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The Founder's AI Visibility Checklist

Everything to check about whether AI answer engines can read, understand and cite your business

Five audit lanes in severity order, the way we work them for clients, and then the monthly rhythm that turns a snapshot into a trend. Access is Lane 2 for a reason: nothing downstream matters if the crawlers are blocked. Print it, work it top to bottom, and keep the file, because next month you run the same checks and read the difference.

Read the book it comes from

Appendix A of The Screenshot, published in full. Nothing here is gated.

Before you start. Every AI answer you capture is a point-in-time observation. Engines change their answers between sessions, accounts and days, so a single reading is a data point and never a verdict. What this checklist covers are the inputs, which are the part you control.

Lane 1 · The answers themselves

You cannot repair a gap you have never looked at. Do this first and keep the file; it becomes the thing every later month is measured against.

  • Prompt set written: 10 to 20 real buying questions, covering category, best-for, versus, how-to and pricing
  • Run across ChatGPT, Perplexity, Gemini, AI Overviews, Copilot and Claude
  • Screenshots dated; named / not-named and citations recorded per engine
  • Login conditions noted, since answers differ between signed-in and signed-out sessions

Lane 2 · Access — fix before everything else

If the crawlers are blocked, every other lane is wasted effort. This is the one that is usually broken by accident, in a file nobody has read in two years.

  • robots.txt fetched and read block by block
  • Per-bot verdict written for GPTBot, ChatGPT-User, PerplexityBot, ClaudeBot, anthropic-ai, Google-Extended and Bingbot: allowed, blocked or unverified, with the reason
  • Bot-protection and firewall layers checked for challenges aimed at AI crawlers
  • Raw-source test: the real copy is present in the initial HTML of every money page, not injected later by script
  • Sitemap present, listed in robots.txt, and actually containing the money pages
  • No stray noindex and no misaimed canonical on any money page
  • Ten-second access check run at optimize.suedeai.ai

Lane 3 · The money pages

An engine has to be able to lift an answer out of your page. The test is whether a claim still holds up once it is pulled out and dropped somewhere else, alone.

  • A plain definition in the first paragraph of every money page
  • Key claims pass the extraction test: true, complete and attributable when read alone
  • Answers-first FAQ, phrased the way buyers actually ask
  • A comparison table wherever the buying question calls for one
  • Headings written as signposts rather than slogans
  • Supported schema only — Organization, Product, FAQPage, Article, HowTo — validated, and matching the visible content
  • Visible, truthful updated dates
  • llms.txt shipped, with claims kept modest

Lane 4 · Evidence

Answer engines and skeptical buyers converge on the same signals: the ones that are expensive to fake. Count your claims against your receipts.

  • Claims-versus-receipts count run across the money pages
  • Named authors with real bios, and Person schema on key content
  • Every number carries a date, a source, or a stated methodology
  • Disclosures present anywhere a skeptic would want one
  • Review-platform presence accurate, and happy customers actually asked
  • Offsite trail checked by asking an engine: "What do people say about [company]? Include sources."

Lane 5 · Entity clarity

Machines have to be able to tell that all of your surfaces are the same company. Being one consistent thing everywhere is most of this lane.

  • One consistent organization name and description across every surface you control
  • Organization and Person schema connecting the people, the product and the site
  • "What do you know about [company]?" asked across engines, and the coherence of the answers graded

Then · The rhythm

Not a lane, but the habit that makes the lanes worth running. One reading is a data point; the trend is the finding.

  • Repairs logged with their ship dates
  • Inputs verified live before each re-scan — the schema block really in production, the deploy really not reverted
  • A 30-minute monthly re-scan on the calendar: same prompts, same file
  • Deltas read as trend, displacement and input correlation, with single-month wobble ignored
Where this comes from

The reasoning behind each line

Every lane above is a chapter. The Screenshot explains why access comes before everything, what each of the six engines actually trusts, how to write a passage that survives extraction, and how to read a month-over-month delta without fooling yourself. It is free, in PDF and EPUB, with no email required.

If you would rather have the audit run for you: this practice runs all five lanes continuously, with GEO, PR and reputation work beside them, for a small number of companies. Scope and price are quoted by reply.

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