To appear in AI answers, a website needs five things: AI crawlers allowed in robots.txt, the content present in the raw HTML, structured data that matches the page, answers in the first sentences under each heading, and a clear, consistent brand entity. Freshness signals that agree with each other close the set. Every requirement on this page comes with a concrete check you can run today.
Published 30 July 2026 by Creative Data Engineers.
AI bots must be allowed in your robots.txt, and the content must be present in the raw HTML the server returns. Both halves matter: an allowed crawler that receives an empty JavaScript shell is as blind as a blocked one. GPTBot, ClaudeBot, and PerplexityBot are documented as reading raw HTML without executing JavaScript; Google's Gemini is the exception.
This is why our audits score every page on two bases: what a browser renders, and what a raw fetch returns. The two scores can be far apart on the same page, and the raw-fetch score is the one most AI systems act on. Content that only appears after client-side rendering, such as product data loaded by a script or FAQ text injected on scroll, does not exist for those crawlers.
Check yours: the Inspector shows the rendering state and a per-crawler robots.txt access row for any URL.
Scan a page free →Three blocks of JSON-LD do the work: an Organization with a real entity graph, a FAQPage that mirrors the questions visible on the page 1:1, and a page-level type that matches the page's role. Schema does not buy citations on its own; what it does is make your pages and entities unambiguous to the crawlers and search indexes AI answers are built from.
Check yours: the Inspector's Schema.org report lists every block, its validity, and the recommended fields it is missing.
Scan a page free →AI systems quote passages, and the passages they quote are the ones that answer a question directly. Put the definition or the answer in the first one or two sentences under each heading, and phrase headings as the questions buyers actually ask. A heading that asks "How long does an audit take?" followed by "Two weeks from kickoff to delivery" is quotable; three paragraphs of context before the number is not.
Check yours: read the first two sentences under each heading and ask whether they answer it. Then scan the page with the Inspector to see whether that text reaches crawlers at all.
Scan a page free →AI systems assemble brands from many sources, and inconsistency splits your identity into fragments. Use one brand name and one description consistently across the site, point your schema's sameAs at real external profiles such as Wikidata and LinkedIn, and keep an about page that plainly says who is behind the site, what the company does, and where it operates.
Check yours: the Inspector's Schema.org report shows whether an Organization block is present and how complete it is.
Scan a page free →A page carries its age in three places: the visible date on the page, the article:modified_time meta tag, and the lastmod entry in the sitemap. They should show the same date, and that date should be true. Matching signals make freshness legible to the systems deciding which source to trust; contradicting ones read as unreliable.
Check yours: the Inspector's meta-tag table shows the date metas a page actually ships.
Scan a page free →No major AI engine reads llms.txt for search or citation today, and Google has confirmed it does not use the file. We ship one on our own site because it costs minutes and does no harm, and that is the whole case for it: a cheap optional extra, never a lever. If a vendor's pitch centers on llms.txt, the pitch is built on a file the engines ignore.
Its plausible future is AI-agent browsing rather than search. Worth a text file, never worth a budget line. Spend the effort on the five requirements above, which are read today.
Check yours: the five requirements above are the ones worth a scan. Point the Inspector at your most important page and spend the effort there.
Scan a page free →An Organization block with a real entity graph: an @id, your logo, and sameAs links pointing at profiles that confirm the entity, such as Wikidata and LinkedIn. On top of that, a FAQPage block that mirrors the questions visible on the page 1:1, and a page-level type that matches the page's role, such as Article for a guide or Service for a service page. Schema does not buy citations on its own; it makes your pages and entities unambiguous to the crawlers and search indexes AI answers are built from.
Yes, when the FAQPage block mirrors questions that are actually visible on the page, word for word. FAQ sections put definitions and direct answers exactly where AI systems quote from, and the schema makes those question-answer pairs machine-readable. Schema-only FAQs, with questions that appear nowhere on the visible page, are the version to avoid: they add markup without adding quotable content.
No major AI engine reads llms.txt for search or citation today, and Google has confirmed it does not use the file. Shipping one takes minutes and does no harm, so we treat it as a cheap optional extra. Be wary of any pitch built around llms.txt: the requirements that measurably matter are crawler access, raw-HTML content, structured data, and answer-first pages.
Mostly no. GPTBot, ClaudeBot, and PerplexityBot are documented as reading raw HTML without executing JavaScript; Google's Gemini is the exception. If your content only appears after client-side rendering, most AI systems receive a blank shell where your page should be. Server-side or static HTML for the content you want cited is the reliable route.
Paste the URL into our free AI Visibility Inspector. It fetches the page the way AI crawlers do and shows the rendering state, per-crawler robots.txt access, the full meta-tag table, and the Schema.org report with fix guidance for every gap. Up to 5 scans a day, no login.
Keep reading: GEO vs SEO explains how these requirements relate to the SEO work you already run, and how it works covers the measurement method behind our audits.
The free Inspector runs this guide's technical checks (rendering state, crawler access, meta tags, Schema.org) on a single page in about half a minute. The writing and entity checks are manual: each section above shows you how. When you want the whole site measured, with the fixes drafted ready to publish, that is the Baseline Audit.