GitHub GEO Skills: Why a Free Audit Isn't Real Data

Your developer finds a free GitHub GEO skill, runs it in an afternoon, and hands you a polished audit. No invoice. No agency. No SerpStat subscription.

It looks like the real thing — until someone asks: "Where did these keyword rankings come from?"

That's the gap. A GitHub SEO GEO skill can read your website's public pages and check basic technical files. What it usually cannot do — unless someone connects paid tools — is pull your actual data from Google Search Console (where Google shows your real rankings and clicks), SerpStat, Ahrefs, or Semrush. The report still reads like a professional SEO audit. One part may be verified. The keyword part may be filler dressed up to look like Semrush.

What is a GitHub GEO skill? (Plain English)

GitHub is where developers share free code and toolkits. A GEO skill is one of those toolkits — written instructions that tell an AI assistant how to audit a website for both classic SEO (Google search visibility) and GEO (getting your site ready so ChatGPT, Perplexity, and Gemini can find and recommend you).

Install it, point it at your domain, and it produces a report: page checks, issue lists, keyword tables, competitor notes. Many advertise "zero API keys required" — meaning no paid logins needed to run it.

In practice, that means:

• It can read what's publicly visible on your site — HTML, page titles, your robots.txt file (a simple instruction file that tells bots what they may read)
• It may run basic speed or crawl tests on your pages
• It does not, by default, log into Google Search Console, SerpStat, or any keyword database

Think of it as a free recipe, not a data subscription. Helpful for a quick technical look. Not a replacement for SerpStat or a full SEO platform — unless your team wires those up separately (most don't).

How can a report show keyword data with no database?

Your SEO lead probably already knows the rule: no connected data source, no real ranking data.

The problem is the PDF doesn't say that out loud. A typical GitHub skill includes instructions (write a keyword section), a report template (tables that look like Semrush), and a note that no paid logins are required. There is no built-in step that connects to Google Search Console or SerpStat unless someone adds it manually.

So when the finished audit shows search volumes or rank positions, one of three things happened:

You don't have to take our word for it. Ask whoever ran the audit:

• Did anyone log into Google Search Console during setup?
• Did anyone enter a SerpStat, Semrush, or Ahrefs API key (a paid login that pulls live data)?
• Does the GitHub page say any data credentials are required — or explicitly say none?

If all three answers are no, the keyword table did not come from a ranking database. It exists because the template asked for one. The formatting looks professional. The source doesn't.

Example: An agency runs a default-install skill on a client site. Page one correctly flags GPTBot blocked — that's the automated visitor OpenAI uses to read sites; anyone can verify it with a simple web test. Page four lists ten "priority keywords" with monthly search volumes. Nobody logged into any tool during the run. The numbers are there because the report template required them, not because SerpStat returned them.

Two different audits hiding in one PDF

Most confusion comes from blending two jobs that paid SEO tools keep separate:

A single GitHub skill tries to answer both — even when only the first one has real inputs.

That matters now. G2 found in 2025 that half of B2B buyers start vendor research in an AI chatbot instead of Google Search. Budget decisions are being made off reports that look identical — a free GitHub export and a $3,000 agency deck can share the same layout. They don't share the same data.

Same website, two different truth levels:

Fix the Cloudflare block and you may become visible to AI assistants. Chase a keyword list that was never sourced from a database and you spend a quarter writing content for searches that may not exist.

What free GitHub skills can actually verify

When no paid tools are connected, these findings are usually real — your team can double-check them:

• robots.txt — does your site tell bots what they may read?
• llms.txt — do you have the short about us file for AI at yoursite.com/llms.txt?
• AI crawler access — can automated readers from ChatGPT, Perplexity, and similar tools reach your pages, or is something blocking them?
• Structured data — do your pages include clear machine-readable labels about your business (schema.org / JSON-LD)?
• On-page basics — page titles, headings, meta descriptions
• Page speed — sometimes tested locally (lab data, not Google's full real-user picture)

This is the AI readiness layer — whether assistants can find and understand you — that classic SEO dashboards often skip. We explain how that differs from traditional SEO tools in our GEO tools vs traditional SEO tools guide.

What only paid tools and accounts can show you

Without Google Search Console, SerpStat, or similar services connected, no audit — GitHub skill or otherwise — can honestly claim:

• How many people saw your site in Google search results (impressions) and clicked
• Real search volume and keyword difficulty
• What the SERP (search results page) actually looks like for your keywords — including Google's AI Overviews
• Backlinks — who links to you and how many
• Which keywords competitors rank for, from a real rank database
• Whether ChatGPT, Perplexity, or Gemini cite your brand over time

Some GitHub skills can connect to paid tools — if your team configures API keys, OAuth logins, and keeps them maintained. The skill install is free. The data usually isn't.

One naming note: people search "GitHub GEO Fix" looking for a free version of a paid readiness service. Unrelated repos may use similar words. GEO Fix the service runs a hosted scan and delivers ready-to-use files — robots.txt, llms.txt, and structured data. Same words, different product.

Why leadership gets misled — even when the SEO team knows better

This usually isn't a story about a careless marketer. Experienced SEOs often spot unverified keyword data immediately.

The problem is who sees the final deck. The report leaves the technical team looking complete and lands in a board meeting where nobody will ask whether SerpStat was connected.

Three things make that easy:

1. Professional formatting = assumed accuracy. Severity scores, executive summaries, and keyword tables look like Ahrefs or an agency report. A CEO reads layout as proof.
2. One real finding hides ten uncertain ones. If the robots.txt section is correct, everything else gets trusted too — including keyword volumes nobody sourced.
3. "It's free on GitHub" ends the debate too early. "Why pay £200 for documents when we can run a skill for nothing?" sounds smart before anyone asks whether the free version used the same data as the paid one.

Example: A services company puts a skill-generated audit in a board deck. Slide three: a competitor "dominating local search results." Slide two — buried below — notes that OAI-SearchBot (OpenAI's search crawler) is blocked, which is the fix that would actually affect ChatGPT visibility. The board approves a content budget based on slide three. Nobody on the call uses Search Console. The developer who built the deck knew the keyword slide was estimated; the export didn't label it that way.

That's a governance problem: unverified sections crossing from a dev workflow into a budget decision.

Five questions to ask before you trust any GEO audit

Before you approve spend based on any SEO or GEO audit — GitHub skill, agency report, or SaaS export — ask these five questions. Any leader can ask them; no SEO background required.

1. Where did the ranking numbers come from? Was a specific tool named — Search Console, SerpStat, Semrush — or is there no source at all?
2. Was Google Search Console connected? Did anyone log into your actual Google account during the audit?
3. Was a keyword database connected? Any paid API key or login step during setup?
4. Which findings were live checks on our website? Things like robots.txt, blocked AI crawlers, and missing llms.txt can be verified directly. Ask which sections those are.
5. Which parts are recommendations only? Strategy slides, priority keyword lists, and competitor gaps may be AI-generated suggestions — even when the technical section is real.

Simple rule for leadership: If questions 2 and 3 are both "no," treat every number in the keyword section as unverified — no matter how polished the table looks. That one filter prevents most of the budget mistakes this article describes.

How the options compare

These aren't interchangeable. A free GitHub skill isn't SerpStat. SerpStat won't generate your robots.txt. GEO Fix focuses on whether AI can reach your site and whether the right files are in place — not on keyword rank tracking. For what a proper AI visibility check should cover, see checking if AI can find your business.

What to do next

Key takeaways:

• A default GitHub GEO skill has no ranking database behind it — ask whether Search Console or SerpStat was connected during the run.
• The risk isn't a naive SEO team; it's an unlabelled report reaching leadership without anyone asking where the keyword data came from.
• Separate two questions before spending budget: Can AI read our site? (technical) and Are we winning the right keywords? (market data — needs paid tools).