AI Search Readiness Checker
See how ready a page is to be cited by AI search engines.
How it works
Enter a URL and the checker audits seven weighted signals that decide whether AI search engines can find, read, and cite the page: server-rendered text (most AI crawlers don't execute JavaScript), an llms.txt index, a markdown twin of the page, JSON-LD structured data, clean heading structure, robots.txt access for GPTBot, ClaudeBot, and PerplexityBot, and a canonical URL.
Each signal earns its weight toward a 0-100 score with an A-F grade, and every dropped point comes with the specific fix that recovers it.
The scorecard and per-signal findings download as CSV or JSON, free and instant.
Frequently asked questions
Why does server-rendered content weigh so much?
Because most AI crawlers fetch your HTML and read the text in it — no JavaScript execution. If your content only exists after client-side rendering, AI search engines see an empty shell, and nothing else on this checklist can compensate.
Which AI crawlers does the robots.txt check cover?
GPTBot (OpenAI), ClaudeBot (Anthropic), and PerplexityBot — the crawlers behind the major AI answer engines. Blocking them in robots.txt is a legitimate choice, but it means those engines can't cite you, so the checker treats it as lost readiness.
What are markdown twins and llms.txt?
A .md twin is a clean markdown version of a page served alongside the HTML; llms.txt is a root-level index pointing agents at those twins. Together they let AI agents consume your content without parsing your page chrome — the core of the AFDocs standard our hero checker scores in full.
Ready for AI search. Now get cited.
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