{"slug":"1sBOgqsi6","url":"https://digiocular.com","query":"best web design agency for small businesses","score":62,"createdAt":"Wed Oct 14 2026 08:25:37 GMT+0000 (Coordinated Universal Time)","result":{"liveCheck":null,"liveEngines":[],"rubric":{"overall":62,"summary":{"ok":31,"weak":6,"absent":10,"total":47},"categories":[{"category":"structure","score":81,"signals":[{"key":"json-ld-presence","category":"structure","label":"JSON-LD structured data","score":0.8,"severity":"ok","detail":"2 JSON-LD blocks found.","remedy":null},{"key":"json-ld-validity","category":"structure","label":"JSON-LD validity","score":1,"severity":"ok","detail":"2 of 2 JSON-LD blocks parse cleanly.","remedy":null},{"key":"json-ld-relevance","category":"structure","label":"Schema type matches query intent","score":0.4,"severity":"weak","detail":"Schema types found (Organization, ProfessionalService, WebSite, WebPage, FAQPage) don't match a transactional buyer intent.","remedy":"Add a Product JSON-LD block — the highest-leverage schema type for a \"best web design agency for small busines\" query."},{"key":"faq-schema","category":"structure","label":"FAQ / Q&A schema","score":1,"severity":"ok","detail":"FAQPage / QAPage schema present — directly cited by AI Overviews and Perplexity.","remedy":null},{"key":"h1-quality","category":"structure","label":"H1 quality","score":1,"severity":"ok","detail":"H1: \"A website thatwins customers.\" (29 chars).","remedy":null},{"key":"h2-coverage","category":"structure","label":"H2 subtopic coverage","score":1,"severity":"ok","detail":"8 H2 headings — answer engines decompose a buyer query into subtopics and match each to an H2.","remedy":null},{"key":"lists","category":"structure","label":"Lists (bulleted / numbered)","score":1,"severity":"ok","detail":"13 lists found.","remedy":null},{"key":"tables","category":"structure","label":"Comparison tables","score":0.2,"severity":"weak","detail":"No tables. Comparison / specification tables are heavily cited for product and technical queries.","remedy":"Add a comparison table — engines cite tables nearly verbatim when answering compare/spec queries."},{"key":"alt-text","category":"structure","label":"Image alt-text coverage","score":0.9230769230769231,"severity":"ok","detail":"12 of 13 images have alt text (92%).","remedy":null},{"key":"open-graph","category":"structure","label":"Open Graph metadata","score":1,"severity":"ok","detail":"Open Graph title, description, and image all present.","remedy":null},{"key":"internal-linking","category":"structure","label":"Internal linking quality","score":0.7,"severity":"ok","detail":"122 internal links (122 with descriptive anchors), 38 external.","remedy":null},{"key":"page-weight","category":"structure","label":"Page weight + render-blocking","score":0.7076923076923078,"severity":"ok","detail":"281 KB HTML, 1 blocking script(s), 2 blocking stylesheet(s), 6/13 images without lazy-load.","remedy":null},{"key":"structural-depth","category":"structure","label":"GEO-SFE structural depth (macro/meso/micro)","score":0.8,"severity":"ok","detail":"Macro: max heading depth H3 (H1=1, H2=8, H3=26, H4=0). Meso: 5.9 chunks/section avg. Micro: 0.00% visual emphasis.","remedy":null}]},{"category":"authority","score":44,"signals":[{"key":"outbound-authority-links","category":"authority","label":"Outbound links to authoritative sources","score":0,"severity":"absent","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."},{"key":"citation-density","category":"authority","label":"Inline citations and attributions","score":0,"severity":"absent","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."},{"key":"statistic-density","category":"authority","label":"Statistic density","score":1,"severity":"ok","detail":"61 numerical facts (~3.0 per 100 words).","remedy":null},{"key":"quotations","category":"authority","label":"Expert quotations","score":1,"severity":"ok","detail":"4 blockquotes + 0 long inline quotes.","remedy":null},{"key":"author-byline","category":"authority","label":"Author byline","score":0.6,"severity":"weak","detail":"Author byline only partially marked up.","remedy":"Add a visible author byline (a `<div class=\"byline\">` or `[rel=\"author\"]`) AND a `<meta name=\"author\">` tag."},{"key":"date-markup","category":"authority","label":"Publish + update date markup","score":0,"severity":"absent","detail":"No structured publish date. Freshness ranking can't be applied.","remedy":"Add `<time datetime=\"...\">` for published date AND a `<meta property=\"article:modified_time\">` for updates."},{"key":"freshness","category":"authority","label":"Content freshness","score":0,"severity":"absent","detail":"No parseable date — engines treat undated content as stale.","remedy":"Add a parseable date — `<time datetime=\"2026-01-15\">` or `<meta property=\"article:modified_time\">`."},{"key":"technical-terms","category":"authority","label":"Technical / domain vocabulary","score":1,"severity":"ok","detail":"442 multi-syllable words (~21.4% of total).","remedy":null}]},{"category":"content","score":64,"signals":[{"key":"direct-answer","category":"content","label":"Direct answer in the lead","score":0,"severity":"absent","detail":"0 of 7 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."},{"key":"query-coverage","category":"content","label":"Query-term coverage","score":0.7142857142857143,"severity":"ok","detail":"71% of query terms appear somewhere on the page.","remedy":null},{"key":"entity-coverage","category":"content","label":"Named-entity coverage","score":1,"severity":"ok","detail":"101 distinct proper-noun entities mentioned.","remedy":null},{"key":"readability","category":"content","label":"Readability (Flesch Reading Ease)","score":0.5,"severity":"weak","detail":"Reading-ease score: 48.6 (target 60-70).","remedy":"Page reads too academic — shorter sentences and simpler vocabulary lift citation rate by ~12% (GEO §4.3)."},{"key":"length","category":"content","label":"Content depth","score":1,"severity":"ok","detail":"2064 words. Target 300-2500 — engines bias toward focused depth.","remedy":null},{"key":"info-density","category":"content","label":"Information density","score":1,"severity":"ok","detail":"Unique-word ratio: 46.0% (target 40-60%).","remedy":null},{"key":"definitions","category":"content","label":"Definitional sentences","score":1,"severity":"ok","detail":"7 definitional sentences.","remedy":null},{"key":"bluf-answer","category":"content","label":"BLUF — answer in first 100 words","score":0.3,"severity":"weak","detail":"First 100 words cover 3/7 query terms.","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."},{"key":"mega-page-coverage","category":"content","label":"Mega-page coverage (what/who/how/pricing)","score":1,"severity":"ok","detail":"4/4 facets covered (what ✓, who ✓, how ✓, pricing ✓).","remedy":null},{"key":"youtube-embed","category":"content","label":"YouTube video presence","score":0,"severity":"absent","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."},{"key":"sub-query-coverage","category":"content","label":"Sub-query coverage","score":1,"severity":"ok","detail":"4/4 decomposed sub-questions addressed on the page.","remedy":null}]},{"category":"trust","score":100,"signals":[{"key":"https","category":"trust","label":"HTTPS","score":1,"severity":"ok","detail":"Page served over HTTPS.","remedy":null},{"key":"canonical","category":"trust","label":"Canonical URL","score":1,"severity":"ok","detail":"Canonical: https://www.digiocular.com","remedy":null},{"key":"viewport","category":"trust","label":"Mobile-friendly viewport","score":1,"severity":"ok","detail":"Viewport meta tag present.","remedy":null},{"key":"twitter-card","category":"trust","label":"Twitter Card","score":1,"severity":"ok","detail":"Twitter Card metadata present.","remedy":null},{"key":"meta-description","category":"trust","label":"Meta description","score":1,"severity":"ok","detail":"Meta description: 151 chars (target 50-160).","remedy":null},{"key":"ai-bot-access","category":"trust","label":"AI retrieval-bot access (robots.txt)","score":1,"severity":"ok","detail":"robots.txt allows all AI retrieval bots — your pages are eligible for citation.","remedy":null},{"key":"llms-txt-presence","category":"trust","label":"llms.txt present at /llms.txt","score":1,"severity":"ok","detail":"/llms.txt found and non-empty — IDE agents (Cursor, Claude Code, Copilot, Windsurf) and Claude.ai will use it for retrieval.","remedy":null}]},{"category":"eeat","score":36,"signals":[{"key":"first-person","category":"eeat","label":"First-person language","score":0.7,"severity":"ok","detail":"62 first-person pronouns (3.0% of words). Target 0.5-3%.","remedy":null},{"key":"case-study-evidence","category":"eeat","label":"Case study / concrete examples","score":0.3333333333333333,"severity":"weak","detail":"1 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."},{"key":"author-credentials","category":"eeat","label":"Author bio with credentials","score":0,"severity":"absent","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)."},{"key":"byline-depth","category":"eeat","label":"Byline depth (link + reviewer + date)","score":0,"severity":"absent","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."},{"key":"brand-entity","category":"eeat","label":"Brand recognized as Wikidata entity","score":0,"severity":"absent","detail":"No Wikidata entry matched. AI engines preferentially cite brands they recognize as knowledge-graph entities.","remedy":"Create a Wikidata entry for \"digiocular\" (and a Wikipedia article when notable). The single highest-leverage move for \"is this a real, recognized brand?\" — answer engines key off knowledge graph membership."},{"key":"press-mentions","category":"eeat","label":"Press / media mentions","score":0,"severity":"absent","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."},{"key":"privacy-terms","category":"eeat","label":"Privacy + Terms links","score":1,"severity":"ok","detail":"Privacy ✓, Terms ✓.","remedy":null},{"key":"contact-info","category":"eeat","label":"Contact information","score":0.8,"severity":"ok","detail":"email ✓, phone ✓, address ✗, contact link ✓","remedy":null}]}],"signals":[{"key":"json-ld-presence","category":"structure","label":"JSON-LD structured data","score":0.8,"severity":"ok","detail":"2 JSON-LD blocks found.","remedy":null},{"key":"json-ld-validity","category":"structure","label":"JSON-LD validity","score":1,"severity":"ok","detail":"2 of 2 JSON-LD blocks parse cleanly.","remedy":null},{"key":"json-ld-relevance","category":"structure","label":"Schema type matches query intent","score":0.4,"severity":"weak","detail":"Schema types found (Organization, ProfessionalService, WebSite, WebPage, FAQPage) don't match a transactional buyer intent.","remedy":"Add a Product JSON-LD block — the highest-leverage schema type for a \"best web design agency for small busines\" query."},{"key":"faq-schema","category":"structure","label":"FAQ / Q&A schema","score":1,"severity":"ok","detail":"FAQPage / QAPage schema present — directly cited by AI Overviews and Perplexity.","remedy":null},{"key":"h1-quality","category":"structure","label":"H1 quality","score":1,"severity":"ok","detail":"H1: \"A website thatwins customers.\" (29 chars).","remedy":null},{"key":"h2-coverage","category":"structure","label":"H2 subtopic coverage","score":1,"severity":"ok","detail":"8 H2 headings — answer engines decompose a buyer query into subtopics and match each to an H2.","remedy":null},{"key":"lists","category":"structure","label":"Lists (bulleted / numbered)","score":1,"severity":"ok","detail":"13 lists found.","remedy":null},{"key":"tables","category":"structure","label":"Comparison tables","score":0.2,"severity":"weak","detail":"No tables. Comparison / specification tables are heavily cited for product and technical queries.","remedy":"Add a comparison table — engines cite tables nearly verbatim when answering compare/spec queries."},{"key":"alt-text","category":"structure","label":"Image alt-text coverage","score":0.9230769230769231,"severity":"ok","detail":"12 of 13 images have alt text (92%).","remedy":null},{"key":"open-graph","category":"structure","label":"Open Graph metadata","score":1,"severity":"ok","detail":"Open Graph title, description, and image all present.","remedy":null},{"key":"internal-linking","category":"structure","label":"Internal linking quality","score":0.7,"severity":"ok","detail":"122 internal links (122 with descriptive anchors), 38 external.","remedy":null},{"key":"page-weight","category":"structure","label":"Page weight + render-blocking","score":0.7076923076923078,"severity":"ok","detail":"281 KB HTML, 1 blocking script(s), 2 blocking stylesheet(s), 6/13 images without lazy-load.","remedy":null},{"key":"structural-depth","category":"structure","label":"GEO-SFE structural depth (macro/meso/micro)","score":0.8,"severity":"ok","detail":"Macro: max heading depth H3 (H1=1, H2=8, H3=26, H4=0). Meso: 5.9 chunks/section avg. Micro: 0.00% visual emphasis.","remedy":null},{"key":"outbound-authority-links","category":"authority","label":"Outbound links to authoritative sources","score":0,"severity":"absent","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."},{"key":"citation-density","category":"authority","label":"Inline citations and attributions","score":0,"severity":"absent","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."},{"key":"statistic-density","category":"authority","label":"Statistic density","score":1,"severity":"ok","detail":"61 numerical facts (~3.0 per 100 words).","remedy":null},{"key":"quotations","category":"authority","label":"Expert quotations","score":1,"severity":"ok","detail":"4 blockquotes + 0 long inline quotes.","remedy":null},{"key":"author-byline","category":"authority","label":"Author byline","score":0.6,"severity":"weak","detail":"Author byline only partially marked up.","remedy":"Add a visible author byline (a `<div class=\"byline\">` or `[rel=\"author\"]`) AND a `<meta name=\"author\">` tag."},{"key":"date-markup","category":"authority","label":"Publish + update date markup","score":0,"severity":"absent","detail":"No structured publish date. Freshness ranking can't be applied.","remedy":"Add `<time datetime=\"...\">` for published date AND a `<meta property=\"article:modified_time\">` for updates."},{"key":"freshness","category":"authority","label":"Content freshness","score":0,"severity":"absent","detail":"No parseable date — engines treat undated content as stale.","remedy":"Add a parseable date — `<time datetime=\"2026-01-15\">` or `<meta property=\"article:modified_time\">`."},{"key":"technical-terms","category":"authority","label":"Technical / domain vocabulary","score":1,"severity":"ok","detail":"442 multi-syllable words (~21.4% of total).","remedy":null},{"key":"direct-answer","category":"content","label":"Direct answer in the lead","score":0,"severity":"absent","detail":"0 of 7 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."},{"key":"query-coverage","category":"content","label":"Query-term coverage","score":0.7142857142857143,"severity":"ok","detail":"71% of query terms appear somewhere on the page.","remedy":null},{"key":"entity-coverage","category":"content","label":"Named-entity coverage","score":1,"severity":"ok","detail":"101 distinct proper-noun entities mentioned.","remedy":null},{"key":"readability","category":"content","label":"Readability (Flesch Reading Ease)","score":0.5,"severity":"weak","detail":"Reading-ease score: 48.6 (target 60-70).","remedy":"Page reads too academic — shorter sentences and simpler vocabulary lift citation rate by ~12% (GEO §4.3)."},{"key":"length","category":"content","label":"Content depth","score":1,"severity":"ok","detail":"2064 words. Target 300-2500 — engines bias toward focused depth.","remedy":null},{"key":"info-density","category":"content","label":"Information density","score":1,"severity":"ok","detail":"Unique-word ratio: 46.0% (target 40-60%).","remedy":null},{"key":"definitions","category":"content","label":"Definitional sentences","score":1,"severity":"ok","detail":"7 definitional sentences.","remedy":null},{"key":"bluf-answer","category":"content","label":"BLUF — answer in first 100 words","score":0.3,"severity":"weak","detail":"First 100 words cover 3/7 query terms.","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."},{"key":"mega-page-coverage","category":"content","label":"Mega-page coverage (what/who/how/pricing)","score":1,"severity":"ok","detail":"4/4 facets covered (what ✓, who ✓, how ✓, pricing ✓).","remedy":null},{"key":"youtube-embed","category":"content","label":"YouTube video presence","score":0,"severity":"absent","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."},{"key":"sub-query-coverage","category":"content","label":"Sub-query coverage","score":1,"severity":"ok","detail":"4/4 decomposed sub-questions addressed on the page.","remedy":null},{"key":"https","category":"trust","label":"HTTPS","score":1,"severity":"ok","detail":"Page served over HTTPS.","remedy":null},{"key":"canonical","category":"trust","label":"Canonical URL","score":1,"severity":"ok","detail":"Canonical: https://www.digiocular.com","remedy":null},{"key":"viewport","category":"trust","label":"Mobile-friendly viewport","score":1,"severity":"ok","detail":"Viewport meta tag present.","remedy":null},{"key":"twitter-card","category":"trust","label":"Twitter Card","score":1,"severity":"ok","detail":"Twitter Card metadata present.","remedy":null},{"key":"meta-description","category":"trust","label":"Meta description","score":1,"severity":"ok","detail":"Meta description: 151 chars (target 50-160).","remedy":null},{"key":"ai-bot-access","category":"trust","label":"AI retrieval-bot access (robots.txt)","score":1,"severity":"ok","detail":"robots.txt allows all AI retrieval bots — your pages are eligible for citation.","remedy":null},{"key":"llms-txt-presence","category":"trust","label":"llms.txt present at /llms.txt","score":1,"severity":"ok","detail":"/llms.txt found and non-empty — IDE agents (Cursor, Claude Code, Copilot, Windsurf) and Claude.ai will use it for retrieval.","remedy":null},{"key":"first-person","category":"eeat","label":"First-person language","score":0.7,"severity":"ok","detail":"62 first-person pronouns (3.0% of words). Target 0.5-3%.","remedy":null},{"key":"case-study-evidence","category":"eeat","label":"Case study / concrete examples","score":0.3333333333333333,"severity":"weak","detail":"1 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."},{"key":"author-credentials","category":"eeat","label":"Author bio with credentials","score":0,"severity":"absent","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)."},{"key":"byline-depth","category":"eeat","label":"Byline depth (link + reviewer + date)","score":0,"severity":"absent","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."},{"key":"brand-entity","category":"eeat","label":"Brand recognized as Wikidata entity","score":0,"severity":"absent","detail":"No Wikidata entry matched. AI engines preferentially cite brands they recognize as knowledge-graph entities.","remedy":"Create a Wikidata entry for \"digiocular\" (and a Wikipedia article when notable). The single highest-leverage move for \"is this a real, recognized brand?\" — answer engines key off knowledge graph membership."},{"key":"press-mentions","category":"eeat","label":"Press / media mentions","score":0,"severity":"absent","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."},{"key":"privacy-terms","category":"eeat","label":"Privacy + Terms links","score":1,"severity":"ok","detail":"Privacy ✓, Terms ✓.","remedy":null},{"key":"contact-info","category":"eeat","label":"Contact information","score":0.8,"severity":"ok","detail":"email ✓, phone ✓, address ✗, contact link ✓","remedy":null}]},"citationVerdict":{"rank":null,"cited":false,"cohort":0,"margin":0},"fixKit":{"headline":"Mid-ranked (62/100) — 8 patches to close the citation gap","patches":[{"key":"primary-schema","title":"Product JSON-LD","kind":"schema-json-ld","priority":"high","content":"<script type=\"application/ld+json\">\n{\n  \"@context\": \"https://schema.org\",\n  \"@type\": \"Product\",\n  \"name\": \"A website thatwins customers.\",\n  \"description\": \"Custom websites from $349 USD, built by Digiocular, an AI-native agency in Manila, Philippines, for businesses in India, the Philippines and worldwide.\",\n  \"url\": \"https://digiocular.com\",\n  \"brand\": {\n    \"@type\": \"Brand\",\n    \"name\": \"Digiocular\"\n  }\n}\n</script>","explainer":"A Product schema is the strongest single AEO signal for a transactional query. Paste this in the <head>."},{"key":"organization-schema","title":"Organization JSON-LD","kind":"schema-json-ld","priority":"medium","content":"<script type=\"application/ld+json\">\n{\n  \"@context\": \"https://schema.org\",\n  \"@type\": \"Organization\",\n  \"name\": \"Digiocular\",\n  \"url\": \"https://digiocular.com\",\n  \"logo\": \"https://digiocular.com/logo.png\",\n  \"sameAs\": [\n    \"https://twitter.com/your-handle\",\n    \"https://linkedin.com/company/your-org\"\n  ]\n}\n</script>","explainer":"Organization schema gives the engine an E-E-A-T anchor — pages without one are treated as anonymous."},{"key":"tables","title":"Comparison tables","kind":"structure","priority":"medium","content":"Add a comparison table — engines cite tables nearly verbatim when answering compare/spec queries.","explainer":"No tables. Comparison / specification tables are heavily cited for product and technical queries."},{"key":"outbound-authority-links","title":"Outbound links to authoritative sources","kind":"structure","priority":"high","content":"Add 2-3 outbound citations to .edu / .gov / known publishers. The GEO paper measured this as the #2 citation-lift factor.","explainer":"0 links to authoritative domains (.edu, .gov, named sources)."},{"key":"citation-density","title":"Inline citations and attributions","kind":"structure","priority":"high","content":"Add inline citations ([1], [2]) or attribution phrases (\"according to X\"). GEO factor #1 for credibility-weighted citation.","explainer":"0 bracketed citations + 0 attribution phrases (per 200 words: 0%)."},{"key":"author-byline","title":"Author byline","kind":"structure","priority":"medium","content":"Add a visible author byline (a `<div class=\"byline\">` or `[rel=\"author\"]`) AND a `<meta name=\"author\">` tag.","explainer":"Author byline only partially marked up."},{"key":"date-markup","title":"Publish + update date markup","kind":"structure","priority":"high","content":"Add `<time datetime=\"...\">` for published date AND a `<meta property=\"article:modified_time\">` for updates.","explainer":"No structured publish date. Freshness ranking can't be applied."},{"key":"freshness","title":"Content freshness","kind":"structure","priority":"high","content":"Add a parseable date — `<time datetime=\"2026-01-15\">` or `<meta property=\"article:modified_time\">`.","explainer":"No parseable date — engines treat undated content as stale."}]},"comparisonPages":[]}}