Technical GEO Audit

Make your site readable by AI agents

When a buyer sends an agent to research you, it gets one fetch. Gumshoe runs its coded assessments against that same page and hands you the specific changes that let the agent read it.

What an agent needs from your page

Agent Access

Is the door open when an agent arrives? 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

An agent gets one fetch, usually while a buyer waits for the answer. 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 an agent reads to work out what the page is: 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

Can an agent find the answer without guessing? 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 an agent is most likely to open when a buyer asks about 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, which is close to what an agent gets back.

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 is the difference between an AI agent and an AI crawler?

A crawler visits ahead of time to build an index or training set. An agent visits in the moment, because a buyer asked it to research a product, compare vendors, or pull a price. Both need the same things from a page: permission to fetch it, a clean response, and content they can parse. The difference is that an agent that hits a wall usually moves on to a competitor's page within the same answer.

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.

Which agents 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 assistant and closed to another.

Why would an agent fail to read my page?

The common causes are a robots.txt rule nobody remembers adding, a bot-protection layer that serves a challenge page instead of content, and pages that render their text only after JavaScript runs. Each of those shows up in the audit as a disallowed agent, a failed fetch, or a near-empty body, with the evidence of what the fetch returned.

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.

Are all the assessments weighted the same?

No, each one carries its own weight, which is why a blocked agent 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.

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 agent 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 agents can't see.

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