ChatGPT answers, unedited

Yes. The category you’re looking for is usually called GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or AI search visibility.

There are now tools that go beyond “does my brand get mentioned?” and actually audit/score individual pages for their likelihood of being retrieved, cited, and used in AI-generated answers. The market is still pretty immature, though—there isn't yet a universally accepted “AI citation score” equivalent to an SEO Domain Rating. Shadow arXiv

Tools worth looking at

• AI Search Visibility — probably closest to what you described. It evaluates pages across dimensions such as crawlability, content depth, snippet/extractability, structured data, trust signals, and attribution risk, then produces an overall score. AISearchVisibility
• BlueJar — focuses more on actual AI visibility and citation tracking across ChatGPT, Perplexity, Gemini, and Copilot, then maps which sources are getting cited and what you need to change. BlueJar
• Profound / Peec AI / Otterly / Scrunch — stronger if your goal is monitoring actual AI answers at scale: prompts → mentions/citations → competitors → share of voice. They tend to be less about a single page's intrinsic “citation probability” score. A recent comparison of the category puts these among the main platforms. Elmo Kitbase
• AuditAE — takes a more explicit audit approach, looking at technical foundations, on-page structure, topical authority, off-page signals, and distribution. AuditAE

The important distinction

There are really two different scores you could be asking for:

1. “How AI-ready is this page?”

URL → score 0–100 → recommendations

Things like:

• Can AI crawlers access it?
• Is the answer explicit and extractable?
• Does it directly answer the query?
• Are facts supported?
• Is there original data/evidence?
• Is the author/entity trustworthy?
• Is the page structured clearly?
• Is it fresh?
• Does schema help?
• Can an LLM easily quote a passage?

Tools like AI Search Visibility are closest to this.

2. “How likely is this page to actually be cited?”

URL + target queries → simulate/measure AI engines → citation probability

This is considerably more valuable, but harder. You'd want to test the page against actual prompts in ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, etc., and compare it against the pages that those engines actually cite.

That distinction matters because research is finding that citation isn't simply a page-quality score. Topical relevance, retrieval position, freshness, completeness, and the competitive set all affect whether a source gets cited. arXiv arXiv

If you're thinking about building this

I actually think there's an interesting product gap here.

A genuinely useful “AI Citation Score” could look something like:

Page: /best-project-management-software
AI Citation Score: 72/100

ChatGPT: 81
Perplexity: 69
Google AI: 74
Gemini: 63

Why you score well

• Strong topical match
• Clear definitions
• Good comparison table
• Recent data
• Author credentials

Why you lose citations

• Competitor X has more first-party data
• Your answer to “pricing” is buried
• Missing explicit methodology
• Two important claims lack supporting sources

Estimated citation likelihood: 18%
Top competing sources: X, Y, Z
Highest-impact changes: 3

That's much more actionable than a generic “GEO score.”

And there's some empirical support for this direction: a 2026 study found that high-influence cited pages tended to be longer, more structured, semantically aligned, and richer in extractable evidence, while another controlled study found topical relevance and retrieval position to be particularly important. arXiv arXiv

If you tell me what kind of pages you have (SaaS, ecommerce, publisher, local, etc.), I can also give you a shortlist of the 3–5 tools I'd actually test, specifically for scoring your existing pages rather than merely tracking brand mentions.

Yes. The category is usually called AI search visibility, GEO (Generative Engine Optimization), or AEO (Answer Engine Optimization).

There are actually two different kinds of tools, and the distinction matters:

For your exact question

A tool called AI Search Visibility is unusually close to what you're describing. It takes a specific URL and gives it an AI Readiness / Citeability score, evaluating things like crawlability, content/intent, E-E-A-T, schema, and how easily an AI can extract and safely cite the page. It currently claims a 0–10 score and 120+ checks. www.aisearchvisibility.ai

There are also:

• SearchScore — broader site-level AI visibility auditing, with 250+ signals and ongoing tracking across ChatGPT, Claude, Gemini, Perplexity, etc. searchscore.io
• OtterlyAI — more focused on actually tracking whether your brand/site gets mentioned and cited across AI search engines, plus content audits. otterly.ai
• Ahrefs AI Visibility Checker — useful for measuring actual AI mentions/citations and seeing which pages/domains are being cited. ahrefs.com
• Yogoo AI — gives a 0–100 visibility score and shows where competitors are being cited instead of you. yogoo.ai

But there's an important limitation

A “likelihood of being cited” score isn't the same thing as measuring actual citations.

For example, a page might get a 9/10 on technical/content criteria but never be cited because an AI engine has better sources available. Conversely, a relatively ordinary page can get cited frequently because the site has strong authority or because it uniquely answers a particular question.

So if you're evaluating your pages, I'd use both:

1. Page-level score:

“How citation-ready is this URL?”

2. Real-world citation rate:

“When AI answers the questions this page should answer, how often does it actually cite us?”

The second metric is much closer to the equivalent of organic search rankings, while the first is more like an SEO technical/content audit.

If you're considering building or buying a tool for your team, I can also compare the current 2026 GEO platforms (Profound, Otterly, Scrunch, Ahrefs, Peec, etc.) specifically on whether they score individual URLs vs. merely track brand citations.

Yes. The category you’re looking for is usually called GEO (Generative Engine Optimization), AI visibility, or AI citeability.

A few tools specifically score individual URLs/pages for how likely they are to be understood and cited by answer engines:

• Frase GEO Score Checker — probably the easiest place to start. Paste a page URL and it grades how ready the page is to be cited by ChatGPT, Perplexity, and Claude, with recommendations. Frase
• AI Search Visibility — more detailed page-level audit: 120+ checks covering indexability, intent, trust/E-E-A-T, schema, citeability, and risk, producing a 0–10 AI Citeability Score. AI Search Visibility AI Search Visibility
• Sona — has a published 209-point / 35-check rubric specifically designed around whether answer engines can fetch, parse, trust, and cite a page. This is particularly interesting if you want to build your own scoring methodology. Sona
• SEObolt GEO Score — scores pages across content structure, evidence/citations, technical accessibility, E-E-A-T, freshness, and writing quality. SEObolt
• GEOSource — gives a page-level score with components such as answerability, citation quality, definitions, readability, and AI accessibility. GeoSource.ai
• CitationDesk — a simpler 0–100 “citation readiness” score based on SEO foundation, GEO readiness, entity coherence, and bot-crawl health. CitationDesk

One important distinction

There are really two different things you can measure:

1. “Is this page structurally likely to be cited?”
Tools like Frase, Sona, AI Search Visibility, and SEObolt attempt to predict this from the page itself.

2. “Is this page actually being cited?”
Tools like EdenRank, CitedSpy, and other AI-visibility trackers run real prompts through multiple answer engines and record the sources they actually cite. EdenRank CitedSpy

The second is arguably the more valuable KPI. Recent research also suggests that being mentioned, being recommended, and having your own website cited are distinct outcomes. Robot Visible

If you're evaluating this for your own site at scale, I’d look for a tool that gives you both a page-level “citation readiness” score and actual citation data. That lets you answer:

“This page scores 82/100 for AI citeability, and here are the 14 prompts where ChatGPT/Perplexity/Gemini actually cited it.”

If you tell me roughly how many pages you have (e.g. 100, 10K, 1M) and whether you're looking for a tool to buy vs. something you could build internally, I can narrow this down considerably.

Yes. There are now several tools designed to estimate GEO (Generative Engine Optimization) / AI visibility — essentially, how likely a page is to be retrieved, understood, and cited by AI answer engines like ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews. The category is still evolving, so treat scores as directional rather than a guaranteed prediction. arXiv

Some options:

When evaluating these tools, I’d look beyond the headline score and check whether they measure:

• Answerability: Does the page answer the likely user question immediately?
• Extractability: Can an AI system pull a clean, self-contained passage from it?
• Evidence: Are claims supported by data, sources, examples, or references?
• Entity clarity: Does the page clearly establish who/what the content is about?
• Technical accessibility: Can AI crawlers access and parse the content?
• Freshness: Is the content updated and date-signaled?

A practical workflow is:

1. Run your top 20–50 money pages through one of these graders.
2. Compare the lowest-scoring pages against pages that already get traffic/leads.
3. Fix structural issues first (clear answers, definitions, tables, FAQs, citations, schema).
4. Then track whether AI engines actually cite you for target queries.

One caveat: no tool can truly know whether ChatGPT or another engine will cite a page in every future answer. AI citation behavior is probabilistic and depends on the query, competitors, retrieval systems, and model updates. arXiv

If you tell me your CMS (WordPress, Webflow, Shopify, custom, etc.) and whether you care more about ChatGPT citations, AI Overviews, Perplexity, or overall visibility, I can suggest the best fit.

Yes. The category you’re looking for is generally called GEO (Generative Engine Optimization), AI visibility, or AI citability.

There are now tools that specifically score an individual page for how likely it is to be understood, extracted, trusted, and cited by AI answer engines such as ChatGPT, Perplexity, Claude, and Google AI Overviews.

A few worth looking at:

• AI Search Visibility — Probably closest to exactly what you described. It gives each URL an AI Readiness score from 0–10, with separate scores for indexability, intent/value, E-E-A-T, schema, and AI citeability, plus prioritized fixes. www.aisearchvisibility.ai
• Rankio — Has a Citability Score out of 100 and compares your page against competing pages for the same query. It specifically evaluates information density, evidence, sourcing, answer structure, expertise, and machine readability. rankio.proanswervisibilitylab.comwww.ahoylighthouse.com
• GEOSource — Scores pages on things like answerability, citation quality, definitions, readability, and AI accessibility. It also has citation research behind its scoring. geosource.ai
• Context.dev's GEO Checker — A free URL checker specifically positioned as a research-backed GEO score for ChatGPT, Perplexity, Google AI Overviews, and Copilot. www.context.dev
• Answer Visibility Lab — Gives a 100-point score across AI crawlability, sitemap/llms.txt, entity clarity, answer extractability, citation-worthiness, and freshness. answervisibilitylab.com

One important distinction

There are really two different things these tools measure:

1. "Is this page citation-worthy?"
A page-level audit: If an AI encounters this page, how good a source is it?
→ Rankio, AI Search Visibility, GEOSource, etc.

2. "Are AI engines actually citing us?"
They run real prompts against AI engines and measure whether your domain appears as a source.
→ Tools such as Lighthouse and GEO Studio focus more on this. www.ahoylighthouse.com

The best setup is actually to use both. An audit score tells you why a page might not be cited; live citation monitoring tells you whether the changes actually caused AI engines to cite it.

And I'd be a little skeptical of treating any single "AI score" as an objective probability of citation. The field is still young, and different engines behave differently. Even Context.dev explicitly describes its score as a directional signal rather than a fixed standard. www.context.dev

If you're asking because you want to build something like this for your own pages, I can also break down what the scoring model should actually measure and which signals I'd use to produce a defensible 0–100 "AI Source Likelihood" score.

Yes. What you’re looking for is usually called a GEO/AEO (Generative Engine Optimization / Answer Engine Optimization) page-level scorer.

A few tools are specifically built around the question “How likely is this page to be cited by AI answer engines?”:

• AEOCrawler — probably the closest match to your question. It scores individual pages 0–100 for “citability”, using nine dimensions, then lets you verify the score against live ChatGPT/Perplexity citations. It’s free to start without signup. aeocrawler.com
• Frase GEO Score Checker — page-level score for readiness to be cited by ChatGPT, Perplexity and Claude, with recommendations for improvement. www.frase.io
• GEO IQ — combines an AI-powered “answerable/factual/citation-worthy” score with technical crawling and actual AI citation measurement. geo.id8s.ai
• AEO Platform — more of a full SEO/AEO workflow. Its page optimizer scores structure, authority, freshness, entity clarity, and machine parsability, alongside actual citation monitoring. www.aeo-platform.com
• OtterlyAI — broader AI-search monitoring, but it also offers a predictive page-level score for crawlability, AI readiness and citation potential. otterly.ai
• Surface Rank — gives an AI visibility/citability score and combines it with observed AI-agent traffic and actual citations. www.surfacerank.com

One important distinction

I'd separate “AI citation readiness” from “actual AI citation performance.”

A page can score 90/100 because it's well structured, authoritative, fresh, etc., but that doesn't mean ChatGPT or Perplexity will actually cite it. The strongest platforms therefore do both:

Page score → actual prompts → actual citations → competitor comparison → recommendations

For example, Scrunch tracks the actual pages/domains being cited in AI answers, while HubSpot's AEO product similarly combines an AI visibility score with citation analysis. aeocrawler.comwww.frase.iogeo.id8s.aiwww.surfacerank.comscrunch.com

If you're evaluating these because you want to build this capability into your own product/site, I can also break down what the scoring algorithm should actually measure (crawlability, passage-level answerability, entity clarity, evidence, freshness, citations/backlinks, schema, etc.) and which parts can be measured deterministically versus with an LLM.

Yes. The category you're looking for is usually called GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or AI search visibility.

There are actually two different kinds of tools, and the distinction matters:

The closest matches to what you're describing

1. GeoSource — probably the closest fit.
It lets you enter a URL and gives a Citation Readiness Score specifically intended to predict AI citation likelihood. It evaluates things like answerability, citation quality, definitions, readability, and AI accessibility. It also distinguishes this from simply measuring whether you're currently being cited. geosource.ai

GeoSource — free GEO scan

2. Frase GEO Score — another very direct option.
Its free checker takes a page URL and grades how ready that page is to be cited by ChatGPT, Perplexity, and Claude, with recommendations for improvement. www.frase.io

Frase GEO Score Checker

3. GEO Toolbox — more focused on the underlying citability signals.
It scores URLs on Citability and AI Readability, including things such as bot accessibility, JavaScript rendering, freshness, schema, and answer-first formatting. It also lets you see actual citations across multiple engines. geotoolbox.ai

GEO Toolbox

If you're evaluating a whole site

I'd look at Profound, Peec AI, Otterly, or Scrunch. Those are more about observed AI visibility—running a set of queries against AI engines and measuring mentions, citations, competitors, share of voice, etc.—rather than giving every URL a theoretical "this page is 82% likely to be cited" score. www.elmohq.com

The important distinction is:

“Citation readiness” ≠ “actual citation visibility.”

A page can score highly on structural/citability signals but never get cited for your target questions. Conversely, a page can have mediocre conventional SEO characteristics and still get cited because it contains exactly the answer an AI engine needs. Current tools increasingly measure both sides. geosource.ai

If you're thinking about building this internally

This is actually a pretty interesting scoring problem. I'd model a page's AI Source Likelihood Score around:

• Answerability — does it directly answer the query?
• Extractability — can an LLM pull a self-contained passage from it?
• Source quality — does the page cite credible primary/secondary sources?
• Definition density — does it clearly establish facts/terms?
• Structural clarity — headings, tables, lists, concise sections
• Freshness
• Crawl/accessibility — can AI crawlers actually retrieve it?
• Entity/topic alignment
• Originality — unique data, research, examples, etc.
• Observed citation history — whether AI engines have actually cited the URL

And I'd keep predicted citation likelihood separate from observed citation rate. That's probably the most useful distinction if you're trying to score thousands of pages.

If you tell me what kind of site/pages you're working with (e.g. SaaS, publisher, ecommerce, docs), I can also give you a shortlist of the 3–5 tools I'd actually test, including which ones score individual URLs versus merely tracking brand visibility.

Yes. This is an emerging category usually called GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or AI visibility/citability scoring. These tools try to estimate how likely a page is to be understood, retrieved, and cited by AI answer engines like ChatGPT, Perplexity, Gemini, and Google AI Overviews. checkaeo.aiwww.surfacerank.com

A few tools worth looking at:

A good scorecard should evaluate more than traditional SEO. The signals that tend to matter for AI citation likelihood include:

• Can AI crawlers access the page? (robots rules, indexing, crawlability)
• Is the content easy to quote? (clear definitions, concise answers, lists, tables)
• Does the page demonstrate authority? (authors, citations, credentials, dates)
• Are entities clearly defined? (organization/person/product relationships)
• Is structured data present? (Schema.org markup)
• Does the page directly answer questions users ask AI?
• Does the content contain unique, verifiable information?

One caveat: these scores are predictive, not a true probability that ChatGPT or another engine will cite a page. The actual systems use proprietary retrieval and ranking processes, so a page with a 95/100 audit score is not guaranteed to appear. The most valuable tools are ones that show why they gave the score and provide specific fixes rather than just a number. visibilityiq.io

If you’re evaluating this for a company site, I’d prioritize a tool that can:

1. score every important URL,
2. compare competitors,
3. track actual AI citations over time,
4. connect recommendations back to specific content changes. checkaeo.aiwww.surfacerank.com

Yes. There’s now a growing category for this, usually called GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or AI search visibility.

If your specific question is “Can I give this URL a page-level score for how likely ChatGPT/Perplexity/Gemini/etc. are to cite it?”, these are worth looking at:

One important distinction: there are really two different things you can score.

1. Citation readiness / potential — “Given the content and technical characteristics of this page, how citable does it appear to be?”
2. Observed citation performance — “When we actually ask hundreds of relevant questions, how often does an AI engine cite this page?”

The second is much more meaningful. A page can score 90/100 on an audit and still never get cited because competitors have stronger evidence, authority, or topical relevance.

There is also emerging research supporting this distinction: recent work separates citation selection (the AI chooses your page as a source) from citation absorption (the answer actually uses the information from your page). arxiv.org

If you're thinking about building this internally

I'd actually avoid calling it simply an “AI SEO score.” A useful internal score could be something like:

AI Citation Potential =

• Query/intent alignment
• Answer extractability
• Factual specificity
• Evidence/citations
• Entity clarity
• Topical completeness
• Authority/E-E-A-T signals
• Technical crawlability
• Structured data
• Freshness

…and then separately measure actual citation rate by running your target queries through the relevant answer engines.

If you tell me what kind of pages you have (e.g. ecommerce product pages, SaaS landing pages, healthcare, publishers, documentation), I can recommend the best existing tool—or sketch out a scoring rubric you could use to evaluate 1,000+ pages automatically.

Yes. This is becoming a real category, usually called GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or AI search visibility.

There are two slightly different things you can measure:

1. “How likely is this page to be cited?” — a page-level score/audit.
2. “Is this page actually being cited?” — monitoring real ChatGPT/Perplexity/Google AI answers.

Tools worth looking at

• Frase GEO Score Checker — probably the closest match to your wording. You paste a URL and it gives the page a GEO score for how ready it is to be cited by ChatGPT, Perplexity, and Claude, with recommendations for improvement. They currently offer a free first result. www.frase.io

• OtterlyAI — more comprehensive. It has a GEO Content Check and audits pages against 20+ factors, but its bigger strength is measuring whether your URLs are actually being cited across ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini and Copilot. otterly.ai

• SearchScore — focused specifically on AI search visibility and evaluates whether AI systems can find, extract, and trust your content—the three stages that determine whether a page can become a source. searchscore.io

One important caveat

I wouldn't treat any vendor's "AI citation score" as an authoritative probability like “this page has a 73% chance of being cited.” There isn't a universal scoring system across answer engines. Research published in 2026 suggests citation selection and the degree to which a cited page actually contributes to the answer are separate phenomena. arxiv.org

So, if you're evaluating a large set of your own pages, I'd ideally want a tool that gives you both:

Page-level readiness score
→ crawlability
→ extractability
→ direct answers to questions
→ structure/headings
→ factual evidence
→ entity/context signals
→ authority/trust
→ freshness

+ actual citation data
→ which prompts trigger the page
→ which engines cite it
→ competitors cited instead
→ citation frequency
→ what portion of the answer comes from your page

Frase is the quickest thing I'd test for the first part; OtterlyAI is more interesting if you're trying to build an ongoing AI-search measurement program.

If you tell me what kind of site/pages you're working with and roughly how many URLs, I can also recommend the best tool specifically for scoring an entire content library rather than individual pages.

Yes. There are now tools specifically aimed at AI search / Answer Engine Optimization (AEO/GEO), but there’s an important distinction:

• “Will AI engines cite this particular page?” → page-level scoring/auditing
• “How visible is our brand across AI answers?” → brand/domain-level tracking
• “Why are competitors getting cited instead of us?” → competitive/prompt analysis

The closest match to what you're describing

AI Search Visibility is probably the most literal fit. You paste in a URL and it gives the page an AI Readiness score (0–10), identifies blockers, and provides prioritized fixes. It specifically evaluates likelihood of being cited by ChatGPT, Google AI Overviews, and Perplexity. www.aisearchvisibility.ai

More established SEO platforms

Semrush AI Visibility is broader. Its AI Visibility Toolkit gives an AI Visibility Score (0–100) and shows mentions, citations, cited pages, competitors, and the prompts where you're appearing or missing. Its Content Toolkit also analyzes content against factors correlated with higher AI citation rates. www.semrush.com

Ahrefs Brand Radar is another strong option. It tracks AI visibility across ChatGPT, Perplexity, Gemini, Copilot, Google AI Overviews/AI Mode and others, including which specific pages get cited. It also distinguishes between pages AI found/retrieved and pages it actually cited. ahrefs.com

That distinction is particularly useful: a page can be relevant enough for an AI engine to retrieve but not authoritative/clear/useful enough to make the final citation.

If you're trying to build an internal scoring system

I wouldn't rely on a single vendor's proprietary score. I'd create something like:

AI Citation Potential Score = 0–100

with components such as:

Then validate the score against actual citation frequency across a set of representative prompts.

That's ultimately more interesting than simply asking an LLM to "grade this page for AI." The strongest signal is: given 50–500 realistic questions, how often does this URL actually get retrieved and cited, and what characteristics distinguish the cited pages from the non-cited ones?

If you're asking because you want a tool that can crawl your entire site and give every URL an “AI citation likelihood” score, that's a narrower product category—and I can compare what's available right now and tell you which ones actually do page-level scoring rather than just brand visibility.

Yes. The category you’re looking for is usually called GEO (Generative Engine Optimization), AEO (Answer Engine Optimization), or AI search visibility.

A few tools now specifically score individual pages for how “citeable” they are:

• Frase GEO Score Checker — probably the easiest starting point. You paste a URL and it grades how ready the page is to be cited by ChatGPT, Perplexity, and Claude, with recommendations.
• AI Search Visibility Audit — specifically gives a page-level “AI Readiness” score based on things like indexability, intent/value, trust, schema, and AI citeability.
• GEOSource — interesting if you want a more research-oriented score. It breaks the score into things like answerability, citation quality, definitions, readability, and AI accessibility.
• SearchScore — broader audit across GEO + traditional SEO + CRO, with 250+ signals.
• Rankeo — combines page auditing with ongoing tracking of citations across multiple AI engines.

One important caveat

I wouldn't treat the resulting “AI score” as an authoritative probability that a page will actually be cited. There isn't a public equivalent of Google PageRank or Search Console for ChatGPT/Claude/Perplexity citations. Vendors generally estimate visibility by combining page-level signals with observed AI citations. www.reddit.com

And research suggests the actual citation process is more nuanced: topical relevance and retrieval position appear to be particularly important, while things like completeness, freshness, structure, and trust signals can help but don't guarantee citation. arxiv.org

If your actual goal is: “We have 5,000 pages. Give every page a score from 0–100 for its likelihood of being cited by an AI answer engine, and tell us what to fix,” — that's a slightly different problem, and I can lay out the best tools/workflow for doing that at scale.

Yes. The category you’re looking for is generally called GEO (Generative Engine Optimization) or AI search visibility.

A few tools specifically score individual pages for their likelihood of being understood/cited by AI answer engines:

• AI Search Visibility — probably the closest match to your question. Paste a URL and it gives an AI Readiness / Citeability score, with checks for indexability, content/intent, E-E-A-T, schema, and how quotable the page is. It explicitly targets ChatGPT, Google AI Overviews, Perplexity, etc. www.aisearchvisibility.ai
• Citera — scores pages across answer directness, authority signals, structured data, semantic coverage, and freshness, and looks at how different AI engines understand/cite the page. citera.dev
• SearchScore — gives an AI Search score plus SEO/CRO scores and can subsequently track actual AI citations across multiple engines. searchscore.io
• Context.dev's GEO Checker — free URL-level checker specifically aimed at citation readiness for ChatGPT, Perplexity, Google AI Overviews, and Copilot. www.context.dev

One important distinction

There are really two different things you can measure:

1. "Is this page structurally/content-wise likely to be cited?"

→ Tools like AI Search Visibility and Citera are what you want.

2. "Is this page actually getting cited when people ask relevant questions?"

→ Tools like SearchScore, Ahrefs Brand Radar, Profound, Peec, etc. are more useful.

The second is ultimately more meaningful. AI answers are probabilistic, so a single "GEO score" isn't a guaranteed probability of citation. Recent research specifically recommends repeated measurements across prompts rather than treating visibility as a single static number. arxiv.org

If you're evaluating this for your own site's pages, I'd actually use both: a page-level citation-readiness score + a real-world citation tracking score. That lets you answer both "what should we fix?" and "did the fix actually make AI engines cite us more?"

If you tell me roughly how many pages you have (e.g. 50, 5,000, 500k), I can recommend the best tool/workflow for scoring the whole site rather than just individual URLs.

Yes. There’s now a fairly mature category of tools for this, usually called AI visibility, AEO (Answer Engine Optimization), or GEO (Generative Engine Optimization).

The important distinction is that there are two different things you might want to score:

1. “How likely is this specific page to be cited?” — content/page-level audit.
2. “How often does our site actually get cited?” — empirical tracking across AI answers.

Tools worth looking at

• AI Search Visibility — probably closest to exactly what you're describing. You give it a URL and it produces an AI Readiness score (0–10) plus blockers and recommended fixes. It specifically evaluates likelihood of citation by ChatGPT, Google AI Overviews and Perplexity. www.aisearchvisibility.ai

• Ahrefs AI Visibility Checker / Brand Radar — stronger if you want to measure actual observed citations, rather than just predict them. It tracks mentions, citations, cited pages/domains and AI share of voice across ChatGPT, Gemini, Perplexity, Copilot, Google AI Overviews and AI Mode. ahrefs.com

• Semrush AI Visibility Toolkit — broader enterprise/SEO-oriented monitoring; useful if you're already in the Semrush ecosystem. A recent comparison of AEO tools also highlighted it alongside Ahrefs, Scrunch, Peec, etc. www.techradar.com

But there's an important caveat

I wouldn't put too much faith in a single “AI citation score.” AI answer engines are nondeterministic: the same query can produce different sources at different times. Recent research specifically argues that citation visibility should be treated statistically rather than as a fixed score. arxiv.org

So, for a serious content program, I'd use a combination:

Page-level score

“Is this page structurally/content-wise likely to be useful to an AI?”

+

Observed citation rate

“When we actually run relevant questions through ChatGPT/Perplexity/Gemini/etc., how often does this URL get cited?”

+

Citation quality

“When cited, does the AI actually use our page's information in its answer?”

That last one is particularly interesting: research published this year distinguishes between a page merely being retrieved, actually being cited, and its information being absorbed into the generated answer. arxiv.org

If you're asking because you want to build something like this for your own pages, that's actually a very interesting product problem. I can break down what I'd put into a page-level “AI citation likelihood score” and how I'd calculate it—including the signals I'd measure from the HTML/content.

Yes. The category is usually called AI visibility, AI search optimization (AISO), generative engine optimization (GEO), or answer engine optimization (AEO). There are tools that try to estimate how likely your pages are to be cited or surfaced by AI answer engines like ChatGPT, Perplexity, Google AI Overviews, and Claude.

A few options:

There are also page-level analyzers that score the factors AI systems tend to favor, such as:

• Clear entity/topic coverage
• Answer-first formatting
• Structured data/schema
• Author expertise signals
• Citations and references
• Freshness
• Crawlability
• Passage-level extractability
• Unique insights vs. generic summaries

A practical "AI citation readiness" score would usually look at:

1. Can an AI crawler access the page?
   • robots.txt
   • indexing
   • rendered HTML availability

2. Can the model understand what the page is about?
   • strong headings
   • concise definitions
   • structured sections
   • schema markup

3. Would an AI trust it as a source?
   • first-hand data
   • expert authorship
   • references
   • reputation signals

4. Is it quotable?
   • direct answers
   • statistics
   • original research
   • clearly stated conclusions

One caveat: no tool can truly predict "ChatGPT will cite this page 73% of the time." The models don't expose a deterministic ranking score, and citation behavior changes by query, model version, user context, and competing sources. The tools above are mostly visibility monitors and optimization proxies, not guaranteed predictors.

If you are looking for something closer to a "score every URL in our site from 0–100 for AI answer engine citation likelihood" product, that is a less mature niche. Some agencies build internal graders using crawl data + LLM evaluation + SEO signals.

I can also outline what a good internal AI-source-readiness scoring model would look like if you are considering building one.

Yes. The category is usually called AEO (Answer Engine Optimization), GEO (Generative Engine Optimization), or AI search visibility tools. They try to estimate whether your pages are likely to be retrieved, cited, or mentioned by systems like ChatGPT, Gemini, Perplexity, and Google AI Overviews. aeoaudit.se

A few tools worth looking at:

A caveat: there is no universally accepted “AI citation score” yet. These tools use proxies because AI engines do not publish their exact ranking/citation algorithms. A good evaluation usually combines:

• Actual citation tracking: “When someone asks X, does ChatGPT/Perplexity/Gemini cite this URL?”
• Retrieval readiness: clear answers, structured headings, tables, definitions, FAQs
• Authority signals: expertise, original data, references, reputation
• Technical accessibility: crawlability, schema, clean HTML, freshness

Research on AI citation behavior suggests that relevance, freshness, structured information, and evidence-rich content are among the factors associated with pages being selected as sources, though results vary by engine. arxiv.org

If you mean “score each URL on my site before publishing” (like an AI equivalent of Lighthouse/SEO grading), the market is still immature. If you mean “tell me whether my existing pages are appearing in AI answers,” the tools above are closer to what you want.

Yes. This is now a real category, usually called GEO (Generative Engine Optimization) or AEO (Answer Engine Optimization).

The important distinction is that there are two different things you might want to measure:

1. “Does AI actually cite our pages today?” — measurable by running a set of representative prompts against ChatGPT, Perplexity, Google AI Overviews/AI Mode, Gemini, etc., and recording which URLs get cited.
2. “How likely is this particular page to be cited?” — harder. Some tools audit the page's structure/content and give an AI-readiness or citation-likelihood assessment, but there isn't a universally accepted equivalent of a Google ranking score.

Tools worth looking at

Profound is probably closest to what you're describing for an enterprise/content team. It tracks which specific URLs are cited across ChatGPT, Google AI Overviews and other answer engines, and lets you analyze citation share at the page level. www.tryprofound.com

OtterlyAI is another strong option. It monitors prompts across ChatGPT, Google AI Overviews, Perplexity, Gemini, Claude and Copilot, then reports whether your site is mentioned/cited. It also has a GEO Audit that evaluates whether AI engines can crawl and understand your site. help.otterly.ai

Semrush has an AI Visibility Toolkit that combines AI visibility tracking with an AI-readiness site audit. A recent independent comparison specifically noted its ability to analyze AI visibility and content readiness. www.techradar.com

But there's a catch

I wouldn't put too much faith in a single “AI citation score = 82/100” number.

Research in 2026 is finding that citation behavior differs substantially between engines. A page that gets cited by Google AI Overviews isn't necessarily the page ChatGPT or Perplexity will cite. arxiv.org

In fact, the more useful measurement is something like:

For the questions we care about, how often does each engine retrieve and cite each of our URLs?

You can then calculate a page-level score such as:

Citation Rate = prompts where page was cited ÷ relevant prompts tested

and break it down by engine, topic, competitor, and query type.

If your actual goal is to score every page on your site and identify which pages are most/least likely to become AI sources, I can also show you what the ideal scoring system would look like—and which existing tool gets closest to it.

Yes. This has become a fast-growing category of SEO tools, often called AI visibility, LLM optimization, or Generative Engine Optimization (GEO). The caveat is that none of them can accurately predict with certainty whether ChatGPT, Gemini, Claude, or Perplexity will cite a specific page, because the models don't publish their ranking algorithms. Instead, they estimate likelihood based on factors correlated with AI citations and often test prompts directly.

Some of the better-known tools include:

What these tools typically score

A good AI visibility score usually combines things like:

• Whether your content is fact-rich and directly answers questions
• Original research or statistics that AI systems are likely to cite
• Clear page structure (headings, FAQs, lists, tables)
• Strong topical authority
• Freshness
• External citations and backlinks
• Technical accessibility (crawlability, rendering)
• How often the page actually appears in AI-generated answers during prompt testing

If you want page-level scoring

The most useful products don't just give a site-wide score—they'll tell you something like:

Likelihood of citation: 82/100

Reasons:

• ✅ Original data
• ✅ Answers common questions directly
• ✅ Good semantic coverage
• ⚠️ Weak entity definitions
• ⚠️ Missing author expertise signals
• ⚠️ Competitor cited instead

That kind of breakdown is more actionable than a single numeric score.

If you're building your own

Many companies are now creating internal "AI Citation Scores." A practical rubric might weight factors like:

• Information quality (30%) – factual completeness, unique insights
• Answerability (20%) – directly answers common user questions
• Authority (20%) – expertise, references, backlinks, reputation
• Structure (15%) – headings, tables, concise summaries, schema
• Freshness (10%) – updated information
• Technical accessibility (5%) – crawlability, page speed, clean HTML

You can then validate that score by periodically testing hundreds of prompts against AI assistants and comparing your predictions to actual citations.

In practice, the most mature products today are Profound, Scrunch AI, and Goodie if your primary goal is understanding how often AI systems surface your content, while Semrush and Ahrefs are adding AI visibility metrics to complement traditional SEO.

Yes. This is an emerging category often called AI visibility, LLM SEO, or Generative Engine Optimization (GEO). There are a few tools that estimate how likely your pages are to be cited or used in AI-generated answers, though none can perfectly predict it because OpenAI, Google, Anthropic, and Perplexity don't publish a "source score."

Some of the stronger options are:

What a good AI source score should evaluate

The best tools don't just look at SEO—they analyze factors that correlate with AI citation, such as:

• Whether the page is actually cited by ChatGPT, Gemini, Perplexity, etc.
• Semantic completeness (does it fully answer a question?)
• Entity coverage
• Original research or proprietary data
• Structured content (tables, FAQs, definitions)
• Internal linking
• Author expertise and trust signals
• Freshness
• Crawlability
• Whether the content appears in search indexes AI systems commonly rely on

If you're thinking about building one

A genuinely useful "AI Source Likelihood Score" could combine signals like:

• Answer Completeness (20%) – Does the page fully answer a user question?
• Citation Worthiness (20%) – Original statistics, studies, examples, or unique insights.
• Entity Coverage (15%) – Clear treatment of relevant people, products, concepts, and organizations.
• Authority Signals (15%) – Author information, references, external citations, and trust indicators.
• Technical Accessibility (10%) – Fast loading, crawlable, clean HTML.
• Content Structure (10%) – Headings, lists, tables, concise summaries.
• Freshness (5%) – Recent updates where appropriate.
• External Recognition (5%) – Backlinks, mentions, or other indicators of authority.

This would be more actionable than a simple SEO score because it focuses on qualities that make content useful for answer engines.

Opportunity

There still isn't a widely accepted equivalent of Google's Lighthouse or PageSpeed Insights for AI citation readiness. Most current tools emphasize tracking ("Did an AI mention my brand?") more than grading ("How likely is this page to become a source, and exactly why?").

A page-level analyzer that provides:

• an overall AI Source Score,
• engine-specific predictions (ChatGPT vs. Google AI Overviews vs. Perplexity),
• explanations for each deduction,
• and concrete recommendations,

would fill a gap that many content teams are actively looking to address.

Yes, although most are still fairly new and none can definitively predict whether a page will be cited by AI systems. What they do instead is estimate "AI visibility" or "citation readiness" by analyzing the factors that large language models and AI search engines tend to reward.

Some of the better options are:

What a good AI citation score should include

If I were designing a page score specifically for "likelihood of being used as an AI source," I'd weight factors like these:

Then produce something like:

AI Citation Score: 84/100

with sub-scores such as:

• Authority: 90
• Originality: 88
• Answerability: 92
• Evidence: 73
• Structure: 95
• AI Extractability: 89

An opportunity that isn't fully addressed

Most current tools focus on whether you're already appearing in AI answers. Fewer evaluate whether a specific page is likely to become a source before it's indexed or cited.

A stronger page-level analyzer could check things like:

• Can the page answer a standalone question in under 150 words?
• Does it include unique facts not found elsewhere?
• Are claims backed by identifiable sources?
• Is the page easy for an LLM to chunk into self-contained sections?
• Does it establish expertise and trustworthiness?
• Would a retrieval system likely rank this page as relevant for common prompts?

That kind of predictive scoring is still relatively uncommon.

If you're building an SEO or GEO product, this is an area where you could differentiate. A page-level "AI Citation Probability" score with concrete recommendations ("add original data," "make this definition self-contained," "cite primary sources," "improve entity coverage") would provide more actionable guidance than simply reporting existing AI mentions.

Yes. This is becoming a new category of SEO tooling, often called AI visibility, LLM optimization, or GEO (Generative Engine Optimization). There isn't yet a universally accepted "AI source score," but several tools estimate how likely your content is to be cited or influence AI-generated answers.

Some of the strongest options are:

If you're looking for a page-level score

The ideal score would evaluate factors like:

• Entity clarity
  • Does the page clearly define who/what it's about?
• Topical completeness
  • Does it answer the primary and related questions?
• Original information
  • Data, research, statistics, or unique insights AI systems can cite.
• Citation quality
  • References to authoritative sources.
• Structured content
  • Good headings, lists, tables, FAQs.
• Schema markup
  • Organization, Article, FAQ, Product, etc.
• E-E-A-T signals
  • Author expertise, about page, references, contact information.
• Technical accessibility
  • Fast loading, crawlable HTML, minimal JavaScript barriers.
• Link authority
  • Backlinks and brand mentions.
• Actual AI citation frequency
  • Whether the page is already being referenced in AI answers.

A scoring model might look like:

• Authority: 22/25
• Content completeness: 18/20
• Entity clarity: 14/15
• Structured data: 8/10
• Originality: 16/20
• AI citation history: 4/10

Overall AI Citation Score: 82/100

The gap in today's tools

Most current platforms tell you:

• "Your brand appeared in ChatGPT 18% of the time."
• "Competitor X appears twice as often."

They don't reliably predict, before publication, whether an individual page is likely to become a source.

That's an opportunity. A useful "AI Source Score" could combine:

• Traditional SEO signals.
• Semantic coverage and entity extraction.
• Readability for retrieval and summarization.
• Originality and evidence.
• Structured data quality.
• Historical citation patterns from AI engines.
• Comparison against the pages currently cited for the same queries.

Such a score would be more actionable than a generic SEO score because it would estimate a page's likelihood of being selected as evidence in AI-generated answers rather than just ranking in search results.

If you're considering building this as a product, it's a timely idea. Most existing tools focus on monitoring visibility after the fact, whereas a predictive AI citation score for individual pages would fill a gap in the current market.

Yes, but with an important caveat: no tool can accurately predict whether a page will be cited by ChatGPT, Gemini, Claude, Perplexity, or Google's AI Overviews, because those systems don't publish their ranking algorithms. The best tools estimate AI visibility by measuring how often your content actually appears in AI-generated answers or by scoring factors that correlate with citation.

Here are the strongest options:

Most of these report metrics like:

• % of prompts where your site is cited
• Share of voice in AI answers
• Competitors that get cited instead
• Pages most frequently referenced
• Missing topics AI prefers from competitors

If you want a page-level "AI citation score"

This is a feature that's still emerging. A good scoring system would combine signals such as:

That produces something like:

AI Citation Score: 87/100

High likelihood of being quoted by AI answer engines.

Biggest improvement: add original statistics and a concise summary section.

The gap in the market

Interestingly, there still isn't a widely accepted equivalent of Google's Lighthouse for AI citation readiness. Most tools focus on:

• monitoring whether you are cited, or
• recommending SEO improvements.

Very few provide a transparent, page-by-page predictive score explaining why a page is or isn't likely to be used as an AI source.

If you're thinking about building a product in this space, a tool that:

1. crawls a page,
2. computes an "AI Sourceability Score,"
3. explains the reasoning,
4. compares it against pages that AI systems actually cite,
5. and suggests specific improvements,

would fill a real need for publishers and SEO teams. It would complement existing AI visibility trackers rather than duplicate them.