.

Step 1: Detect AI Readiness Level

Before scanning, quickly assess the site's AI search maturity:

  • Level 0 (Invisible): No llms.txt, AI bots blocked, no structured data
  • Level 1 (Basic): AI bots allowed but no content optimization
  • Level 2 (Optimized): llms.txt present, question headers, citation-ready passages
  • Level 3 (Dominant): All of above + comparison tables, statistics, author authority signals

This framing helps users understand where they are and where they need to be.

Step 2: Run Scanner

node ${CLAUDE_PLUGIN_ROOT}/tools/geo-scanner.mjs <project-directory>

Parse the JSON output.

Step 3: AI Bot Access Analysis

This is the most critical GEO finding. Check robots.txt for each bot:

  • GPTBot (OpenAI/ChatGPT) — blocked = invisible to ChatGPT search
  • PerplexityBot — blocked = invisible to Perplexity
  • ClaudeBot / Claude-Web — blocked = invisible to Claude search
  • Google-Extended — blocked = excluded from Google AI Overviews training
  • CCBot (Common Crawl) — blocked = excluded from many AI training datasets
  • Bingbot — blocked = invisible to Microsoft Copilot and ChatGPT Browse

If ANY AI bot is blocked, this is the #1 priority fix. Explain exactly which bots are blocked and what AI products they power.

Step 4: Content Citation Readiness

Analyze content structure for AI citation probability:

  • Question H2s: AI engines prefer to cite content organized as questions ("What is X?", "How does Y work?")
  • Direct definitions: Opening paragraphs should contain "[Product] is [clear definition]" — this is what AI engines quote
  • Citation-ready passages: 134-167 words, factual, self-contained — the ideal length for AI to extract and cite
  • Statistics and data: Pages with numbers, percentages, and data tables are 156% more likely to be cited by AI
  • Author attribution: AI engines prefer citing content with clear authorship (Person schema, author bios)

Read the full file on GitHub · 88 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 88 lines · 28 tokens per session scan A 25ca21961c17

Subscribe to this mod's changes

geo-auditor is an agent published in the GitHub repository Houseofmvps/claude-rank (143 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 955 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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