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AI visibility checklist: twenty things you can actually check

Not tips but checks: for every item you can determine in an afternoon whether it is true of you.

Updated ·

This is the cluster's star point, pulling together what the other recipes cover individually. The editorial rule is that every item must be CHECKABLE — not "have good content" but a statement you can verify about your own site. The order roughly matches the order of repair: access and entity first, because nothing else works without them; then citability; then the discipline of measurement. You do not need all of it at once — with the first third green you have already done more than most. One thing to note: this is not a scorecard. There is no aggregate number to extract from it, deliberately — a composite score hides which layer the problem is in, and the fix differs entirely by layer.

The twenty checks

  • Your key pages render server-side

    Look at the served HTML rather than the rendered view: if the substantive text only assembles after JS, a fetcher sees an empty page.

    llms.txt

  • You parsed robots.txt with a tool, not by eye

    Run a parser over every important URL for every AI user-agent — the common error is not a missing rule but an over-broad one.

    AI crawlers in robots.txt

  • You know which bot class you allow

    Training, retrieval and user-initiated are three separate decisions with three separate commercial consequences.

    AI crawlers in robots.txt

  • Your rules point at paths that exist

    After a rename the rule stays but matches nothing — and a rule that matches nothing raises nothing.

    AI crawlers in robots.txt

  • Your name resolves to one thing

    Ask for your name with no context on several surfaces; mixed or foreign results mean entity ambiguity.

    Entity canonicalization

  • You have one stable @id, used everywhere

    A different identifier per page does not describe one company many times; it describes many companies once.

    Organization schema and sameAs

  • Every sameAs URL is live and yours

    A sameAs pointing at a deleted item is worse than none: a broken identity claim that reflects on the whole node.

    Organization schema and sameAs

  • Every page carries the FULL node

    A crawler reads each URL in isolation; a stub node IS the entity for whoever fetched that page.

    Organization schema and sameAs

  • Your five core facts agree everywhere

    Name, location, founding, category, size — contradiction costs more than omission.

    Entity canonicalization

  • You know whether you qualify for a registry item

    Without two or three independent sources, get those first — an item is a consequence of presence, not a means to it.

    Wikidata item for a company

  • You know whether you have a knowledge panel

    Check signed out, on another device and region; with no panel, claiming is not an applicable step.

    Google knowledge panel

  • Your sentences assert something when lifted

    Read them without surrounding context: if they say nothing alone, they cannot be cited.

    Getting cited by Perplexity

  • Your figures carry a source or a method

    A number with no method carries no more weight than an adjective.

    Getting cited by Perplexity

  • Freshness is visible and honest

    Advancing a date without changing content buys nothing short-term and costs credibility later.

    Getting cited by Perplexity

  • Visible text says WHO produced it

    You can be quoted without being named — an author field in the markup is not enough.

    Getting cited by Perplexity

  • You measure repeatedly, not once

    One run is one sample; the variance is the result, and it is the part people throw away.

    AI visibility self-test

  • You ask unaided first

    Once you supply the name you measure whether it KNOWS you, not whether you COME TO MIND.

    AI visibility self-test

  • You separate knowing from finding

    Ask on a sourced and an unsourced surface: the difference between them is the diagnosis.

    Why AI doesn't recommend you

  • You know which layer you are fixing

    Retrieval moves in weeks, trained memory in model generations — patience is also an intervention.

    Why AI doesn't recommend you

  • You ruled out the usual alternatives

    Algorithm update, your own technical change, a new competitor, seasonality — all likelier, because more provable.

    AI Overview traffic drop

Frequently asked questions

In what order should I work through it?
Roughly the order given. Access and entity are the foundation: if machines cannot get in, or cannot tell which one you are, content work attaches to an ambiguous entity. Citability follows, and measurement discipline last — though it is worth starting that early so you have a baseline.
Do I need a developer?
For roughly half the items, yes — server-side rendering, markup and robots.txt touch code. The other half are content and organisational questions you can handle without one: reconciling your facts, visible authorship, the shape of your sentences, measurement.
How long does it take to work through?
CHECKING takes a few hours, given access to your own site and one AI surface. FIXING takes far longer and varies enormously by item: robots.txt is a minute, earning an independent source is months. That is why it pays to walk the whole list and assess before starting anything.
Is there a total score?
No, deliberately. A composite number would hide which layer the problem is in, and fixes differ completely by layer — access moves in weeks, trained memory in model generations. A number that averages those two together is noise rather than information.