BE DISCOVERABLE BY AI
robots.txt, sitemaps, canonicals, indexability and AI crawler access form the discovery foundation.
Experience, Expertise, Authoritativeness and Trustworthiness: a quality-evaluation concept used in Google's guidance and quality rater framework.
Google says E-E-A-T can help creators self-assess content quality. Search quality raters use it to evaluate results, but rater data is not used directly as a ranking algorithm score.
Clear authorship, first-hand experience, sourcing, organization identity, editorial accountability and factual accuracy make content easier to trust and verify.
For commercial and high-stakes topics, visitors and systems both need evidence of who is responsible for the information and why it should be trusted.
HTML&HTML observes authorship, About/Contact/Privacy presence, organization/person schema, citations, freshness and trust signals; it does not claim to measure Google's internal E-E-A-T score.
E-E-A-T is not a single public numeric Google ranking factor that third-party tools can read.
HTML&HTML prepares your website for visibility, citation eligibility and recommendation opportunity across AI search experiences. It shows measurable website-side blockers that can prevent discovery, understanding and source consideration.
robots.txt, sitemaps, canonicals, indexability and AI crawler access form the discovery foundation.
GEO, AEO, LLMO, entity graphs, schema and answer extractability reduce machine ambiguity.
RAG/retrieval, original information, E-E-A-T, freshness and evidence support source eligibility.
AAO, accessible journeys, intact links, measurable referrals and clear CTAs connect AI discovery to commercial action.
Recommendations, rankings, citations, traffic, customers and revenue are not guaranteed. HTML&HTML measures website-side technical and content blockers; it does not claim control over external AI systems.