AI Overview Checker
Pages with proper schema and clear answer structure are 3.2x more likely to be cited in Google AI Overviews (Frase 2025). Our checker fetches any public URL and runs 10 deterministic signals: schema markup, meta tags, headings, E-E-A-T, freshness. Then you get an AI Citation Score from 0 to 100 with a per-signal checklist and a one-click fix for the most common gap: missing FAQPage schema. Pure HTML parse, no AI, no signup.
How it works
A short, focused workflow — input, run, read the result.
Paste your public URL
Drop the full URL (must start with https://) into the input field. Try a blog post, a product page, or your homepage.
See your AI Citation Score + 10-signal checklist
In 2-5 seconds, you'll get a 0-100 score with a color band and a 10-row ✓/⚠/✗ checklist showing the detected value for each signal.
Click into any ⚠ or ✗ signal to see the fix
Every failing row expands with a one-line plain-English fix. Schema issues specifically link straight to our free Schema Markup Generator. If your page is missing FAQPage schema, you'll get a one-click path to a copy-paste JSON-LD block in 30 seconds.
Re-check after fixing
Hit "Check again" with the same URL after you've shipped the fixes. The score will update, and you can iterate until you're in the green band. No account, no history.
What is an AI Overview, and why does getting cited matter more than ranking?
An AI Overview is the AI-generated answer block Google now places at the top of many search results. Pages cited inside an AI Overview get a visibility boost that is disproportionate to their organic position. The signal set Google uses for citation is partially separate from the ranking algorithm, which is why a page can rank #7 and still be cited.
What this AI Overview checker covers
The 10 on-page signals Google AI Overviews, ChatGPT, and Perplexity read when deciding what to cite.
- FAQPage schema check — presence of FAQPage JSON-LD. Highest-weighted signal (20 points) because FAQ pages are cited 2-4x more often.
- Meta tag presence — title tag and meta description present, within SERP length limits. Affects snippet eligibility inside the AI Overview.
- Heading structure — logical H1 to H2 to H3 hierarchy. AI Overview extractors use headings to find answerable questions in the page.
- E-E-A-T markers — author byline, credentials, organizational authority. Claude in particular weights E-E-A-T heavily in citation choice.
- Freshness signals — publish date, last updated date, and visible time references. Perplexity prioritizes fresh content over older evergreen pages.
- Direct answer density — short, factual answer sentences near the top of the page. The extractable units AI Overviews prefer to cite.
- HowTo schema check — presence of HowTo JSON-LD for procedural pages. Correlates r=0.67 with citation on how-to queries.
- Structured data audit — any other valid JSON-LD types on the page. More valid schema means more entry points for AI extractors.
Who uses this AI Overview checker
Anyone whose traffic depends on Google, ChatGPT, or Perplexity citations needs to know whether their pages qualify.
Your top 50 pages have never been cited in an AI Overview and you suspect missing schema is the cause.
Run the check, find the missing FAQPage or HowTo schema, ship the fix, re-check the score.
You published a HowTo guide last week and want to confirm it qualifies for AI citation.
Check the URL, confirm HowTo schema, add the FAQPage block, watch the score climb into the green band.
A client wants an AI visibility audit across their 100 priority pages.
Bulk run the checks, build the score distribution, ship the audit as a deliverable with fix priorities.
You write tutorials and want to know which posts qualify for HowTo rich results and AI citations.
Check your top 20 tutorials, add HowTo and FAQ schema where missing, capture the citation traffic.
You want your product comparison pages to be cited in ChatGPT and Perplexity answer blocks.
Run the check, add the missing structured data, ship a content refresh that earns the citation.
Your news articles are getting fewer Google referrals since AI Overviews launched and you want to understand why.
Check the top 30 articles, find the schema gaps, ship the fixes, monitor citation share month over month.
Related glossary terms
Want a deeper dive? These glossary entries explain the concepts behind this tool.
Frequently Asked
Questions
Everything you need to know about AI Overviews, AI citation, and the 10-signal audit in 2026.
An AI Overview is the AI-generated answer block that appears at the top of Google search results for many queries. Google launched it broadly in 2024-2025 and it now appears on roughly 30-42% of all queries (SparkToro 2025 study). The block synthesizes information from multiple web pages into a few-paragraph answer with linked sources. The pages it cites get a significant visibility boost. The term has become a generic shorthand for "AI-generated answer" across ChatGPT, Perplexity, Claude, and Copilot as well.
It depends on the engine. Per the Digital Bloom 2025 AI Visibility Report and AI Rank Lab's 10,000-query study: ChatGPT cites Wikipedia and Bing's top results most often (Wikipedia is 47.9% of top citations, 87% of ChatGPT citations match Bing's top 10). Perplexity cites Reddit (46.7% of top citations), real-time content, and pages with strong schema. It's the most "responsive" LLM to AEO signals. Claude emphasizes E-E-A-T (author credentials, methodology, organizational authority). Google AI Overviews pull 93.67% of citations from the top-10 organic results. Only ~11% of domains are cited by BOTH ChatGPT and Perplexity, so optimizing for one engine doesn't guarantee the others. Our checker focuses on the on-page signals (schema, meta, E-E-A-T) that all engines share.
Per AI Rank Lab's 10,000-query study, the strongest correlations are: FAQPage schema presence (r=0.61), Domain Authority 50+ (r=0.54), Content freshness within 6 months (r=0.51), AI bot access in robots.txt (r=0.49), E-E-A-T signals (r=0.47), and Direct answer density (r=0.44). HowTo schema correlates even higher (r=0.67) for procedural "how do I" queries. Our checker focuses on the on-page signals you can control (schema, meta tags, headings, FAQ presence, author markup, date markup). Authority and freshness are tracked in your analytics.
It's a weighted sum of 10-12 deterministic signals, not an AI judgment. Each signal is checked against a clear yes/no/warn rule and given a weight between 4 and 20 points. The final score is Σ(weight × status multiplier), where ✓ = 1.0, ⚠ = 0.5, ✗ = 0.0. The FAQ presence signal has the highest weight (20 points) because FAQPage schema gets cited 2-4x more often (AI Rank Lab 2026). The result is reproducible: paste the same URL tomorrow and you'll get the same score, exactly the property you want from a validation tool.
Yes, completely free. No signup, no email gate, no per-audit cap beyond 10/hour to keep server load manageable. Your URL is fetched server-side by an ephemeral serverless function that runs for the duration of one audit and is then destroyed. The URL is not logged, not stored in a database, and not sent to any AI model (this tool makes zero LLM calls). The HTML we fetch is parsed for the 10 signals and discarded. You can verify by checking Vercel's logs and reading our Privacy Policy.
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