Want to know if ChatGPT, Gemini or Perplexity could actually cite one of your pages? Paste the URL below. The checker fetches the live page and reports the exact signals these engines look for, then tells you what to fix first.
This is not a guess based on your own answers. The tool reads the real HTML of the page, the same way an engine’s crawler does, and scores what it finds.
AI readiness score
Fix these first
Every signal we checked
What the checker looks at
AI engines do not cite pages they cannot parse, verify or trust. Every check here maps to one of those three jobs.
Parsing is about structure: a clean title, one H1, real H2 sections, and schema markup that spells out what the page is. Verification is about evidence: original numbers, a visible date, a named author. Trust is the rest: HTTPS, canonical tags, enough depth to be worth quoting.
The single heaviest check is structured data, because schema is how a page hands an engine clean, machine-readable facts. Right behind it sit content depth and original-data markers, because a page with at least 3 original data points is about 4x more likely to be cited in AI answers, per 2026 industry analyses. A thin page with no numbers gives the engine nothing to lift.
How to read your score
Treat the number as a worklist, not a grade on your work. The fixes are ranked by how many points they are worth, so the top item is always the highest-leverage change you can make.
Most pages fail in the same three places: no schema, no original data, and no visible freshness date. Those three are also the cheapest to fix and the ones engines weight most. Start there.
Run it on a competitor’s page too. If they are getting cited and you are not, this is usually where the gap shows up.
Two tools, one framework
This checker grades a single page from the outside. The AI Recommendation Scorecard grades your whole brand against the full 22-point framework, including the off-page signals (reviews, listicles, community presence) that a single page cannot show.
Use the checker to fix individual pages. Use the scorecard to plan the bigger picture. Both rest on the same playbook.
Read the full AI recommendation playbook →
Questions people ask
Is it really free, and is my data stored? Free, no signup, nothing stored. The page is fetched server-side, analyzed in memory, and the result is returned to your browser. We keep none of it.
Does a high score guarantee citations? No. The checker measures the on-page signals you control. The engines still decide, and off-page factors like third-party reviews and listicle presence matter too. A high score means you are not losing on the basics.
Why did a page fail a check it should pass? The checker reads the HTML as served. If a signal is added by JavaScript after load, or sits behind a login, it may not see it. Check the page source to confirm.
Can I link to or share this tool? Yes. Link freely. A useful free tool is exactly the kind of page that earns citations, which is one of the things it measures.
Sources and method
How it works. The tool fetches the URL server-side, reads the returned HTML, and scores eleven on-page signals weighted by how much each one influences AI citability. It does not run JavaScript, so client-rendered signals may not be detected.
Original Topickz data. The framework behind the weighting comes from Topickz’s analysis of 816 B2B SaaS tool entries, May to June 2026. See the B2B SaaS Buyer-Behavior Report .
Third-party figures, attributed. The citation statistic (3+ data points about 4x more likely cited) is drawn from 2026 industry analyses of AI Overview and generative-engine citations, not generated by Topickz.
For our independence and corrections policy, see our editorial standards .