Technical GEO Audit

A page can be perfectly written and still be unreadable to an AI crawler

Gumshoe fetches your page, runs its coded assessments against it, and hands you the specific changes that make it readable.

What the Technical GEO Audit assesses

Crawlability

Can AI crawlers reach your pages? robots.txt checked against named AI and search agents, plus meta robots and X-Robots-Tag noindex, plus the HTTP status.

robots.txt

GPTBot Allowed

ClaudeBot Allowed

PerplexityBot Blocked

Fetch health

If your page can't be fetched cleanly, that's the finding. A bot wall, an error response, a redirect to the homepage, or a near-empty body stops the audit and gets reported instead of a score.

Fetched cleanly

the audit runs and returns a score

Otherwise, reported instead of a score

Bot wall Error response Redirect to homepage Near-empty body

Structured Data

Is there JSON-LD, and does every block parse? Plus the metadata a model reads to classify your page: canonical, title, OpenGraph, Twitter card, published date.

{ "@context": "https://schema.org", ... }

{ "name": "Acme", "url": , }

Every block has to parse. One broken block is a finding.

Page Structure

Is your content easy to lift into an answer? One h1 and no skipped heading levels, main content volume against the markup around it, and a main or article landmark.

Answer

What the audit gives you

Summary Score

A score, the reasoning behind it, and the strengths and gaps that produced it.

Very Good

Crawlable and structurally sound, but under-signaled where answer engines preview and attribute the page.

Strengths

Returns 200 and is indexable
Valid JSON-LD is present

Gaps

No Open Graph title or image
Very little text relative to markup

Component Breakdown

Every assessment grouped into its category, each with a score and a pass or fail count.

Machine Readability & Data Layer up to 60% of score

7 pass · 2 fail · 1 not applicable

Content Clarity & Answer-Readiness up to 27% of score

5 pass · 1 fail · 0 not applicable

Authority & Trust Signals up to 9% of score

1 pass · 1 fail · 0 not applicable

Multimodal & Agent Optimization up to 4% of score

1 pass · 0 fail · 1 not applicable

Assessments

Open an assessment and it shows what it looked for, how to fix it, and the evidence.

Open Graph essentials

Fail

Why it matters: Answer engines use these fields to preview and attribute the page.
How to fix: Add og:title, og:type, og:image and og:url to the head.

Evidence

<meta property="og:title"> not found

Canonical tag

Pass

Points at this URL, so the models converge on one version.

How you use it

Point it at a page

Paste a URL and the audit runs against that one page. Start with the pages AI is most likely to draw on when it describes you: home, pricing, product, comparisons.

acme.com/pricing

Run

Assessments run in code

Every assessment runs against the fetched page in code, so the score is repeatable rather than a model's opinion. The written summary sitting on top of it is AI-generated.

robots and status

structured data

headings and content

Findings with evidence

Each finding names what the assessment looked for, what it found, and the change that fixes it. The evidence is what the fetch actually returned, so nothing rests on taking the score at its word.

Open Graph essentials evidence

Text to markup ratio evidence

Publish date evidence

Fix, then run it again

Ship the change and re-run the audit. The score moves with the page, and the audit carries the latest run and the date it ran, so progress is easy to track.

before

after the fix

Questions about the Technical GEO Audit

What does the Technical GEO Audit actually check?

Every assessment is written in code, and they roll up into four categories: Machine Readability and Data Layer, Content Clarity and Answer-Readiness, Authority and Trust Signals, and Multimodal and Agent Optimization. Before any of them run, the page has to be fetched cleanly. When it cannot be, the audit reports the reason instead of a score.

Why might the score move between runs?

Every assessment is coded rather than judged by a model, so the assessments themselves are repeatable. Some inputs are read live at run time though: robots.txt, the HTTP status and the redirect chain all come from your server, and checks that come back not applicable leave the scoring denominator. When the number moves, the evidence on each check tells you which one moved it.

How is this different from a technical SEO audit?

There is real overlap between the two, but the systems underneath them reward different things. AI models favor content they can extract and quote with confidence, which in practice means clear self-contained answers, clean structure, and rendering that does not hide the text from anything that is not a browser. A page can be thoroughly well optimized for Google and still be close to invisible to an AI model.

Are all the assessments weighted the same?

No, each one carries its own weight, which is why a blocked crawler counts for roughly ten times as much as a missing caption track. That keeps a small omission from dragging the score around on its own, and the weighting doubles as a guide to where your effort is genuinely worth spending.

Which crawlers do you check?

Eighteen named AI and search agents are checked against your robots.txt, GPTBot and ClaudeBot included. The finding lists exactly which agents are disallowed, so you can see when a page is open to one bot and closed to another.

Which pages should I audit first?

Start with the pages AI is most likely to draw on when it describes you, which usually means your homepage, your pricing page, your product pages, and your comparison content. Your Citation Audit shows which of your pages AI already cites, and that makes a good priority list to work down.

How many audits do I get?

Starter covers ten page audits a month and Pro covers fifty, and Pro also brings the Citation, Content, and Sentiment Audits with it. The full plan comparison lays out everything else that differs between the two.

How is it different from the Content Audit?

This audit is concerned with whether an AI model can get to a page and parse it, while the Content Audit looks at whether what is on the page answers the questions your buyers are actually putting to AI. Access comes first and substance second, and most sites turn out to need both.

Find out what AI can't see.

Run the Technical GEO Audit on your most important page and get every finding back with the evidence behind it.