Free · observed-correlation check
Citation-Readiness Check
Paste a page and we check the structural signals our AI Visibility Index observes on pages AI engines cite — valid schema, answer-first structure, a clean heading outline, a freshness signal, a consistent entity, and an llms.txt. These are observed correlations from our measurement, not a guarantee that you'll be cited — the measured answer for your domain comes from a teardown.
Check a page
This runs entirely in your browser — nothing is sent anywhere. Because a browser can't fetch another site's HTML (CORS), paste your page's source below. In your browser, open the page, view source (Ctrl/Cmd+U), and copy it all in.
Citation-readiness signals
This is not an instant verdict on whether AI will cite you — it's a read on the structural signals our AI Visibility Index observes on pages that do get cited. The measured picture for your own domain, across the AI engines we track, comes from a teardown. How we measure.
A structural check is a starting point — the real number is measured across engines. Get a free teardown, or find your fit in 7 questions.
What each signal means
These six signals are what our AI Visibility Index sees again and again on pages AI engines quote. Valid JSON-LD schema lets engines extract your entity and claims cleanly. An answer-first structure — a direct summary plus lists or tables — gives them extractable chunks to quote. A clean heading outline maps to the sub-questions they answer. A freshness signal shows the page is current. A consistent entity (Organization schema, sameAs, linked profiles) is easier to attribute and trust. And an llms.txt hands agents a curated map of your canonical content. Having them is correlation, not a promise — but it's the structural groundwork citation rests on.
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