GEO Optimizer is a toolkit that checks whether AI answer services such as ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews can find, interpret, and cite a website. It helps people audit and improve a site's visibility in AI-generated answers through a command-line tool, Python library, MCP server, GitHub Action, or Astro integration.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Auriti-Labs/geo-optimizer-skillnpx agentmods add skills/auriti-labs/geo-optimizer-skill/geo-optimizerWrote 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.
[](https://agentmods.dev/skills/auriti-labs/geo-optimizer-skill/geo-optimizer)<a href="https://agentmods.dev/skills/auriti-labs/geo-optimizer-skill/geo-optimizer"><img src="https://agentmods.dev/badge/skills/auriti-labs/geo-optimizer-skill/geo-optimizer/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.
<a href="https://agentmods.dev/skills/auriti-labs/geo-optimizer-skill/geo-optimizer"><img src="https://agentmods.dev/badge/skills/auriti-labs/geo-optimizer-skill/geo-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00091 | $0.05002 |
| Opus 5.5 | $0.00036 | $0.02001 |
| Sonnet 5.5 | $0.00018 | $0.01000 |
| Haiku 4.5 | $0.00009 | $0.00500 |
Grade A, and why
geo-optimizer 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO Optimizer
Make websites visible and citable by AI search engines (ChatGPT Search, Perplexity, Claude, Google AI Overviews). Implements the GEO audit framework plus a citability engine of 47 content checks, 9 of them taken directly from the methods tested in Princeton KDD 2024 research.
Before you run anything
Preflight (stop if it fails)
Every command below is the geo executable from the geo-optimizer-skill PyPI package. It is not a separate third-party tool. Check it before the first command:
geo --version # expect: geo-optimizer, version 4.19.10 or later
If geo is missing or older, do not guess an alternative and do not continue. Ask the user to install it (Python 3.10+):
pipx install geo-optimizer-skill # or: pip install geo-optimizer-skill
pip install "geo-optimizer-skill[pdf]" # only for --format pdf (needs WeasyPrint system libraries)
pip install "geo-optimizer-skill[llm]" # only for geo citations with the OpenAI/Anthropic/Groq SDKs
pip install "geo-optimizer-skill[mcp]" # only for the geo-mcp server
Core dependencies (click, requests, beautifulsoup4, lxml, urllib3, rich) and every extra are declared in pyproject.toml.
What each command touches
Machine-readable version: capabilities.json. A test keeps it in sync with the registered commands and MCP tools.
Target below means the URL, domain or sitemap you pass, plus redirect targets and, where noted, the pages and sub-sitemaps its sitemap lists. Those can be on any public host; private and internal addresses are blocked.
Any command you give --output also writes that file.
| Command | Network | API keys | Writes to disk |
|---|---|---|---|
audit, access, diff, perception |
Target (audit --sitemap/--max-pages: also the sitemap's pages) |
None | audit --format pdf writes geo-report.pdf; --cache uses ~/.geo-cache; audit --save-history/--regression use ~/.geo-optimizer/tracking.db |
coherence, authority |
Target, including the sitemap's pages and sub-sitemaps | None | None |
fix |
Target | None | Nothing by default (preview). Files in ./geo-fixes/ only with --apply |
llms |
Target: robots.txt and common sitemap paths (unless --sitemap), the sitemap and its sub-sitemaps; every listed page with --fetch-titles; <base-url>/llms.txt with --check-drift |
None | None |
schema |
None | None | --inject edits the .html file you name, after writing <file>.bak |
monitor, track |
Target | None | ~/.geo-optimizer/tracking.db; track --report writes geo-track-report.html |
history, drift |
None | None | ~/.geo-optimizer/tracking.db |
snapshots |
None | None | ~/.geo-optimizer/snapshots.db |
logs |
None | None | None (reads the log file you name) |
citations |
The LLM or SERP API you configure (OpenAI, Anthropic, Groq, Perplexity, Gemini, DeepSeek, MiniMax, SerpBase) | Required, one of: GEO_LLM_PROVIDER + GEO_LLM_API_KEY, OPENAI_API_KEY, ANTHROPIC_API_KEY, GROQ_API_KEY, PERPLEXITY_API_KEY, GEMINI_API_KEY, DEEPSEEK_API_KEY, MINIMAX_API_KEY; SERPBASE_API_KEY for --provider serpbase |
None |
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.
- 3d ago First seen · 302 lines · 91 tokens per session scan A 28d62dde4104
geo-optimizer is a skill published in the GitHub repository Auriti-Labs/geo-optimizer-skill (1,280 stars, last pushed 2d ago), licensed MIT. It adds 91 tokens to every session and 5,002 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-11-04.
geo-optimizer compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| geo-optimizerAuriti-Labs/geo-optimizer-skill | Skill | 1.3k | 2d ago | MIT | A | 91 | Claude Code |
| content-amplifieraaron-he-zhu/aaron-marketing-skills | Skill | 3.1k | yesterday | Apache-2.0 | A | 202 | Claude Code |
| campaign-planneraaron-he-zhu/aaron-marketing-skills | Skill | 3.1k | yesterday | Apache-2.0 | A | 124 | Claude Code |
| cold-outbound-sequenceraaron-he-zhu/aaron-marketing-skills | Skill | 3.1k | yesterday | Apache-2.0 | A | 172 | Claude Code |
| inbox-placement-monitoraaron-he-zhu/aaron-marketing-skills | Skill | 3.1k | yesterday | Apache-2.0 | A | 166 | Claude Code |
| subject-line-labaaron-he-zhu/aaron-marketing-skills | Skill | 3.1k | yesterday | Apache-2.0 | A | 170 | Claude Code |
| email-sequence-designeraaron-he-zhu/aaron-marketing-skills | Skill | 3.1k | yesterday | Apache-2.0 | A | 197 | Claude Code |