Run a Technical GEO Audit for Clients | Readable by AI crawlers

Technical GEO Audit

Your client's page can be perfectly written and still be unreadable to an AI crawler.

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

See the audit

What the Technical GEO Audit assesses

Crawlability

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

Fetch health

If the 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.

Structured Data

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

<script type="application/ld+json">
{ "@context": "https://schema.org", ... }
</script>
<script type="application/ld+json">
{ "name": "Acme", "url": , }
</script>

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

Page Structure

Is the 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.

What the audit gives you

  1. Summary Score

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

    • Score: 78%
    • Rating: Very Good
    • Strengths:
      • Returns 200 and is indexable
      • Valid JSON-LD is present
    • Gaps:
      • No Open Graph title or image
      • Very little text relative to markup

  2. 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
      • Score: 71
      • 7 pass · 2 fail · 1 not applicable
    • Content Clarity & Answer-Readiness up to 27% of score
      • Score: 84
      • 5 pass · 1 fail · 0 not applicable
    • Authority & Trust Signals up to 9% of score
      • Score: 45
      • 1 pass · 1 fail · 0 not applicable
    • Multimodal & Agent Optimization up to 4% of score
      • Score: 90
      • 1 pass · 0 fail · 1 not applicable

  3. Assessments

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

    • Open Graph essentials
      • Status: 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
      • Status: Pass
      • Points at this URL, so the models converge on one version.

How you use it

  1. 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 the client: home, pricing, product, comparisons.

    • Example: acme.com/pricing

  2. 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

  3. 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

  4. 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 show a client.

Questions about the Technical GEO Audit

  1. 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.

  2. Can I put this score in a client report?

    • That is what it is built for. Every assessment reports the evidence it found.

  3. How is this different from a technical SEO audit?

    • There is real overlap between the two, but the systems underneath them reward different things.

  4. Are all the assessments weighted the same?

    • No, each one carries its own weight.

  5. Which crawlers do you check?

    • Eighteen named AI and search agents are checked against the client's robots.txt, GPTBot and ClaudeBot included.

  6. How many pages can I audit across a client roster?

    • Starter covers ten page audits a month and Pro covers fifty.

  7. Is it priced per client?

    • Pricing works per project rather than per client.

  8. 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.

Find out what AI can't see on your clients' sites.

Run the Technical GEO Audit on a client's most important page and get every finding back with the evidence behind it.

Run a Technical GEO Audit