Sample AI Visibility Audit Report

What the report looks like

Technical foundations

Six live HTTP checks run against your domain, as the AI crawlers themselves see it.

• Crawler access (6 AI user agents)

  All six fetches returned 200.

• robots.txt

  Present, no AI crawler blocked.

• llms.txt

  Missing — assistants have no curated entry point.

• sitemap.xml

  Found, 34 URLs discovered.

• Schema markup

  Organization only; no Service or FAQPage.

• JS rendering dependency

  Key copy only appears after JavaScript runs.

AI citation results

We generate 8 buyer-intent questions for your category and ask all four assistants — 32 real AI answers — then measure how often your brand is named.

Prioritized fixes

Every recommendation is written twice: once in plain English for you, once as an implementation note for whoever owns the site.

1. Priority 1

   Publish an llms.txt file

   What this means

   Give AI assistants a short, plain-text map of what you do and which pages matter. It is a small, self-contained change to your site.

   For your developer

   Serve /llms.txt as text/plain with a company summary and a linked index of canonical pages. Mirror the long form at /llms-full.txt.

2. Priority 2

   Server-render the pages you want cited

   What this means

   Right now some of your best copy only appears after the page loads scripts. Several AI crawlers never see it.

   For your developer

   Move category and service copy into the SSR payload. Verify with curl -A 'GPTBot' and confirm the text is present in the raw HTML.

3. Priority 3

   Add Service and FAQPage schema

   What this means

   Structured data tells assistants exactly what you sell and answers the questions buyers ask, in a format they can quote.

   For your developer

   Add JSON-LD Service on each offering page and FAQPage on the pricing and support pages. Validate against schema.org.

4. Priority 4

   Build third-party mention volume

   What this means

   Assistants repeat what the wider web says about you. Four review profiles and two industry mentions moves this category more than any on-site change.

   For your developer

   Claim and complete review profiles, publish comparison pages, and pursue two category round-up placements per quarter.

How we test

Six live technical checks

We fetch your site as six AI user agents (GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, Google-Extended and a control browser), then parse robots.txt, llms.txt, sitemap.xml, schema markup, semantic HTML and JavaScript dependency.

8 questions across 4 engines = 32 AI answers

We generate buyer-intent questions for your specific category, then ask ChatGPT (GPT-4o), Claude, Gemini and Perplexity. Every answer is stored verbatim in your report so you can read exactly what a buyer would see.

Citation Signal Scan™ (Visibility Proof Package)

Five off-site channels — YouTube, LinkedIn, Wikipedia, review platforms and owned content — reported as diagnostic findings that explain why your mention rate is what it is. They are not score inputs.

Transparent scoring

Foundation Score = % of technical checks passed. AI Visibility Score = % of AI answers that mention you. Overall = the average. Every number shows its X-of-Y math, so you can re-test and see movement.