` or `[rel=\"author\"]`) AND a `` tag.","weight":0.1,"category":"authority","severity":"absent"},{"key":"date-markup","label":"Publish + update date markup","score":0,"detail":"No structured publish date. Freshness ranking can't be applied.","remedy":"Add `` for published date AND a `` for updates.","weight":0.09,"category":"authority","severity":"absent"},{"key":"freshness","label":"Content freshness","score":0,"detail":"No parseable date — engines treat undated content as stale.","remedy":"Add a parseable date — `` or ``.","weight":0.13,"category":"authority","severity":"absent"},{"key":"technical-terms","label":"Technical / domain vocabulary","score":1,"detail":"5 multi-syllable words (~29.4% of total).","remedy":null,"weight":0.14,"category":"authority","severity":"ok"},{"key":"direct-answer","label":"Direct answer in the lead","score":0.5,"detail":"2 of 4 query terms appear in the first paragraph.","remedy":"Open the page with a direct, complete answer to the buyer query — engines extract their citation snippet from the lead paragraph.","weight":0.18,"category":"content","severity":"weak"},{"key":"query-coverage","label":"Query-term coverage","score":0.75,"detail":"75% of query terms appear somewhere on the page.","remedy":null,"weight":0.15,"category":"content","severity":"ok"},{"key":"entity-coverage","label":"Named-entity coverage","score":0.3,"detail":"3 distinct proper-noun entities mentioned.","remedy":"Mention the named entities (people, products, organisations, places) the buyer query implies. Entity coverage feeds knowledge-graph retrieval.","weight":0.14,"category":"content","severity":"weak"},{"key":"readability","label":"Readability (Flesch Reading Ease)","score":0.2,"detail":"Reading-ease score: 21.9 (target 60-70).","remedy":"Page reads too academic — shorter sentences and simpler vocabulary lift citation rate by ~12% (GEO §4.3).","weight":0.11,"category":"content","severity":"absent"},{"key":"length","label":"Content depth","score":0,"detail":"17 words. Target 300-2500 — engines bias toward focused depth.","remedy":"Page is too short. Expand to at least 500 words covering the query in depth.","weight":0.1,"category":"content","severity":"absent"},{"key":"info-density","label":"Information density","score":0.3,"detail":"Unique-word ratio: 88.2% (target 40-60%).","remedy":"Vocabulary varies too wildly — content may lack topical focus. Engines prefer focused pages.","weight":0.1,"category":"content","severity":"weak"},{"key":"definitions","label":"Definitional sentences","score":0,"detail":"0 definitional sentences.","remedy":"Include definitional sentences (\"X is...\", \"X refers to...\"). Engines specifically extract definitions for AI Overview snippets.","weight":0.1,"category":"content","severity":"absent"},{"key":"bluf-answer","label":"BLUF — answer in first 100 words","score":0.6499999999999999,"detail":"First 100 words cover 2/4 query terms + definitional phrase ✓.","remedy":"Put the answer in the FIRST 100 words — Perplexity's pipeline summarizes that exact span before reranking. \"BLUF\" (bottom-line-up-front) is the format that wins.","weight":0.16,"category":"content","severity":"weak"},{"key":"mega-page-coverage","label":"Mega-page coverage (what/who/how/pricing)","score":0,"detail":"0/4 facets covered (what ✗, who ✗, how ✗, pricing ✗).","remedy":"Cover what / who / how / pricing in the same URL. Chatoptic's 75k-page study found the top 4.8% of repeatedly-cited pages share this single-URL completeness.","weight":0.14,"category":"content","severity":"absent"},{"key":"youtube-embed","label":"YouTube video presence","score":0,"detail":"No YouTube presence.","remedy":"Embed (or link to) a YouTube video covering this topic. Ahrefs's 75k-brand study measured YouTube as the SINGLE strongest correlation (0.737) with AI citation across ChatGPT, AI Mode, and AI Overviews.","weight":0.13,"category":"content","severity":"absent"},{"key":"sub-query-coverage","label":"Sub-query coverage","score":0.6666666666666666,"detail":"2/3 decomposed sub-questions addressed on the page.","remedy":"Cover the sub-questions buyers actually ask along with the seed query. Currently failing on: how does what is example domain work","weight":0.13,"category":"content","severity":"weak"},{"key":"https","label":"HTTPS","score":1,"detail":"Page served over HTTPS.","remedy":null,"weight":0.25,"category":"trust","severity":"ok"},{"key":"canonical","label":"Canonical URL","score":0,"detail":"No canonical link element.","remedy":"Add ``. Engines use it to de-duplicate competing URLs for the same content.","weight":0.15,"category":"trust","severity":"weak"},{"key":"viewport","label":"Mobile-friendly viewport","score":1,"detail":"Viewport meta tag present.","remedy":null,"weight":0.15,"category":"trust","severity":"ok"},{"key":"twitter-card","label":"Twitter Card","score":0.3,"detail":"No Twitter Card — secondary signal but easy to add.","remedy":"Add `` and the matching title/description/image.","weight":0.1,"category":"trust","severity":"weak"},{"key":"meta-description","label":"Meta description","score":0,"detail":"No meta description.","remedy":"Add a `` summarising the page in 120-160 characters.","weight":0.35,"category":"trust","severity":"weak"},{"key":"ai-bot-access","label":"AI retrieval-bot access (robots.txt)","score":0.7,"detail":"No robots.txt found — all crawlers default to allowed (acceptable for AEO).","remedy":null,"weight":0.12,"category":"trust","severity":"ok"},{"key":"llms-txt-presence","label":"llms.txt present at /llms.txt","score":0,"detail":"No /llms.txt found. Adoption is ~10% in 2026; presence is a recognized AI-readiness signal.","remedy":"Add a spec-compliant /llms.txt at the site root. Use VectorCite's generator at /audit/llms-txt — free, no signup. Anthropic's Claude and the major IDE coding agents fetch it for retrieval.","weight":0.08,"category":"trust","severity":"weak"},{"key":"first-person","label":"First-person language","score":0,"detail":"0 first-person pronouns (0.0% of words). Target 0.5-3%.","remedy":"Add first-person language showing lived experience — \"we\", \"our team\", \"I\". Google rates first-person as direct evidence of the new E-for-Experience EEAT pillar.","weight":0.1,"category":"eeat","severity":"absent"},{"key":"case-study-evidence","label":"Case study / concrete examples","score":0,"detail":"0 case-study patterns matched (examples, results, hands-on phrases).","remedy":"Add at least 2-3 concrete examples or mini-case-studies. \"We helped X achieve Y\" beats abstract claims; AI engines preferentially cite pages with measurable outcomes.","weight":0.1,"category":"eeat","severity":"absent"},{"key":"author-credentials","label":"Author bio with credentials","score":0,"detail":"No `.author-bio` / `[itemprop=\"author\"]` element found.","remedy":"Add an author-bio section with the author's name, role, and credentials (degree, years of experience, certifications).","weight":0.13,"category":"eeat","severity":"absent"},{"key":"byline-depth","label":"Byline depth (link + reviewer + date)","score":0,"detail":"no linked byline, no reviewer, no date","remedy":"Strengthen the byline: link author name to an author profile page; add \"reviewed by\" / \"edited by\" markup; mark published + modified dates explicitly.","weight":0.08,"category":"eeat","severity":"absent"},{"key":"brand-entity","label":"Brand recognized as Wikidata entity","score":1,"detail":"Wikidata: Q114424786 — mathematical subtext, which presents an application or an illustration of the subject or of the theo","remedy":null,"weight":0.16,"category":"eeat","severity":"ok"},{"key":"press-mentions","label":"Press / media mentions","score":0,"detail":"0 press-mention pattern(s) matched.","remedy":"Add a \"Featured in\" / \"As seen in\" strip listing publications that have covered you. External recognition is a top authority signal.","weight":0.11,"category":"eeat","severity":"absent"},{"key":"privacy-terms","label":"Privacy + Terms links","score":0,"detail":"Privacy ✗, Terms ✗.","remedy":"Add Privacy Policy and Terms of Service links (typically in the footer). Their absence is a hard trust-floor signal — Google's quality raters down-rank pages that lack them.","weight":0.13,"category":"eeat","severity":"absent"},{"key":"contact-info","label":"Contact information","score":0,"detail":"email ✗, phone ✗, address ✗, no contact link","remedy":"Expose verifiable contact info: an email link, a phone number, and ideally a physical address marked up with `

` or `itemprop=\"address\"`. Anonymous sites read as low-trust.","weight":0.13,"category":"eeat","severity":"absent"}],"summary":{"ok":10,"weak":10,"total":47,"absent":27},"categories":[{"score":29,"signals":[{"key":"json-ld-presence","label":"JSON-LD structured data","score":0,"detail":"No JSON-LD blocks found. Answer engines key off schema.org markup to ground citations.","remedy":"Add at least one schema.org JSON-LD block — Article, Product, FAQPage, or HowTo are the highest-lift types.","weight":0.13,"category":"structure","severity":"absent"},{"key":"json-ld-validity","label":"JSON-LD validity","score":1,"detail":"No JSON-LD blocks to validate (the presence signal covers that).","remedy":null,"weight":0.1,"category":"structure","severity":"ok"},{"key":"json-ld-relevance","label":"Schema type matches query intent","score":0,"detail":"No schema types — for a informational query, add one of: Article, BlogPosting, FAQPage, HowTo.","remedy":"Add a Article JSON-LD block — the highest-leverage schema type for a \"what is example domain\" query.","weight":0.12,"category":"structure","severity":"absent"},{"key":"faq-schema","label":"FAQ / Q&A schema","score":0,"detail":"No FAQPage / QAPage schema — AI Overviews preferentially cite pages exposing structured Q&A.","remedy":"Add a FAQPage schema with 3-5 questions buyers actually ask. The single most direct path to AI Overview citation.","weight":0.1,"category":"structure","severity":"absent"},{"key":"h1-quality","label":"H1 quality","score":0.6,"detail":"H1: \"Example Domain\" (14 chars).","remedy":"Adjust H1 length to 20-80 chars — shorter than 20 lacks context, longer than 80 loses retrieval focus.","weight":0.1,"category":"structure","severity":"weak"},{"key":"h2-coverage","label":"H2 subtopic coverage","score":0,"detail":"0 H2 headings — answer engines decompose a buyer query into subtopics and match each to an H2.","remedy":"Break the page into at least 4 H2 sections, each answering one aspect of the buyer query. Engines surface specific H2s as citations.","weight":0.09,"category":"structure","severity":"absent"},{"key":"lists","label":"Lists (bulleted / numbered)","score":0,"detail":"No lists — AI engines preferentially cite list items because they pack into answer summaries cleanly.","remedy":"Add 2-3 bulleted lists summarising key points. They're the single most-cited structural element in AI summaries.","weight":0.08,"category":"structure","severity":"absent"},{"key":"tables","label":"Comparison tables","score":0.5,"detail":"No tables. Comparison / specification tables are heavily cited for product and technical queries.","remedy":null,"weight":0.07,"category":"structure","severity":"ok"},{"key":"alt-text","label":"Image alt-text coverage","score":1,"detail":"No images — alt-text coverage trivially complete.","remedy":null,"weight":0.05,"category":"structure","severity":"ok"},{"key":"open-graph","label":"Open Graph metadata","score":0,"detail":"Open Graph: title ✗, desc ✗, image ✗.","remedy":"Add og:title, og:description, og:image meta tags. AI engines use OG for the cited preview card.","weight":0.06,"category":"structure","severity":"absent"},{"key":"internal-linking","label":"Internal linking quality","score":0,"detail":"0 internal links (0 with descriptive anchors), 1 external.","remedy":"Add 5-15 internal links to related pages on the same domain — engines use the internal link graph to weight topical relevance.","weight":0.08,"category":"structure","severity":"absent"},{"key":"page-weight","label":"Page weight + render-blocking","score":1,"detail":"1 KB HTML, 0 blocking script(s), 0 blocking stylesheet(s), 0/0 images without lazy-load.","remedy":null,"weight":0.06,"category":"structure","severity":"ok"},{"key":"structural-depth","label":"GEO-SFE structural depth (macro/meso/micro)","score":0.28,"detail":"Macro: max heading depth H1 (H1=1, H2=0, H3=0, H4=0). Meso: 2.0 chunks/section avg. Micro: 0.00% visual emphasis.","remedy":"Three-level structural depth (validated +17.3% citation lift, GEO-SFE arXiv:2603.29979): use H1→H2→H3 hierarchy, 5+ paragraphs/lists per H2 section, and 1-5% visual emphasis (bold/italic/code) to flag retrieval-worthy spans.","weight":0.1,"category":"structure","severity":"absent"}],"category":"structure"},{"score":14,"signals":[{"key":"outbound-authority-links","label":"Outbound links to authoritative sources","score":0,"detail":"0 links to authoritative domains (.edu, .gov, named sources).","remedy":"Add 2-3 outbound citations to .edu / .gov / known publishers. The GEO paper measured this as the #2 citation-lift factor.","weight":0.16,"category":"authority","severity":"absent"},{"key":"citation-density","label":"Inline citations and attributions","score":0,"detail":"0 bracketed citations + 0 attribution phrases (per 200 words: 0%).","remedy":"Add inline citations ([1], [2]) or attribution phrases (\"according to X\"). GEO factor #1 for credibility-weighted citation.","weight":0.14,"category":"authority","severity":"absent"},{"key":"statistic-density","label":"Statistic density","score":0,"detail":"0 numerical facts (~0 per 100 words).","remedy":"Add concrete statistics with sources. AI engines preferentially cite paragraphs containing numbers — a GEO paper §4.1 finding.","weight":0.13,"category":"authority","severity":"absent"},{"key":"quotations","label":"Expert quotations","score":0,"detail":"0 blockquotes + 0 long inline quotes.","remedy":"Include at least one direct quote from a named expert, ideally in a

. Quote-rich pages are 28% more likely to be cited (GEO paper).","weight":0.11,"category":"authority","severity":"absent"},{"key":"author-byline","label":"Author byline","score":0,"detail":"No author byline. E-E-A-T penalises anonymous content.","remedy":"Add a visible author byline (a `
` or `[rel=\"author\"]`) AND a `` tag.","weight":0.1,"category":"authority","severity":"absent"},{"key":"date-markup","label":"Publish + update date markup","score":0,"detail":"No structured publish date. Freshness ranking can't be applied.","remedy":"Add `` for published date AND a `` for updates.","weight":0.09,"category":"authority","severity":"absent"},{"key":"freshness","label":"Content freshness","score":0,"detail":"No parseable date — engines treat undated content as stale.","remedy":"Add a parseable date — `` or ``.","weight":0.13,"category":"authority","severity":"absent"},{"key":"technical-terms","label":"Technical / domain vocabulary","score":1,"detail":"5 multi-syllable words (~29.4% of total).","remedy":null,"weight":0.14,"category":"authority","severity":"ok"}],"category":"authority"},{"score":34,"signals":[{"key":"direct-answer","label":"Direct answer in the lead","score":0.5,"detail":"2 of 4 query terms appear in the first paragraph.","remedy":"Open the page with a direct, complete answer to the buyer query — engines extract their citation snippet from the lead paragraph.","weight":0.18,"category":"content","severity":"weak"},{"key":"query-coverage","label":"Query-term coverage","score":0.75,"detail":"75% of query terms appear somewhere on the page.","remedy":null,"weight":0.15,"category":"content","severity":"ok"},{"key":"entity-coverage","label":"Named-entity coverage","score":0.3,"detail":"3 distinct proper-noun entities mentioned.","remedy":"Mention the named entities (people, products, organisations, places) the buyer query implies. Entity coverage feeds knowledge-graph retrieval.","weight":0.14,"category":"content","severity":"weak"},{"key":"readability","label":"Readability (Flesch Reading Ease)","score":0.2,"detail":"Reading-ease score: 21.9 (target 60-70).","remedy":"Page reads too academic — shorter sentences and simpler vocabulary lift citation rate by ~12% (GEO §4.3).","weight":0.11,"category":"content","severity":"absent"},{"key":"length","label":"Content depth","score":0,"detail":"17 words. Target 300-2500 — engines bias toward focused depth.","remedy":"Page is too short. Expand to at least 500 words covering the query in depth.","weight":0.1,"category":"content","severity":"absent"},{"key":"info-density","label":"Information density","score":0.3,"detail":"Unique-word ratio: 88.2% (target 40-60%).","remedy":"Vocabulary varies too wildly — content may lack topical focus. Engines prefer focused pages.","weight":0.1,"category":"content","severity":"weak"},{"key":"definitions","label":"Definitional sentences","score":0,"detail":"0 definitional sentences.","remedy":"Include definitional sentences (\"X is...\", \"X refers to...\"). Engines specifically extract definitions for AI Overview snippets.","weight":0.1,"category":"content","severity":"absent"},{"key":"bluf-answer","label":"BLUF — answer in first 100 words","score":0.6499999999999999,"detail":"First 100 words cover 2/4 query terms + definitional phrase ✓.","remedy":"Put the answer in the FIRST 100 words — Perplexity's pipeline summarizes that exact span before reranking. \"BLUF\" (bottom-line-up-front) is the format that wins.","weight":0.16,"category":"content","severity":"weak"},{"key":"mega-page-coverage","label":"Mega-page coverage (what/who/how/pricing)","score":0,"detail":"0/4 facets covered (what ✗, who ✗, how ✗, pricing ✗).","remedy":"Cover what / who / how / pricing in the same URL. Chatoptic's 75k-page study found the top 4.8% of repeatedly-cited pages share this single-URL completeness.","weight":0.14,"category":"content","severity":"absent"},{"key":"youtube-embed","label":"YouTube video presence","score":0,"detail":"No YouTube presence.","remedy":"Embed (or link to) a YouTube video covering this topic. Ahrefs's 75k-brand study measured YouTube as the SINGLE strongest correlation (0.737) with AI citation across ChatGPT, AI Mode, and AI Overviews.","weight":0.13,"category":"content","severity":"absent"},{"key":"sub-query-coverage","label":"Sub-query coverage","score":0.6666666666666666,"detail":"2/3 decomposed sub-questions addressed on the page.","remedy":"Cover the sub-questions buyers actually ask along with the seed query. Currently failing on: how does what is example domain work","weight":0.13,"category":"content","severity":"weak"}],"category":"content"},{"score":43,"signals":[{"key":"https","label":"HTTPS","score":1,"detail":"Page served over HTTPS.","remedy":null,"weight":0.25,"category":"trust","severity":"ok"},{"key":"canonical","label":"Canonical URL","score":0,"detail":"No canonical link element.","remedy":"Add ``. Engines use it to de-duplicate competing URLs for the same content.","weight":0.15,"category":"trust","severity":"weak"},{"key":"viewport","label":"Mobile-friendly viewport","score":1,"detail":"Viewport meta tag present.","remedy":null,"weight":0.15,"category":"trust","severity":"ok"},{"key":"twitter-card","label":"Twitter Card","score":0.3,"detail":"No Twitter Card — secondary signal but easy to add.","remedy":"Add `` and the matching title/description/image.","weight":0.1,"category":"trust","severity":"weak"},{"key":"meta-description","label":"Meta description","score":0,"detail":"No meta description.","remedy":"Add a `` summarising the page in 120-160 characters.","weight":0.35,"category":"trust","severity":"weak"},{"key":"ai-bot-access","label":"AI retrieval-bot access (robots.txt)","score":0.7,"detail":"No robots.txt found — all crawlers default to allowed (acceptable for AEO).","remedy":null,"weight":0.12,"category":"trust","severity":"ok"},{"key":"llms-txt-presence","label":"llms.txt present at /llms.txt","score":0,"detail":"No /llms.txt found. Adoption is ~10% in 2026; presence is a recognized AI-readiness signal.","remedy":"Add a spec-compliant /llms.txt at the site root. Use VectorCite's generator at /audit/llms-txt — free, no signup. Anthropic's Claude and the major IDE coding agents fetch it for retrieval.","weight":0.08,"category":"trust","severity":"weak"}],"category":"trust"},{"score":17,"signals":[{"key":"first-person","label":"First-person language","score":0,"detail":"0 first-person pronouns (0.0% of words). Target 0.5-3%.","remedy":"Add first-person language showing lived experience — \"we\", \"our team\", \"I\". Google rates first-person as direct evidence of the new E-for-Experience EEAT pillar.","weight":0.1,"category":"eeat","severity":"absent"},{"key":"case-study-evidence","label":"Case study / concrete examples","score":0,"detail":"0 case-study patterns matched (examples, results, hands-on phrases).","remedy":"Add at least 2-3 concrete examples or mini-case-studies. \"We helped X achieve Y\" beats abstract claims; AI engines preferentially cite pages with measurable outcomes.","weight":0.1,"category":"eeat","severity":"absent"},{"key":"author-credentials","label":"Author bio with credentials","score":0,"detail":"No `.author-bio` / `[itemprop=\"author\"]` element found.","remedy":"Add an author-bio section with the author's name, role, and credentials (degree, years of experience, certifications).","weight":0.13,"category":"eeat","severity":"absent"},{"key":"byline-depth","label":"Byline depth (link + reviewer + date)","score":0,"detail":"no linked byline, no reviewer, no date","remedy":"Strengthen the byline: link author name to an author profile page; add \"reviewed by\" / \"edited by\" markup; mark published + modified dates explicitly.","weight":0.08,"category":"eeat","severity":"absent"},{"key":"brand-entity","label":"Brand recognized as Wikidata entity","score":1,"detail":"Wikidata: Q114424786 — mathematical subtext, which presents an application or an illustration of the subject or of the theo","remedy":null,"weight":0.16,"category":"eeat","severity":"ok"},{"key":"press-mentions","label":"Press / media mentions","score":0,"detail":"0 press-mention pattern(s) matched.","remedy":"Add a \"Featured in\" / \"As seen in\" strip listing publications that have covered you. External recognition is a top authority signal.","weight":0.11,"category":"eeat","severity":"absent"},{"key":"privacy-terms","label":"Privacy + Terms links","score":0,"detail":"Privacy ✗, Terms ✗.","remedy":"Add Privacy Policy and Terms of Service links (typically in the footer). Their absence is a hard trust-floor signal — Google's quality raters down-rank pages that lack them.","weight":0.13,"category":"eeat","severity":"absent"},{"key":"contact-info","label":"Contact information","score":0,"detail":"email ✗, phone ✗, address ✗, no contact link","remedy":"Expose verifiable contact info: an email link, a phone number, and ideally a physical address marked up with `
` or `itemprop=\"address\"`. Anonymous sites read as low-trust.","weight":0.13,"category":"eeat","severity":"absent"}],"category":"eeat"}]},"diagnostics":{"serp":{"ddg":false,"wikipedia":false},"embeddingsLoaded":false,"competitorsFetched":0},"serpContext":{"query":"what is example domain","results":[],"degraded":{"ddg":false,"wikipedia":false},"entities":[{"qid":"Q481","url":"https://en.wikipedia.org/wiki/.xxx","title":".xxx","description":".xxx is a sponsored top-level domain (sTLD) intended as a voluntary option for pornographic websites on the Internet. This option enables website operators to establish a web address like example.xxx instead of example.com. The sponsoring organization is the International Foundat"},{"qid":"Q19652","url":"https://en.wikipedia.org/wiki/Public_domain","title":"Public domain","description":"The public domain (PD) consists of all creative work to which no exclusive intellectual property rights apply. Those rights may have expired, be forfeit, waived or may be inapplicable. Because no one holds the exclusive rights, anyone can legally use or reference those works with"},{"qid":"Q14296","url":"https://en.wikipedia.org/wiki/Top-level_domain","title":"Top-level domain","description":"A top-level domain (TLD) is one of the domains at the highest level in the hierarchical Domain Name System of the Internet after the root domain. The top-level domain names are installed in the root zone of the name space. For all domains in lower levels, it is the last part of t"}]},"semanticVoid":[],"centroidShift":null,"citationVerdict":{"rank":null,"cited":false,"cohort":0,"margin":0},"retrievalRanking":[]}}