robots.txt is a site-wide file — blocking AI bots here prevents them from crawling any page on this domain. Unblocking is the highest-priority fix.

llms.txt lives at the domain root and describes the whole site to AI agents. Its impact on citation rates is plausible but not yet confirmed by published research.

JSON-LD schema markup helps AI engines correctly categorise your content and may improve how it is attributed in their answers.

Your page does not answer questions that AI search engines frequently receive about your topic. Add them as clearly-headed sections with a direct one-paragraph answer each.

Add author bylines and a link to an About or Team page — this signals to AI that a real organisation or expert stands behind the content, which may increase citation likelihood.

Organization schema already present — add author fields to it.

Estimated score after all fixes

Projected gain is conservative (40% of theoretical max) — real-world improvements depend on implementation quality.

Mostly — the majority of questions are covered, but remaining gaps reduce citation frequency.

Partial — some AI bots are likely blocked in robots.txt (a site-wide setting).

Not detected — we found no JSON-LD of the types AI engines rely on. If you have added schema recently, re-audit to re-check.

Partial — some sections are well structured, but most aren't in Q&A format.

Checked on the audited URL only. If your FAQ or Q&A content lives on a separate page (e.g. /faq), audit that URL directly for a higher score.

No — page lacks statistics or external sources. AI engines prefer pages that back claims with data.

Yes — content was recently published or updated.

Not detected in markup — we found no author byline, About link or Organization schema. Trust signals that exist only as text or images are not machine-readable, which is what this measures.