ChatGPT answers, unedited

If you mean “can I test whether my SaaS documentation pages are actually being cited as sources by AI assistants?”, I’d separate the tools into two categories:

1. Citation reality checks — run prompts against AI assistants and see whether your docs appear as sources.
2. Citation readiness graders — analyze docs structure and estimate whether they’re easy for AI systems to quote.

A few free options worth trying:

For a SaaS docs site, I’d probably build a simple internal grader rather than rely only on third-party scores. A useful MVP would:

1. Pick 20–50 “buyer/support” questions

Examples:

• “How do I authenticate with API X?”
• “How do I migrate from competitor Y?”
• “Does Product Z support SSO?”
• “What are the rate limits?”

2. Run each question through:

• ChatGPT with web/search
• Perplexity
• Gemini
• Claude (where web access is available)

Record:

• Was your docs domain cited?
• Which URL was cited?
• Was the answer accurate?
• Did the assistant choose a blog post, docs page, GitHub, or third-party source?

3. Grade each doc page on:

• Clear title matching user intent
• One-sentence product definition near the top
• Stable URLs
• Copyable code examples
• Tables for specs/limits
• Version/date metadata
• Author/source attribution
• Structured data where relevant
• No marketing-only language in technical answers

A simple scorecard could be:

AI Citation Score (100)

+25  Appears as cited source in target queries
+20  Correct page chosen (not homepage/blog)
+15  Answer is extractable in <200 words
+15  Docs contain canonical examples
+10  Freshness/version signals
+10  Structured metadata
+5   Internal linking/context

One caution: a “citation readiness” score is not the same as actual AI citation frequency. Some graders estimate whether content is citable; they do not prove that ChatGPT/Claude/etc. will cite a page in live answers. Gadex Jason Burns

For a SaaS docs site, I’d start with a live query-based tracker plus a docs-page grader. The combination tells you both “are we being cited?” and “why not?”.

Yes. If your goal is specifically “which of my docs get cited when someone asks an AI assistant a relevant question?”, I’d separate that from generic GEO/AI-readiness audits.

A few free options worth testing:

• Citegrade — probably the closest match to your use case. You give it a URL + target query, and it checks ChatGPT and Perplexity live, showing whether your page was cited, its citation position, and which competitors appeared instead. Citegrade
• Landing Creator AI Citation Checker — free/no-login check across ChatGPT, Claude, Perplexity and Gemini. It can generate relevant questions from your domain and test whether your site gets cited. Landing Creator
• pressGEO — free/no-signup visibility check across ChatGPT, Perplexity, Gemini, Claude and Copilot, with buyer-intent questions. More brand-oriented than individual-doc oriented, but useful for SaaS. PressGeo
• CitationDesk — offers a free AI Visibility Score for individual URLs, plus other free auditing tools. It is more of a “is this page citation-ready?” grader than a live citation monitor. CitationDesk
• SearchScore — broader AI-search visibility auditing and tracking across multiple engines; useful if you eventually want ongoing monitoring rather than a one-off grader. SearchScore

If you're thinking of building this yourself

For a SaaS docs site, I'd actually make the grader doc-centric rather than domain-centric:

Paste your docs URL → identify important docs → generate 10–20 questions → query several AI engines → report exactly which docs were cited.

For each doc, something like:

Then show the actual queries and citations underneath.

One important distinction: “AI can cite my page” and “AI actually cites my page in the wild” are different measurements. Live web-search systems can produce citations from current web results; for example, Claude's web-search system explicitly returns the URLs of sources it used. Claude Platform

So I'd have two scores:

1. Citation readiness — does the doc contain clear, extractable answers?
2. Observed citation rate — when we ask realistic customer questions, does the AI actually cite it?

If you're looking for a free tool you can use right now, I'd start with Citegrade + Landing Creator and compare their results against ~10 real questions from your docs. Citegrade Landing Creator

If you're asking because you want to build a free grader as a lead magnet for your own SaaS docs product, I can also sketch the MVP architecture and scoring methodology.

One important distinction: “AI can cite my page” and “AI actually cites my page in the wild” are different measurements. Live web-search systems can produce citations from current web results; for example, Claude's web-search system explicitly returns the URLs of sources it used.

So I'd have two scores:

Yes. If your goal is specifically “give me a URL + a question and tell me whether an AI assistant cites that exact docs page”, I’d look at these:

• citegrade.com — probably the closest match. You enter a specific page URL and target query, and it checks ChatGPT and Perplexity, including citation position and competing sources. It explicitly distinguishes mentioned from actually cited. Citegrade
• citationdesk.com — useful if you want a broader docs-page citation-readiness audit rather than only live queries. Its free URL score covers ChatGPT, Claude, Perplexity and Gemini. CitationDesk
• rank.ai — good for testing a prompt across ChatGPT, Claude and Gemini and seeing whether your domain is cited. Rank.ai
• aicitationmonitor.com — broader multi-engine snapshot across ChatGPT, Perplexity, Gemini and Google AI Overviews, including the URLs actually cited. AI Citation Monitor

For a SaaS docs site, I'd test this way

Don't just test “Is Acme mentioned?”. Build a small test set around your documentation:

Then record:

Query → assistant → cited? → exact URL → citation position → answer accuracy

That's much more useful for a docs team than a generic “AI visibility score.”

One caveat: AI citations aren't deterministic. The same query can produce different sources on different runs, so a one-shot grader is best treated as a snapshot rather than proof that a page is permanently “citable.” Citegrade explicitly makes this point, and other tools use repeated sampling for the same reason. Citegrade AI Citation Monitor

If you're actually thinking of building this as a free tool for your own SaaS docs site, I can also sketch a very simple grader architecture (crawl docs → generate questions → query 2–3 LLM/search APIs → extract citations → score pages) that could be built pretty cheaply.

Yes. For a SaaS docs site, I’d distinguish “is this page technically citable?” from “do AI assistants actually cite this page for the questions customers ask?” The second is much more useful.

Free tools I’d try

• rank.ai — probably the closest fit for your use case. You give it a prompt + domain, and it queries ChatGPT, Claude, and Gemini, showing whether you were mentioned and whether your site was actually cited. Free/no registration. Rank.ai
• seo.bike — runs live prompts against ChatGPT and Perplexity and reports whether your domain gets cited. Useful for quickly testing a handful of documentation-related queries. seo.bike
• github.com — especially interesting if you want to crawl the whole docs site rather than test individual prompts. It's open source and scores pages for how extractable/citable they are across ChatGPT, Perplexity, Gemini, Claude, Copilot and Google AI Overviews. GitHub
• frase.io — has separate free checks for page-level GEO readiness, whether AI engines cite your domain, and whether AI agents can access your site. Frase
• citatur.com — offers a free audit across ChatGPT, Claude, Gemini and Perplexity, including cited sources and competitor comparison. Better if you're interested in ongoing monitoring eventually. Citatur

For your specific use case

I'd actually build a tiny “docs citation grader” workflow rather than rely entirely on a generic GEO score.

Take your 10–30 most important docs pages and create questions such as:

“How do I configure webhooks in [product]?”
“How do I authenticate with [product] API?”
“What is the difference between X and Y in [product]?”
“How do I troubleshoot error XYZ?”

Then grade each page × question × assistant:

That gives you a much more actionable metric than a generic “AI visibility = 73.”

One particularly useful distinction is domain citation vs. correct-document citation. For documentation, you ideally want the assistant to cite the specific canonical page that answers the question, not merely some page on your domain.

Also worth checking the free Microsoft/Bing AI Performance data if your site is verified in Bing Webmaster Tools: it exposes cited pages and the grounding queries associated with those citations. Search - Microsoft Bing

My shortlist: start with Rank.ai + CITED Score. Rank.ai answers “are assistants citing us?” while CITED Score answers “is our documentation structured so that assistants can extract/cite it?” Together they're a pretty good free baseline.

Yes. If your goal is specifically “do AI assistants cite my docs as sources?”, rather than generic GEO/SEO scoring, I’d test a few options:

• rank.ai — probably the closest fit for a quick test. You give it a prompt + domain and it checks ChatGPT, Claude, and Gemini, including whether your domain was cited, not merely mentioned. It says the free checker requires no signup. Rank.ai
• app.citecue.com — has a free grader plus separate checks for AI visibility/readiness. Useful if you want something you can hand to prospects or teammates. CiteCue
• learn.microsoft.com — more interesting if you want ongoing measurement rather than a one-off grader. It tracks which pages are actually cited in AI-generated answers, grounding queries, and AI referral traffic. Microsoft Learn
• searchgrade.app — broader than your use case: it grades technical SEO, content, AEO and GEO across 126+ checks. Good if you also want to diagnose why docs aren't discoverable/citable. SearchGrade

What I'd actually do for a SaaS docs site

I'd not rely on a single “AI score.” Build a tiny repeatable benchmark:

1. Pick 10–20 questions that a prospective developer/customer would actually ask.
2. Run each question through ChatGPT, Claude, Gemini, and Perplexity.
3. Record: - Was your company mentioned?
4. Was your docs domain cited?
5. Which exact documentation URL was cited?
6. Was the citation actually relevant/correct?
7. Which competitor docs were cited instead?
8. Calculate something like:

Citation rate = prompts where your docs were cited / total prompts

That distinction matters: being mentioned and being used as a source are different outcomes. Rank.ai explicitly measures both. Rank.ai

And this is increasingly worth tracking separately from traditional SEO. Google itself now documents AI Overviews/AI Mode and notes that AI-generated answers can draw on web sources; Search Console also counts AI-feature activity. Google for Developers Google for Developers

If you're thinking of building the free grader yourself, I think there's a particularly nice SaaS-docs-specific product hiding here: enter docs URL → automatically extract the important pages → generate 10 realistic buyer/developer prompts → query several assistants → show a “citation coverage” score + exactly which docs are missing.

That would be considerably more useful than another generic “GEO score.”

Yes. If your goal is specifically “which of my docs pages actually get cited by AI assistants?”, I’d distinguish that from generic GEO/AI-readiness graders.

A few worth trying:

• citegrade.com — probably the closest fit. You give it a specific URL + target query, and it checks ChatGPT and Perplexity in real time, including citation position and competitors that were cited instead. Free. Citegrade
• frase.io — free check of whether ChatGPT, Perplexity, and Gemini cite your domain. Better for a quick domain-level sanity check than individual docs-page testing. Frase
• citationdesk.com — free, no signup, but primarily a citation-readiness score rather than proof that a particular assistant actually cited the page. CitationDesk
• cite.watch — more of a monitoring product; it tracks prompts across ChatGPT, Gemini, Claude, Copilot, and Perplexity and reports citation/share-of-voice metrics. Its free Light Scan is useful for an initial test. Cite Watch
• github.com — interesting if you're technical and want something you can run yourself. It's open source and can audit pages and actually check citation coverage across multiple models. GitHub

For a SaaS docs site, I'd build/test it slightly differently

The useful grader isn't just:

“Is this page AI-friendly? → 82/100”

I'd make the core test:

1. Select 10–20 important docs URLs.
2. Associate each with 3–10 questions users might ask an AI assistant.
3. Run those questions against several assistants.
4. Determine: - Was the page cited?
5. Which URL was cited?
6. Citation position
7. Was the page merely mentioned vs actually cited?
8. Which competitor/docs page was cited instead?
9. Was the relevant passage from your page actually reflected in the answer?
10. Produce something like:

That gives you a much more actionable “AI citation coverage” metric than a generic GEO score.

There's also a free browser-based tracker from Plain Intelligence that takes this approach: you define a fixed set of queries and manually log citation results across ChatGPT, Claude, Gemini, Perplexity, Copilot, and Google AI Overviews. Plain Intelligence

If you're thinking of building this as a free grader for your own docs site, I can also sketch a lightweight architecture for a “Docs AI Citation Grader”—including the scoring rubric, test prompts, and what the report should show.

Yes. If your goal is specifically “do AI assistants cite these particular docs pages?”, I’d separate tools that grade citation-readiness from tools that actually test live AI answers.

Good free options

• rank.ai — probably the quickest starting point. You give it a prompt + domain and it checks ChatGPT, Claude, and Gemini, including whether your site is actually cited. Free/no signup. Rank.ai
• frase.io — checks ChatGPT, Perplexity, and Gemini for mentions/citations and lets you provide your own phrases. Useful if you already have a list of questions your docs should answer. Frase
• fogtrail.ai — broader engine coverage: ChatGPT, Perplexity, Claude, Gemini, and Grok, with per-query citation status. The free scan is delivered as a report. FogTrail
• lacleo.ai — more page-oriented. You submit an individual URL and it combines citation-readiness checks with a live Perplexity probe. Good fit if you have a handful of “key docs” pages you want to audit individually. LaCleo
• searchgrade.app — useful if by “grader” you mean score my docs for AI-citability, rather than merely test whether they're currently being cited. It reports 126+ SEO/AEO/GEO checks and supports individual URLs or bulk audits. SearchGrade

What I'd do for a SaaS docs site

I'd actually build a tiny repeatable benchmark rather than rely on a single generic “AI score.”

Take your 10–30 most important docs pages and create 3–5 natural questions for each page, e.g.:

“How do I configure X in [product]?”
“What happens when X fails?”
“How does [product] compare with Y for X use case?”

Then track:

The important distinction is mention vs. citation. A model saying “Acme supports OAuth” isn't the same as actually linking to your /docs/oauth page.

For your use case, Rank.ai or Frase would be my first quick test, then I'd use a spreadsheet to establish a fixed benchmark you can rerun after documentation changes. Rank.ai explicitly runs identical prompts across its supported assistants, which makes it particularly useful for before/after comparisons. Rank.ai

If you tell me what your docs stack is (Mintlify, GitBook, Docusaurus, ReadMe, custom, etc.) and roughly how many key pages you have, I can suggest a free/DIY grader setup specifically for docs citation coverage, including the scoring rubric.

Yes. If your goal is specifically “do AI assistants cite my actual docs pages?”, I’d avoid generic AI-readiness graders—they often score things like robots.txt, schema, and crawler access rather than testing whether a particular documentation page actually gets cited.

A few worth trying:

• seo.bike — free, live checks against ChatGPT and Perplexity. Good quick sanity check for whether your domain is being cited.
• aisearchvisibility.ai — more page-oriented; its audit scores a specific URL for “AI citeability” among other factors. It offers a free first audit.
• crawlpod.com — useful if you're trying to distinguish “AI can't access/read my docs” from “AI can access them but doesn't cite them.”
• nyftylabs.com — free/BYOK and checks citation/mention behavior across several models, which is useful if you're comfortable supplying API keys.
• github.com — probably the most interesting starting point if you want something you can inspect or adapt yourself; it's MIT-licensed and checks ChatGPT, Gemini, and Perplexity.

But for a SaaS docs site, I'd test something slightly different

I'd make a “Docs Citation Grader” rather than a generic AI visibility grader.

Give it:

1. Your docs domain
2. 5–20 important documentation URLs
3. 5–10 questions each page should answer

Then test questions such as:

“How do I configure X in [product]?”
“Does [product] support Y?”
“What is the API limit for Z?”

For each question, record:

That's substantially more actionable than a single “AI visibility = 63” score.

I'd also distinguish mention vs citation. Those are genuinely different outcomes; some monitoring products explicitly score them separately because being named isn't the same as having your page appear as a source. CueScout

If you're actually thinking of building this grader as a free lead-gen tool for your SaaS docs product, I can sketch a very simple architecture and scoring methodology that you could launch without paying for an expensive GEO platform.

Yes. If your goal is specifically “do AI assistants cite my actual docs pages?”, I’d avoid tools that only give a generic GEO/AI-readiness score.

A few free options worth testing:

• citerank.io — particularly relevant for SaaS. Its free diagnostic lets you enter your site, generates buyer-style questions, and checks whether AI assistants recommend you, which competitors appear, and which sources get cited. CiteRank
• frase.io — free first result; checks whether ChatGPT, Perplexity, and Gemini link to your domain. Frase
• tryprefer.com — free/no account and checks ChatGPT, Google AI Overviews, Perplexity, Claude, and Gemini, including sources cited instead of you. Prefer
• citationdesk.com — completely free, no signup, but it's more of a citation-readiness audit than proof that a particular docs page is actually being cited. CitationDesk
• llmranks.io — another useful quick snapshot that queries AI assistants and analyzes the cited sources. LLMRanks

For a SaaS docs site, I'd test it differently

The interesting metric isn't just:

“Does AI mention my company?”

It's:

“When someone asks a question that my docs answer, does the assistant cite the specific documentation page?”

I'd create ~20–50 questions from your highest-value docs, e.g.:

• “How do I configure X?”
• “Does [product] support Y?”
• “How do I authenticate with Z?”
• “[Product] API rate limits”
• “How do I troubleshoot error X?”
• “[Product] vs competitor for use case Y”

Then run those questions repeatedly across ChatGPT, Claude, Perplexity, and Gemini and record:

Prompt → cited URL(s) → whether your domain appeared → exact docs page → competitor cited instead → answer accuracy.

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

If you want, I can also find a genuinely free tool/workflow that accepts a sitemap or list of docs URLs and grades citation coverage page-by-page—which sounds closer to what you're after.

Yes. For a SaaS docs site, I’d separate “is this page citation-ready?” from “is an AI assistant actually citing this page?” They’re related, but not the same test.

Free tools I’d try

• Citegrade — probably the closest match to what you described. You give it a specific docs URL + target query, and it checks ChatGPT and Perplexity for whether your page is actually cited, including citation position and competing pages. Its free plan currently includes 2 audits/month. Citegrade Citegrade
• CitationDesk — good for a quick page-level citation-readiness audit. It grades things such as SEO foundation, GEO readiness, entity coherence and crawlability; the free audit requires no signup. CitationDesk
• Yogoo AI — useful if you want a broader site/brand visibility check across ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews. It offers a free score without signup. Yogoo
• FogTrail — another useful free baseline: enter your domain and it checks five engines, including ChatGPT, Perplexity, Claude, Gemini and Grok, then reports whether you're cited, merely mentioned, or absent. FogTrail
• FixAEO — more of a content grader than a real citation test. It checks whether the structure of a page makes it easy for answer engines to extract/quote, and is completely free/no-signup. FixAEO

For SaaS docs specifically

I'd actually build a tiny testing spreadsheet around your important docs + the questions each doc should answer.

For example:

That gives you a much more meaningful “docs citation rate” than a generic AI visibility score.

One important caveat: don't treat one AI response as definitive. These systems' retrieved sources can change between runs, so repeat the same question periodically and look at citation rate over time, rather than declaring a page “not cited” from one test. Citegrade explicitly recommends treating individual checks as samples for this reason. Citegrade

If you tell me what your docs stack is (Mintlify, Docusaurus, ReadMe, GitBook, custom, etc.), I can also suggest a completely free way to automatically test your 20–50 most important docs against a set of questions.

Yes. For a SaaS docs site, I’d distinguish between “is this page citation-ready?” and “is an AI assistant actually citing this page?” Those are different tests.

My picks

• citegrade.com — probably the closest match to what you described. Give it a specific docs URL + target question, and it checks ChatGPT and Perplexity for whether your page is actually cited, including citation position and competing sources. It says citation checks are free/unlimited. Citegrade
• rank.ai — good for a quick cross-model check. It sends the same prompt to ChatGPT, Claude, and Gemini and reports mentions and citations. Rank.ai
• frase.io — useful if you want both sides: a page-level GEO readiness score and a domain-level check for whether AI engines cite you. Frase
• github.com — interesting if you're technical and want something you can incorporate into your own docs QA/CI. It's open source and has an eval harness for measuring mentions/citations across several AI engines. GitHub

For SaaS docs specifically

I'd actually build a simple recurring grader around your 20–50 highest-value questions, rather than just checking whether the domain gets mentioned.

For each question, record:

Then calculate something like:

Docs Citation Rate = questions where the expected docs URL was cited / total questions

That's considerably more actionable than a generic “AI visibility score.”

One caveat: don't confuse a readiness grader with observed citations. Several free tools score whether a page looks citation-worthy without actually querying AI systems. For your use case, I'd prioritize tools that expose the actual URLs returned by live AI answers. jasonburns.co.uk citedspy.com

If you tell me what your SaaS does + roughly how many docs pages you have, I can suggest a free testing setup (including a prompt set and scoring rubric) that you could run weekly.

If your goal is specifically “which of my docs pages are actually being cited by AI assistants?”, I’d look for tools that measure citation URLs, not just “AI visibility” or brand mentions. A lot of graders only tell you whether your company appeared; you want a docs-level source audit.

A few options:

Free / lightweight graders to try

• rank.ai — probably the closest fit for a quick SaaS check. It runs prompts across multiple assistants and reports whether your domain is mentioned and whether your site is cited. Rank.ai

• Good for: “Does AI cite my docs domain at all?”
• Limitation: not primarily a page-by-page docs crawler.
• app.citecue.com — focuses on whether AI answers cite your site and includes checks around AI accessibility. CiteCue

• Good for: understanding why assistants may not retrieve your content.
• Useful if you’re also looking at robots.txt, llms.txt, and crawlability.
• lantad.co — audits how AI systems can read a page, including things like rendered vs crawler-visible content and extractability. Lantad

• Good for: docs sites built with JS-heavy frameworks where crawlers may see less than humans.
• quanticdata.io — more page-oriented; it checks whether a page is likely to be readable/citable by AI systems. QuanticData

• Good for: testing your highest-value docs pages individually.

For a SaaS docs site, I’d probably build a simple internal grader

The best signal is not “is my brand mentioned?” but:

A simple workflow:

1. Pick 50–100 customer questions from:

• support tickets
• docs search queries
• sales calls
• onboarding questions
• Run them against:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Extract:

• cited URLs
• domains
• whether your answer pages appeared
• whether the answer was correct
• Create a “docs AI citation score”:

cited_queries / total_queries × 100

For a SaaS docs team, this is often more actionable than generic GEO scores because it tells you exactly which docs pages to improve.

A few docs-specific improvements that tend to help citation likelihood:

• Put the direct answer near the top of the page.
• Use descriptive headings (“How to rotate API keys”) rather than marketing headings.
• Include exact error messages, parameters, limits, and examples.
• Keep canonical URLs stable.
• Add structured metadata where appropriate.
• Make sure important docs are accessible without heavy client-side rendering.

If you want something closer to a “Lighthouse for AI citations” for your own SaaS docs, I’d actually consider building a small internal tool: ingest sitemap → generate customer prompts → query assistants → diff cited URLs weekly. That’s a very reasonable weekend MVP.

Yes. For a SaaS docs site, I’d distinguish between “is this page technically citable?” and “do AI assistants actually cite this page when answering relevant questions?” The second is much more valuable.

A few free options worth trying:

• edenrank.com — probably the closest to what you want for a quick test. You give it a brand, URL, and prompt, and it runs the query across ChatGPT, Perplexity, Gemini, Google AI surfaces, Claude, Copilot, and DeepSeek, showing mentions and citations. Free/no signup. EdenRank
• fogtrail.ai — useful if you want a broader report. It checks ChatGPT, Perplexity, Claude, Gemini, and Grok and reports per-query citation status plus competitor citations. FogTrail
• citationdesk.com — more of a page-level citation-readiness grader. It scores SEO/GEO readiness, entity coherence, crawlability, etc. Good for figuring out why a docs page might not be citable, but it isn't the same as measuring actual citation frequency. CitationDesk
• geosource.ai — specifically geared toward whether individual content can be cited by AI search, with dimensions such as answerability, citation quality, definitions, readability, and AI accessibility. GeoSource.ai
• plain-intelligence.com — surprisingly useful if you want a DIY benchmark. You maintain a fixed list of 10–20 important queries and log whether each engine cites you; the data stays in your browser. Plain Intelligence

What I'd do for SaaS docs

I'd actually build a very simple “AI Docs Citation Score” rather than rely solely on a generic GEO score.

Take your 10–30 most commercially important docs/questions, e.g.:

• “How do I integrate {product} with Salesforce?”
• “How does {product} compare with Zapier?”
• “How do I authenticate with {product} API?”
• “What are the rate limits for {product}?”
• “Best alternatives to {competitor} for X”
• “How do I solve {common customer problem}?”

Then run each prompt against 3–5 assistants and record:

The “correct page” metric is particularly important for a docs site. A SaaS company can have good AI visibility while its actual documentation is never cited—the AI might instead cite Reddit, a blog post, GitHub, or a competitor's docs.

If you're thinking of building this as a free lead-gen tool for your SaaS, I'd make the input simply:

Docs URL → choose 10 key pages → automatically generate relevant questions → test AI answers → show citation rate by page and assistant → give each doc an AI Citation Score.

That would be substantially more useful to a SaaS documentation team than a generic 0–100 “GEO score.”

Yes. For a SaaS docs site, I’d distinguish between “can AI access/read my docs?” and the more useful “does an AI assistant actually cite my docs when answering questions?”

A few free tools worth trying:

• zionlabs.io — probably the closest match to what you described. It explicitly separates mentioned, cited, and passed over, and checks ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews, and AI Mode. Free/no-login.
• rank.ai — lets you supply a specific prompt + domain and compares whether ChatGPT, Claude, and Gemini mention/cite you. This is useful if you already have a list of important docs/questions.
• crawlpod.com — better for diagnosing why docs aren't being cited. It checks crawlability, rendering, AI crawlers, etc., rather than just observed citations.
• aisearchvisibility.ai — URL-level auditing with a free tier; useful if you want to grade individual documentation pages rather than the whole domain.
• answerlume.com — particularly interesting for SaaS: it runs buyer-style prompts against ChatGPT Search and Perplexity and shows the actual citation URLs/evidence.

What I'd use for your use case

If your goal is something like:

“Here are our 30 most important docs pages. Tell me whether ChatGPT/Claude/Perplexity actually cite each page when users ask questions that page should answer.”

I'd not rely on a generic AI-visibility score. I'd build a simple citation grader around a fixed test set:

The key metric I'd call Documentation Citation Rate:

citation rate = runs where the specific docs page was cited ÷ total test runs

That's considerably more actionable than “your site has 62% AI visibility.”

Also, I'd run each question several times because AI answers and source selection aren't deterministic. Perplexity itself describes citations as sources selected for a particular answer, and its current source system evaluates domains as well as individual source material. perplexity.ai

If you tell me what your docs stack is (Mintlify, GitBook, Docusaurus, ReadMe, custom, etc.) and roughly how many key pages you have, I can suggest a free/near-free setup for automatically grading all of them.

Yes. If your goal is specifically “are AI assistants citing my actual docs pages?”, I’d separate tools into two categories:

Free tools worth trying

• georion.vercel.app — probably the closest match to what you described. Give it a URL + question and it checks multiple AI engines for whether that URL gets cited, what competitors get cited, and potential fixes. Georion
• rank.ai — checks the same prompt across ChatGPT, Claude, and Gemini and distinguishes being mentioned from having your site cited. Rank.ai
• citerank.io — useful if you want to turn this into a more systematic SaaS benchmark. Its free diagnostic generates buyer questions and shows which sources AI answers cite. CiteRank
• crawlpod.com — different angle: tests whether AI crawlers can actually read/parse/cite your site, including crawler access and technical structure. CrawlPod
• citationdesk.com — more of a per-page “citation readiness” grader than a true citation-observation tool. It grades structural factors associated with pages being cited. Clear Cited

For a SaaS docs site, I'd do this

Don't just ask:

“Does ChatGPT cite mydocs.com?”

Instead build a small docs citation scorecard around your important pages:

Then run perhaps 10–30 questions against your key docs and calculate:

Docs Citation Rate = exact target-doc citations / total AI tests

That's considerably more actionable than a generic “AI visibility score.”

One important distinction: crawlability ≠ citation. A page can be perfectly accessible to AI crawlers and still never be selected as a source. Conversely, citation tracking tools actually observe the URLs returned as sources. Perplexity's own API documentation, for example, exposes the search-result URLs associated with citations. Perplexity

If you're thinking about building this grader into your SaaS docs product, I can also sketch a free/open-source implementation that takes a sitemap, automatically generates questions from the docs, queries 3–4 AI providers, and produces a per-page “AI Citation Score.”

If you run a SaaS docs site, I’d separate this into two problems:

1. “Are my docs technically citation-friendly?” (free page grader)
2. “Do AI assistants actually cite my docs?” (query monitoring)

A few options:

Free / lightweight graders

• Citation readiness checkers — useful for a first pass on individual docs pages. They typically look at things like structure, headings, schema, clarity, crawlability, and whether the page contains extractable answers. One example is a free citation-readiness checker from Jason Burns, which explicitly distinguishes readiness scoring from live AI citation tracking. Jason Burns
• DIY prompt tests — still surprisingly effective:

1. Pick 20–50 questions users ask before adopting your SaaS.
2. Run them in ChatGPT, Claude, Gemini, and Perplexity.
3. Record: - Was your docs domain cited?
4. Which URL was cited?
5. Was a competitor cited instead?
6. Was the answer accurate?
7. Repeat monthly.

For a docs-heavy SaaS, this manual benchmark often reveals more than a generic score.

Tools that track AI citations

• Citations.io tracks whether AI assistants mention brands and cite sources across assistants such as ChatGPT, Gemini, Perplexity, and Claude. It is aimed more at ongoing monitoring than a one-off docs audit. Citations Citations
• CitationDesk is positioned around a free citation-readiness score and AI visibility checks. CitationDesk
• Search Engine Land has a free AI visibility checker aimed at seeing whether AI systems recommend/cite a company across AI platforms. Search Engine Land

If I were building this into a SaaS docs workflow

I’d make a simple internal grader:

Input: docs URL + target questions

Checks:

• ✅ Page is indexable
• ✅ Title/H1 match the user question
• ✅ Has direct answer blocks (“How do I…”, “Why does…”)
• ✅ Has code examples where relevant
• ✅ Has canonical URL
• ✅ Has structured metadata
• ✅ Contains product/entity names consistently
• ✅ Links to related docs
• ✅ AI test prompts return your URL as a citation

Output:

AI Citation Score: 72/100

Most cited:
✓ /docs/authentication
✓ /docs/api/webhooks

Missing:
✗ /docs/rate-limits
  Competitors cited: example.com, github.com
  Fix: add explicit limits table + examples

For a SaaS docs site specifically, I’d prioritize the real citation test over generic SEO-style graders: ask realistic buyer/user questions and measure whether your actual docs pages appear as sources. devtune.ai

If you’re thinking of building this as a free lead-gen tool for your own SaaS, the MVP is very doable: crawler + prompt set + LLM API calls + citation URL extraction + scorecard.

If you mean “I have docs pages for my SaaS — can I tell whether ChatGPT/Claude/Gemini/Perplexity actually cite those pages?”, there are a few useful options. The market is still early, so I’d separate free graders from ongoing monitoring.

Free / lightweight graders

• citationdesk.com — probably closest to a “paste a docs URL and get a score” workflow. It grades a page for AI citation readiness (crawlability, structure, entity signals, etc.) and provides suggested fixes. CitationDesk
• crawlpod.com — a free scan focused on whether AI systems can read and parse your site, including crawler accessibility signals. CrawlPod
• no7software.co.uk — checks technical AI visibility signals such as crawlability, structured data, and related readiness factors. No7 Software

These are mostly “could an AI cite me?” graders rather than proof that your docs are actually being cited.

For “are my docs actually appearing as citations?”

You’ll likely want an AI visibility tracker:

• citations.io — tracks whether AI assistants mention/cite your brand and pages across ChatGPT, Gemini, Perplexity, and Claude. It is more of a monitoring product than a one-off grader. Citations.io
• learn.microsoft.com — has citation reporting that surfaces pages referenced in AI-generated answers and related metrics. Microsoft Learn

If I were building a free SaaS docs grader

I’d avoid a generic “AI score” and make it answer a docs team’s actual questions:

1. Citation coverage

• “Of 50 buyer questions, how often does AI cite /docs/*?”
• Missing-doc opportunities

• “Users ask: ‘Does your API support X?’ AI cites competitor docs instead.”
• Page-level score

• “This API reference page is cited 0/20 times because examples are missing.”
• Technical checks

• robots.txt allows AI crawlers
• sitemap coverage
• canonical URLs
• structured data
• clear headings
• copyable code examples
• stable URLs
• A simple weekly report

• “Your docs were cited 14 times this week”
• “Competitor docs appeared 39 times”
• “Top missing topics”

A practical MVP could be:

• Crawl the docs sitemap
• Generate 20–100 realistic customer prompts
• Run those prompts against AI APIs
• Extract cited URLs
• Match citations back to docs pages
• Show coverage + gaps

That would be much more valuable to SaaS teams than a single “AI SEO score.”

Yes. The important distinction is between “is my docs site citation-ready?” and “are AI assistants actually citing these specific docs?” For the latter, I’d prioritize tools that run real prompts and show the cited URLs.

A few free options worth testing:

• auditae.app — probably the closest fit for your use case. You give it a brand/domain and a buyer prompt; it checks ChatGPT, Perplexity, Gemini, and Google AI Overviews and reports who gets cited. It currently offers a free live check with no signup. AuditAE AuditAE
• citatur.com — free audit across ChatGPT, Perplexity, Gemini, and Claude, including cited sources and competitor comparisons. Citatur
• pressgeo.com — aimed specifically at SaaS; probes five AI engines and shows whether you're cited and who gets cited instead. Free, no signup. PressGeo
• aisearchvisibility.ai — more of a page-level readiness grader: give it a docs URL and it scores indexability, structure, trust, schema, and “AI citeability.” Free first audit. AI Search Visibility
• citationdesk.com — another no-signup URL grader, with a 0–100 citation-readiness score across several dimensions. CitationDesk

For a SaaS docs site specifically

I'd actually test both types:

1. Pick 10–20 questions your users ask, e.g. - “How do I authenticate with Acme API?”
2. “How do I paginate Acme API results?”
3. “Acme webhook retry behavior”
4. “How do I migrate from Stripe to Acme?”
5. Run those prompts through AuditAE/Citatur/etc.
6. Record whether your docs URL was cited, not merely whether your company was mentioned.
7. Separately run your key documentation URLs through a page-level grader.
8. Re-run monthly to measure whether changes to the docs actually increase citation frequency.

That's important because a SaaS can have excellent brand-level AI visibility while its actual documentation pages aren't being cited.

If you're thinking about building your own free grader for your docs product, there's also a pretty compelling product gap here: most of these tools are focused on brand visibility, while a docs-specific grader could say something like:

“12 of your 25 critical documentation pages were cited in AI answers. Here are the 8 questions where competitors' docs are being cited instead.”

That would be considerably more actionable for a developer/docs team.

If you mean “does an AI assistant actually cite my docs URL when users ask questions my docs should answer?”, you’re looking for an AI citation / GEO visibility grader, not a traditional SEO audit.

A few free options worth trying:

For a SaaS docs site, I’d test it slightly differently than a marketing site:

1. Pick your top 20–50 customer questions:

• “How do I authenticate with API X?”
• “How do I migrate from Y?”
• “Does product support feature Z?”
• “What are the rate limits?”
• Run the exact same prompts monthly.
• Track:

• Citation rate: % of prompts where your docs URL appears
• Position: first cited source vs buried source
• Missing pages: questions where competitors/docs elsewhere get cited
• Citation freshness: whether AI picked your latest docs version

A simple spreadsheet works surprisingly well:

If you’re building this internally, the MVP is also pretty straightforward:

• Store target prompts + URLs
• Query AI engines with web access enabled
• Extract cited URLs
• Compare against your docs domain
• Score citation coverage over time

For SaaS documentation specifically, I’d prioritize citation testing over “AI readiness scores”. A page can score well on generic GEO checklists but still never get retrieved for the questions your users ask. seo.bike AISearchVisibility

I can also suggest a simple architecture for building a free self-serve grader as a lead magnet if that’s what you’re considering.

If you run a SaaS docs site, I’d focus less on a generic “AI SEO score” and more on whether your actual documentation URLs get retrieved and cited for the questions users ask.

A few free or freemium options worth testing:

For a SaaS docs site specifically, I’d also build a simple internal grader:

1. Pick 25–100 real user questions:

• “How do I configure SSO in [product]?”
• “Does [product] support webhooks?”
• “How do I migrate from X to Y?”
• “What are the API rate limits?”
• Run those prompts monthly through:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Track:

• Was my docs domain cited?
• Which URL was cited?
• Was the answer accurate?
• Did a competitor’s docs get cited instead?
• Score each page:

• Citation rate (% of relevant prompts where page appears)
• Retrieval coverage (which topics AI can answer from your docs)
• Accuracy of generated answer
• Freshness (last updated date)

For a docs-heavy SaaS, the most actionable signal is usually not “AI visibility score” but:

“When someone asks an AI assistant a question that my docs answer, does it pull my docs page as the source?”

Tools like usecite.ai and similar monitoring platforms are aimed more at ongoing tracking across prompts and engines, while the free checkers above are better for an initial benchmark. Cite AI

If you’re technical, I’d probably start with a spreadsheet + a few API calls rather than paying for a GEO tool. For a SaaS docs site, you can get 80% of the insight by testing your top 50 support questions.

If you run a SaaS docs site, I’d look for something that measures “citation readiness” at the URL/page level, not just brand mentions. A lot of AI visibility tools answer “does the model know my company?” but your question is more valuable: “does the assistant cite the right docs page when a user asks a product question?” Rank.ai Frase

Some options:

Free / lightweight graders to try

• frase.io

Good if you want a quick domain/page-level check. It also has tools aimed at whether AI systems can read and cite your content. Frase

• rank.ai

Runs prompts against multiple assistants and checks whether your brand/domain is mentioned or cited. Useful for a baseline, though it is more “visibility” than “docs coverage.” Rank.ai

• citationdesk.com

More focused on citation readiness and AI visibility scoring. CitationDesk

• pressgeo.com

Geared toward SaaS-style visibility checks across several AI engines. PressGeo

For a SaaS docs site, I’d actually build a simple internal grader

A good free MVP could be:

1. Inventory your important docs

• /docs/getting-started
• /docs/api/authentication
• /docs/integrations/slack
• /docs/pricing/limits
• etc.
• Create 20–100 real user questions:

• “How do I authenticate with Acme API?”
• “Does Acme support SSO?”
• “How do I migrate from X to Acme?”
• “What are Acme rate limits?”
• Run those prompts through:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Score each answer:

• 0 — not mentioned
• 1 — mentioned but no citation
• 2 — cited wrong page
• 3 — cited correct docs page
• 4 — cited docs page + used accurate details
• Track:

• citation rate by doc URL
• questions your docs fail
• competitors cited instead
• stale pages AI ignores

The biggest product opportunity, if you’re thinking of building this as a feature, is probably not another “AI SEO score.” It’s a docs coverage grader:

“Here are your 50 highest-value support questions. AI assistants answered them 37% correctly. These 12 docs pages are missing citations. Fix these sections first.”

A few implementation details that matter:

• Store the exact prompt + model + date (AI answers drift).
• Separate mention rate from citation rate.
• Evaluate whether the cited URL actually answers the question (many tools stop at “domain cited”).
• Include docs-specific checks: - code examples
• headings matching user questions
• version numbers
• structured metadata
• canonical URLs
• crawl accessibility

For a SaaS docs product, I’d probably start with a free self-serve grader that accepts a sitemap URL, extracts top docs pages, generates test questions, and returns a “citation coverage report.” That is much more differentiated than a generic AI visibility score.

• Store the exact prompt + model + date (AI answers drift).
• Separate mention rate from citation rate.
• Evaluate whether the cited URL actually answers the question (many tools stop at “domain cited”).
• Include docs-specific checks: - code examples
• headings matching user questions
• version numbers
• structured metadata
• canonical URLs
• crawl accessibility

For a SaaS docs product, I’d probably start with a free self-serve grader that accepts a sitemap URL, extracts top docs pages, generates test questions, and returns a “citation coverage report.” That is much more differentiated than a generic AI visibility score.

Yes. For a SaaS docs site, I’d distinguish “is my site AI-readable?” from the more useful question: “when someone asks a question that my docs should answer, does the assistant actually cite the right doc page?”

A few free options worth trying:

• citegrade.com — probably the closest match to what you described. Give it a specific URL + target query, and it checks ChatGPT and Perplexity for whether your page was cited, its citation position, and which competitors were cited instead. It says citation checks are free. Citegrade
• citedspy.com — useful if you want to run the same question across ChatGPT, Perplexity, Gemini, Claude, and Grok and inspect the actual cited URLs. CitedSpy
• rank.ai — checks ChatGPT, Claude, and Gemini side-by-side for a prompt and domain, including whether your site was cited. No signup is advertised. Rank.ai
• frase.io — checks ChatGPT, Perplexity, and Gemini and reports citations back to your domain. Frase

For docs specifically

I'd actually test at the individual-page level, not just your domain.

For example, if you have:

docs.example.com/api/authentication

create 5–10 questions that a developer might ask:

• “How do I authenticate with Example API?”
• “How do I refresh an Example API access token?”
• “Example API OAuth vs API keys”
• “How do I handle expired Example API tokens?”
• “Show me an Example API authentication example”

Then record:

That gives you a much more meaningful Docs Citation Rate than a generic GEO score.

One important caveat: AI citations aren't deterministic. ChatGPT's web-search results can vary, and OpenAI itself notes that citations/search results can be incomplete or incorrect. OpenAI Help Center So I'd run each question several times rather than treating one “not cited” result as definitive.

If you want the simplest starting point, I'd try Citegrade first because its workflow maps almost exactly to “does this particular docs page get cited for this particular question?” Citegrade

If you're actually building a free grader for your own SaaS/docs product, rather than looking for an existing one, I can also suggest a very simple scoring methodology and MVP architecture for it.

If you run a SaaS docs site, I’d look for a grader that checks actual citation behavior (does an assistant cite your docs URLs?) rather than only “AI SEO” scores.

A few free or freemium options:

• rank.ai — probably the closest match to your use case. You enter a prompt + domain, and it checks whether assistants mention your site and whether your pages are cited. It compares multiple assistants side-by-side. Rank.ai

• Good for: “When someone asks How do I integrate X?, does the AI cite our docs?”
• aisearchvisibility.ai — URL-level audits. Useful for individual docs pages because it scores things like AI citeability, structure, schema, trust signals, and extraction friendliness. AI Search Visibility

• Good for: finding why a specific API reference page or tutorial is not being surfaced.
• app.citecue.com — has lightweight checks around AI visibility and citation readiness. CiteCue

• Good for: quick diagnostics before building your own system.

For a SaaS docs-specific grader, I’d also consider building a simple internal one. The signal you probably care about is:

1. Pick 20–50 real customer questions:

• “How do I authenticate with API X?”
• “How do I migrate from Y?”
• “Does product support feature Z?”
• Run those prompts against:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Track:

• Was your domain cited?
• Which docs URL was cited?
• Was a competitor cited instead?
• Did the answer use your docs correctly?
• Citation rate by doc section

A useful score could be:

Docs AI Citation Score =
(cited answers / total test prompts) × 100

+
(correct page cited × 0.5)
+
(answer accuracy × 0.5)

For SaaS docs, I’d prioritize:

• API reference pages
• getting-started guides
• integration tutorials
• troubleshooting pages
• pricing/limits pages

Those are the pages users ask AI about most.

One caveat: no free grader can truly guarantee “ChatGPT will cite this page,” because citations depend on the model, retrieval system, query wording, freshness, and competing sources. Treat these as benchmarks you can trend over time rather than a permanent ranking. Rank.ai

If you want the most useful version for a docs team, I’d probably combine a URL-level auditor with a monthly prompt-based citation test.

Yes. For a SaaS docs site, I’d distinguish “is my domain mentioned?” from “are my actual docs pages being cited for the questions they should answer?” The latter is what you want.

Good free options

• Citegrade — probably the closest fit. You enter a specific URL + target query, and it checks ChatGPT and Perplexity in real time, showing whether your page was cited, its citation position, and which competitor pages were cited instead. Its free tier includes citation verification. citegrade.com
• CitedSpy — useful if you want breadth. It runs the same query across ChatGPT, Perplexity, Gemini, Claude, and Grok and shows the actual cited URLs. No signup is required. www.citedspy.com
• Rank.ai's free AI visibility checker — simpler brand/domain-level test across ChatGPT, Claude, and Gemini. It distinguishes being mentioned from actually being cited. www.rank.ai
• Frase's free AI Visibility Checker — another easy domain-level check; Frase also has a page-level GEO grader and an agent-readiness checker. www.frase.io
• CiteRank — more SaaS-oriented: it generates buyer questions and reports which sources AI cites, plus competitor gaps. The free diagnostic is one website/project. citerank.io

What I'd do for a docs site

I'd use Citegrade or CitedSpy rather than a generic “AI visibility score.”

Take your 10–20 highest-value docs pages and create 2–5 natural-language questions for each. For example:

“How do I configure SSO in [product]?”
“Does [product] support SCIM?”
“How do I troubleshoot a 401 from the API?”
“What is the difference between X and Y in [product]?”

Then record:

That gives you a much more actionable docs citation coverage metric than a generic AI visibility score.

One important caveat: AI citations are nondeterministic, so a single pass shouldn't be treated as definitive. Run each important query multiple times and measure citation rate rather than simply yes/no. Citegrade explicitly notes that results can vary between sessions. citegrade.com

If you tell me what your SaaS does and what docs stack you use (Mintlify, Docusaurus, ReadMe, GitBook, custom, etc.), I can suggest a free testing setup specifically for your docs, including how I'd choose the queries and score the pages.

For a SaaS docs site, I’d look for tools that measure URL-level citation, not just “does the AI know my brand?” A docs site can be mentioned while the actual API/reference/tutorial pages never get surfaced.

A few options:

• HubSpot’s AI Search Grader — good quick baseline. It gives a snapshot of how AI assistants perceive your brand/content, but it is more brand-level than docs-page-level. Cituna
• ahrefs.com — useful if you already use Ahrefs; free checks can show AI visibility signals across several AI surfaces. Cituna
• semrush.com — similar: good for seeing whether your site appears in AI answers and comparing competitors. Cituna
• citationdesk.com — specifically positioned around citation readiness and checks for whether pages are likely to be cited by assistants. CitationDesk
• rank.ai — lets you test a prompt and see whether assistants mention/cite your domain. Rank.ai

For a SaaS docs site, I’d probably also build a lightweight internal grader rather than rely only on tools:

1. Pick 50–200 real user questions:

• “How do I authenticate with API X?”
• “How do I migrate from Y?”
• “Does product support feature Z?”
• For each question, run:

• ChatGPT
• Claude
• Gemini
• Perplexity
• Record:

• Did the answer mention your company?
• Did it cite your docs URL?
• Which page was cited?
• Was a competitor cited instead?
• Was the answer correct?
• Score each docs page:

• Citation rate
• Mention rate
• Correctness rate
• Competitor displacement rate

For SaaS docs specifically, the biggest levers are usually:

• Put the answer directly near the top of pages (AI systems often prefer extractable passages).
• Add stable canonical URLs for docs pages.
• Avoid hiding critical info behind JS-only interactions.
• Add structured metadata where appropriate.
• Make “comparison,” “migration,” and “how-to” pages very explicit, since those map closely to buyer questions.

If you want a free-only stack, I’d combine:

• one AI visibility checker for broad monitoring, and
• a spreadsheet + manual monthly runs for your top 50 docs queries.

That will usually tell you more than a generic domain score because you’ll know exactly which docs pages are winning or losing citations. amicited.com

If you mean “do AI assistants actually cite my docs pages when users ask product questions?” (rather than just “is my site AI-readable?”), I’d look at tools that run real prompts and inspect citations. A few free or free-tier options:

Best fits for a SaaS docs site

1. app.citecue.com

• Good for: checking whether AI answers cite your domain and comparing against competitors
• Useful workflow: - Add important docs URLs
• Create prompts like: - “How do I configure SSO in [category] software?”
• “What are alternatives to [your product]?”
• “How do I migrate from X to Y?”
• Track whether your docs appear as cited sources
• Has free tools for AI visibility checks. CiteCue

2. citationdesk.com

• Good for: single-page citation readiness audits
• Checks things like: - extractable content
• AI-readiness signals
• structure/schema
• crawl health
• More “will this page be citable?” than “how often is it cited.” CitationDesk

3. grow.contact

• Good for: technical docs hygiene
• Looks at agent-readability factors such as: - semantic HTML
• structured data
• llms.txt
• accessibility for AI agents
• Useful if your docs are generated by tools like Docusaurus, Mintlify, ReadMe, GitBook, etc. Grow Contact

4. Build a lightweight internal grader (often the best option for SaaS docs)

For a docs site, I’d probably create a small spreadsheet/script with:

Run 20–50 “money questions” monthly. This gives you a much better signal than a generic AI score.

What I would grade for SaaS docs specifically

A good docs citation grader should check:

• Task coverage - Does a page answer the exact user question?
• Quoteability - Are there concise explanations AI can reuse?
• Canonical URLs - Does each feature have one obvious source page?
• Examples - API calls, configs, troubleshooting steps
• Freshness - Updated dates and versioning
• Navigation - Can an AI agent find the right page quickly?
• Structured data / machine-readable hints

Microsoft also has an AI Visibility citation dashboard that measures which pages are referenced in AI-generated answers, though it is more of an analytics product than a simple docs grader. Microsoft Learn

If your goal is a free lead magnet for your own SaaS docs audience, I’d avoid building a generic “AI score.” A stronger grader would take a docs sitemap, extract the top 20 pages, generate likely customer questions, and test whether those exact pages are cited. That maps much closer to developer-docs value.

Yes. For a SaaS docs site, I’d distinguish “is my site citation-ready?” from “does an AI assistant actually cite this specific docs page?” The latter is what you probably care about.

Free options worth trying

• citegrade.com — probably the closest fit. Give it a specific docs URL + target query, and it checks ChatGPT and Perplexity to see whether your page is cited, including citation position and competing pages. Its citation checker is advertised as free/unlimited. Citegrade
• citationdesk.com — useful as a broader page/site readiness grader. It gives a 0–100 score across SEO/GEO, entity, structure and crawlability, and explicitly covers ChatGPT, Claude, Perplexity and Gemini. It's free and doesn't require signup. CitationDesk CitationDesk
• citedspy.com — good for quickly running the same query across ChatGPT, Perplexity, Gemini, Claude and Grok and comparing the actual sources cited. CitedSpy
• rank.ai — simpler, but useful for a quick three-model check across ChatGPT, Claude and Gemini. Rank.ai
• nyftylabs.com — interesting if you're comfortable bringing your own API keys. It records whether Claude, ChatGPT, Gemini and Perplexity mention/cite your domain and lets you rerun the snapshot over time. NYFTY Labs

What I'd do for SaaS docs

Don't just ask:

“Does AI cite my company?”

Instead, build a small test set of 20–50 questions your docs are supposed to answer, e.g.:

• “How do I configure X in Acme?”
• “Acme API authentication example”
• “How do I handle webhooks in Acme?”
• “Acme rate limits”
• “How do I migrate from v1 to v2?”
• “What's the difference between Acme's X and Y?”

Then track, for each question:

That “correct page” metric is particularly important for SaaS docs. A tool can tell you that example.com is visible while AI is actually citing your homepage or blog instead of the canonical API reference page.

If you want something you can run repeatedly for free, I'd start with Citegrade for page/query-level verification + CitationDesk for diagnosing why a page isn't citation-ready. Citegrade CitationDesk

One caveat: AI citation results are inherently variable. Even Citegrade notes that repeated runs can produce different citations because model outputs aren't deterministic, so I'd run each important query several times rather than treating a single pass as definitive. Citegrade

Yes. If your goal is specifically “are these particular SaaS docs pages actually being cited as sources by AI assistants?”, I’d separate tools into two categories:

Best free options I’d try

• citegrade.com — probably the closest match. You give it a URL + target query, and it checks ChatGPT and Perplexity in real time, including whether your page was cited and its citation position. It says citation verification is free. Citegrade Citegrade
• frase.io — useful for a broader domain-level check. It can tell you whether ChatGPT, Perplexity, and Gemini cite your domain; the first result is free. Frase
• citedspy.com — interesting if you want to run the same question across several assistants and see the actual sources side-by-side. It currently advertises ChatGPT, Perplexity, Gemini, Claude, and Grok. CitedSpy
• fogtrail.ai — more of a broad visibility report; its free scan checks ChatGPT, Perplexity, Claude, Gemini, and Grok and reports whether you're cited, mentioned, or invisible for each query. FogTrail
• citationdesk.com — good for assessing citation readiness of individual docs, rather than proving that an assistant actually cited them. It's free/no-signup and scores pages across several citation-readiness dimensions. CitationDesk CitationDesk

For a SaaS docs site, I'd test it like this

Don't just enter your homepage. Build a little matrix:

The important distinction is citation vs. mention. An assistant saying “Acme supports OAuth” isn't necessarily useful evidence that it is using your docs. You want to know:

1. Was your URL actually cited?
2. Which exact page was cited?
3. For which questions?
4. Which competitor docs got cited instead?
5. Did the assistant extract the correct answer from your page?

For that reason, Citegrade is the first one I'd try for your use case, while CitationDesk/Frase are useful complementary graders.

If you're actually thinking about building a free grader into your SaaS/docs workflow, that's a slightly different problem—and there are some fairly simple ways to build one that tests a selected set of docs against a fixed prompt suite and produces a citation coverage %.

Yes. If your goal is specifically “give me a URL + a set of questions, and tell me whether AI assistants actually cite my docs”, I’d separate that from generic “AI visibility” graders.

My picks

1. Citegrade — probably the closest match to what you described. You provide a specific page + target query, and it checks ChatGPT and Perplexity live, including whether your page was cited and which competitors were cited instead. It says the citation checker is free. citegrade.comwww.citedspy.com

2. CitedSpy — useful if you want breadth. It runs the same query across ChatGPT, Perplexity, Gemini, Claude and Grok and shows the sources cited by each. It's free/no signup. www.citedspy.com

3. FactSentry — more SaaS/brand-oriented. It looks at whether ChatGPT mentions your product, what competitors get cited, inaccuracies, and an overall visibility score. factsentry.ai

4. Citera — interesting if you want to evaluate individual documentation pages, not merely brand mentions. It combines a page-level “citation potential” score with live AI simulations across ChatGPT, Claude, Gemini and Perplexity. citera.dev

One important distinction

Tools like IsVisible.ai are useful, but they're answering a different question: “Can AI crawlers access my site?” It checks robots.txt, llms.txt and crawler access. That's a good prerequisite, but being crawlable ≠ actually being cited. citegrade.comwww.citedspy.comisvisible.ai

For a SaaS docs site, I'd actually build a tiny test set like:

Then rerun it after documentation changes. CitedSpy is the easiest free starting point for this, while Citegrade looks better if you want to focus tightly on individual pages and competitor gaps. citegrade.comwww.citedspy.com

If you're actually thinking about building this as a free grader for your own SaaS/docs product, I can also suggest what I'd put in the grader and how I'd score “AI-citability” versus merely “AI-accessibility.”

Yes. For a SaaS docs site, I’d distinguish between two things:

1. “Is this page technically citable?” — crawlability, structured data, headings, answerability, etc.
2. “When someone asks an AI a question this page should answer, does the AI actually cite this URL?” — much more useful for docs.

For #2, these are worth trying:

• Citability — probably the closest match to what you're describing. It runs live tests across ChatGPT, Claude, Perplexity, and Gemini and reports whether you're cited, mentioned, or absent, including the cited position. It currently advertises a free, no-card scan. citability.dev
• Frase AI Visibility Checker — free/no-signup initial check; specifically tests whether AI engines cite your domain. Its GEO checker can also grade an individual page for citation readiness. www.frase.io
• GEO Checker — interesting if you want to test a set of actual buyer questions. Its free browser extension runs prompts through your own logged-in AI sessions and shows citations and competitors that appear instead. geochecker.net
• Revenue Grader — particularly relevant to SaaS because it lets you submit a page and tests ChatGPT, Claude, and Perplexity against buyer questions, showing cited vs. mentioned vs. omitted. Free scan, no login. getrevenuegrader.com
• GEO Optimizer — if you're technical and want something you can run in CI. It's open source and can audit a site plus test AI citation visibility across several engines. github.com

What I'd use for docs specifically

Don't just enter your domain and ask “Is my site cited?”.

Take your 20–50 highest-value documentation questions, e.g.:

“How do I configure SSO in [product]?”
“Does [product] support SCIM?”
“How do I rotate an API key?”
“[Product] webhook retry behavior”
“[Product] vs [competitor]”

Then measure:

That correct-page rate is especially important for SaaS docs. A domain-level “you were cited” score can look great while the AI is actually citing your changelog or homepage instead of the documentation page that answers the question.

If you want something you could potentially embed into your own docs product as a free “AI citation grader”, I can also suggest a lightweight architecture/API approach for building one yourself.

Yes. If your goal is specifically “do AI assistants cite my actual documentation pages?”, I’d separate tools into two categories:

Best free options

• EdenRank AI Visibility Checker — probably the closest match for a quick test. It runs one prompt across ChatGPT, Perplexity, Gemini, Google AI, Claude, Copilot, and DeepSeek and shows the answers plus citations. edenrank.com
• FogTrail Free AI Visibility Scan — useful for a more domain-oriented test. It checks ChatGPT, Perplexity, Claude, Gemini, and Grok and reports whether your domain is cited, mentioned, or invisible for individual queries. fogtrail.ai
• Frase's free AI tools — particularly interesting for a docs site because it has both a page-level GEO grader and a domain-level citation checker. www.frase.io
• AI Search Visibility — lets you audit individual URLs and gives an AI-readiness score plus prioritized fixes; the free tier currently allows 5 audits/month. www.aisearchvisibility.ai
• Ahrefs Free AI Visibility Checker — better for measuring overall brand/domain visibility than individual docs, but it shows cited pages and domains across several AI search surfaces. ahrefs.com

What I'd do for a SaaS docs site

I'd not rely on a generic “AI visibility score.” Build a small benchmark around your most important docs:

Then record for each prompt:

AI → mentioned? → cited? → exact URL cited? → competitor cited instead?

That's much more actionable than simply knowing that your domain has “AI visibility.”

One important distinction: crawler/accessibility checkers aren't citation graders. For example, tools like isvisible.ai mainly test whether AI crawlers can access your site and whether things like robots.txt/llms.txt permit access. isvisible.ai They can identify a prerequisite for citation, but they don't prove that an assistant actually cites a particular doc.

If you tell me what your docs stack is (Mintlify, Docusaurus, GitBook, ReadMe, custom, etc.) and roughly how many key pages you want to monitor, I can suggest the simplest free setup for automatically grading them.

Yes. For a SaaS docs site, I’d separate “is this page AI-citable?” from “does an AI assistant actually cite this page?” The second is the more useful grader.

Free tools worth trying

• Citegrade — probably the closest match. You give it a specific docs URL + target query, and it checks ChatGPT and Perplexity in real time, showing whether your page was cited, its citation position, and which competitors were cited instead. citegrade.com

Try Citegrade

• AI Search Visibility — better if you want a page-level grading system. It scores indexability, content structure, trust, schema, and “AI citeability”; its free tier currently includes 5 audits/month. www.aisearchvisibility.ai

Try AI Search Visibility

• Frase's free AI Visibility Checker — useful for a quick domain-level check across ChatGPT, Perplexity and Gemini, plus a page-level GEO score checker. www.frase.io

Try Frase's free tools

• AuditZap — nice if your concern is whether docs are technically exposed to AI: crawler access, robots.txt, schema, semantic structure, freshness, etc. It's free with no signup. auditzap.io

Try AuditZap

What I'd use for a docs site

I'd actually build your grader around a simple citation test matrix:

For each query, record:

Cited? → Which URL? → Citation position → Was the answer actually supported by that URL? → Which competitor/docs page won?

That gives you a much more meaningful Docs AI Citation Score than a generic GEO score.

If you want something free and self-hostable, there's also an open-source MCP project called Citation Intelligence that measures which URLs get cited across ChatGPT, Claude, Gemini, Perplexity, Google AI Overviews and Bing, using your own API keys. github.com
Citation Intelligence on GitHub

My pick: start with Citegrade for manual testing, then turn the matrix above into your own automated grader. That would let you test your 20–100 most important docs pages against the questions your customers actually ask, rather than merely checking whether your domain has “AI visibility.”

Yes. The key distinction is “is my docs site technically citeable?” vs. “do AI assistants actually cite these specific docs when answering relevant questions?” For a SaaS docs site, I’d prioritize the latter.

A few free options worth trying:

• GEOSource — probably the closest match to your use case. It says it checks whether AI systems such as ChatGPT, Perplexity, and Claude actually cite your content, with a free no-account scan. It also gives page-level scores for answerability, citation quality, definitions, readability, and AI accessibility. geosource.ai
• FactSentry — geared specifically toward SaaS. Its free audit runs buyer-intent queries and reports citations, competitor mentions, inaccuracies, and a visibility score. factsentry.ai
• urlrank.ai AI visibility checker — useful if you want to manually supply a question such as “How do I configure X with [your product]?” and see whether ChatGPT, Claude, and Gemini mention/cite your domain. It says the free checker uses direct provider APIs. www.rank.ai
• urlFrase's free AI Visibility Checker — another easy domain-level check for whether ChatGPT, Perplexity, and Gemini cite your site. It also has a separate free page-level GEO grader. www.frase.io
• urlAuditZap's AI Visibility Checker — better for diagnosing why a docs page may not be citeable: crawler access, semantic structure, freshness, schema, question-format headings, etc. It's free with no signup. auditzap.io

What I'd do for a docs site

Don't just enter your domain and accept a generic “AI visibility score.” Build a small test set of 20–50 questions that your docs are supposed to answer, e.g.:

“How do I rotate an API key in Product X?”
“Does Product X support SAML SSO?”
“How do I handle rate limits?”
“What happens when a webhook delivery fails?”

Then run those questions periodically across the assistants and record:

That gives you a much more useful docs citation rate than a generic AI SEO score.

One important caveat: crawler/accessibility audits aren't proof of citations. For example, an audit can establish that GPTBot/ClaudeBot/etc. can access your content, but actual citation behavior is a separate measurement. isvisible.ai

If you want one free starting point, I'd try GEOSource first, then FactSentry for the SaaS/buyer-query angle. If your real goal is specifically “grade these 30 docs URLs against these 30 questions and tell me which ones AI assistants cite”, I can also suggest a lightweight way to build that yourself for essentially $0.

Yes. For a SaaS docs site, I’d distinguish between two things:

1. “Can AI access/cite this page?” — crawlability, structure, schema, etc.
2. “Does an AI assistant actually cite this page for the questions it should answer?” — much more useful for docs.

For #2, these are the free options I’d try first:

• Citegrade — probably the closest match. You give it a URL + target query and it checks ChatGPT and Perplexity in real time, including whether your page was cited and which competing sources were cited instead. It says citation checks are free and unlimited. citegrade.com
• GeoSource — free checks across ChatGPT, Perplexity, and Claude, with no account required. More focused on whether individual content is actually citable. citegrade.comgeosource.ai
• PixelMojo's Answer Engine Citation Tester — particularly relevant to docs: enter a specific page + question, and it checks whether ChatGPT, Perplexity, Claude, and Gemini cite it, plus competitor URLs. www.pixelmojo.io
• Rank.ai's free checker — lets you submit one prompt + domain and compare ChatGPT, Claude, and Gemini, including whether they cite your site. www.rank.ai
• EdenRank — useful if you want broader coverage: its free checker runs one prompt across 8 AI surfaces, including ChatGPT, Claude, Gemini, Perplexity, Copilot and Google AI surfaces. edenrank.com

What I'd use for a docs site

I'd start with Citegrade or PixelMojo, because they're testing the thing you actually care about: specific documentation pages being cited for specific questions, rather than giving you a generic “AI readiness” score.

For example, take 10–20 important docs pages and create queries like:

“How do I configure SSO in [product]?”
“How do I authenticate with the [product] API?”
“What are the rate limits for [product]?”
“How do I troubleshoot error XYZ?”

Then record:

That gives you a much more actionable “docs citation coverage” metric than an overall GEO score.

One caveat: AI answers are nondeterministic, so one successful citation isn't proof that a page is consistently cited. For anything you want to measure seriously, run the same query multiple times and track citation rate over time. Citegrade explicitly notes this variability. citegrade.com

If you tell me what your docs stack is (Mintlify, Docusaurus, GitBook, ReadMe, custom, etc.), I can also suggest a free way to automatically grade your top 20 docs pages weekly rather than checking them manually.

Yes. If your goal is specifically “do AI assistants actually cite my docs?”, rather than just “is my site GEO-friendly?”, I’d test these:

1. Citegrade — probably the closest fit. Give it a docs URL + target question, and it checks ChatGPT and Perplexity live, showing whether your page was cited and which competing pages won when it wasn't. Citation checks are currently free. citegrade.com

2. GEOSource — particularly interesting for a docs site. It does a free check across ChatGPT, Perplexity, and Claude, with a citation-readiness score and factors such as answerability, citation quality, definitions, readability, and AI accessibility. geosource.ai

3. Frase's AI Visibility Checker — quick domain-level check for whether ChatGPT, Perplexity, and Gemini cite your domain. It also has a separate page-level GEO scorer. www.frase.io

4. CitePilot — worth trying if you want to move from one-off testing toward ongoing prompt monitoring. It offers a free citation audit and tracks multiple AI platforms. getcitepilot.com

5. SiteTest.ai — less about actual citations and more about diagnosing whether your docs are technically extractable/citable. It claims 168 free checks covering crawler access, extraction, structure, etc. sitetest.ai

For a SaaS docs site, I'd do this

Don't just enter your homepage. Pick 10–20 high-value docs pages and create questions a developer would actually ask an AI assistant, e.g.:

• “How do I authenticate with Acme API?”
• “How do I handle Acme webhook retries?”
• “What's the rate limit for Acme API?”
• “How do I paginate Acme API results?”
• “How do I upload a file using Acme?”
• “What error does Acme return when a token expires?”

Then measure:

Prompt → cited/not cited → exact docs URL cited → citation position → competitor cited instead

That's substantially more useful than a generic “AI visibility score.”

If you want one free tool to start with, I'd try Citegrade first, because it tests the thing you actually care about—whether the assistant cites a particular documentation page for a particular question—rather than merely grading the page's structure. citegrade.com

One caveat: AI citation results are inherently noisy because responses can change between runs, so don't treat a single “not cited” result as definitive. Running each important prompt multiple times gives you a much more meaningful citation rate. nicklafferty.com

If your goal is specifically “do my SaaS docs pages get cited by AI assistants?”, I’d separate this into two buckets:

1. Citation testing (does an AI answer actually reference your docs?)
2. Citation readiness (are your docs structured so AI systems are likely to use them?)

Free tools I’d look at:

1. Manual “gold standard” test (free, surprisingly useful)

Create a spreadsheet of ~20–50 questions your customers ask:

• “How do I configure X in [your product]?”
• “What is the API limit for X?”
• “How do I troubleshoot error Y?”
• “Compare [your product] vs [competitor]”

Run those prompts in:

• ChatGPT with web/search enabled
• Claude with web search
• Perplexity
• Gemini

Track:

• Was your docs domain cited?
• Which page was cited?
• Was a competitor cited instead?
• Did the model answer correctly without citing anyone?

This is still the most trustworthy approach because AI citation behavior varies a lot between assistants. www.reddit.com

2. AI Search Visibility audit tools

A few free/limited options:

• AI Search Visibility — audits individual URLs for AI citation readiness and gives scores/fixes. It has a free tier. www.aisearchvisibility.ai
• FogTrail Free AI Visibility Scan — runs queries across several AI engines and reports whether your domain appears/cited. fogtrail.ai
• GrowRanko AI Search Visibility Checker — checks technical signals like crawlability, schema, and AI-oriented page structure. growranko.comno7software.co.uk

3. Build your own lightweight grader (probably best for a SaaS docs site)

For docs, I’d make a small internal tool:

Input

• Docs sitemap URL
• Top customer questions
• Competitor docs URLs

Checks

• Does an AI assistant cite your docs for the question?
• Citation rate %
• Correct page cited?
• Answer accuracy
• Missing docs topics
• Competitor citation share

Example output:

What I’d prioritize for SaaS docs

AI assistants tend to favor pages that are:

• very explicit (“To configure X, do Y”)
• structured with headings/tables
• authoritative (official docs > blog posts)
• easy to quote (short factual passages)
• updated and versioned
• internally linked

Also make sure your docs aren’t accidentally blocking AI crawlers and that your sitemap/canonical/schema setup is clean. Some graders specifically check these technical signals. growranko.comno7software.co.uk

For a SaaS docs site, I’d probably start with a 50-query citation benchmark rather than a generic “AI SEO score.” It gives you a much clearer answer: “Can customers find our docs through AI?”

If you mean “which of my docs pages are actually getting cited as sources by ChatGPT/Perplexity/Claude?”, I’d look at AI visibility / GEO (generative engine optimization) graders rather than normal SEO tools. A few free or free-tier options:

For a SaaS docs site, I’d probably build a lightweight internal grader instead of relying only on these:

1. Export your top 50–200 docs URLs (from analytics, sitemap, or search console).
2. Create a list of prompts users ask AI assistants:
   • “How do I configure [feature]?”
   • “Does [product] support [integration]?”
   • “What is the API limit for [feature]?”
3. Run those prompts periodically in:
   • ChatGPT
   • Perplexity
   • Claude
   • Gemini
4. Track:
   • Was your docs domain cited? (yes/no)
   • Which URL was cited?
   • Citation position
   • Competitors cited instead
   • Whether the answer used your docs accurately

A simple spreadsheet can get you surprisingly far because AI citation results are noisy and change between runs. Research on AI visibility measurement also notes that single-run citation checks can be unstable, so repeated sampling is more meaningful than one-off scores. arxiv.org

For a SaaS docs team, the metric I’d care about most is not “AI mentions our brand,” but:

% of high-intent support/product questions where the canonical docs URL is cited.

That catches the real failure mode: AI answers your users correctly but cites a competitor, a blog post, or an outdated page instead of your docs. citegrade.com

If you’re technical, you could also turn this into a small internal “Docs AI Citation Grader” with a sitemap crawler + prompt set + scheduled model checks. That may be a better long-term asset than paying for a dashboard.

Yes. For a SaaS docs site, I’d separate “can AI read/crawl my docs?” from “does AI actually cite my docs?” Those are different tests.

Free tools worth trying

• Citegrade — probably the closest match to what you described. Give it a specific docs URL + target query, and it checks ChatGPT and Perplexity in real time, including whether your page was cited and which competitors were cited instead. citegrade.com
• AI Grade Tool — better for grading a page's citation readiness than measuring actual citations. It gives a 0–100 score and identifies potentially quotable passages. aigradetool.com
• isvisible.ai — useful technical complement. It checks whether AI crawlers such as GPTBot, ClaudeBot and Perplexity can access your site, plus robots.txt/llms.txt. isvisible.ai
• AuditZap AI Visibility Checker — free URL-level audit covering crawler access, structure, freshness, schema, and other citation-readiness signals. auditzap.io

What I'd do for SaaS docs

Don't just enter your homepage. Build a tiny test set like:

Then map each question to the one canonical docs page you want cited.

Run those queries periodically through ChatGPT/Perplexity and record:

cited? → citation position → exact page cited → competitor cited → whether your page actually supplied the answer

That last metric is important: simply being mentioned isn't necessarily the same as your documentation being used as evidence. Recent research on generative-search measurement explicitly distinguishes citation selection from whether the cited page's content is actually absorbed into the answer. arxiv.org

If you're looking specifically for a free grader to plug into your SaaS docs workflow, I'd start with Citegrade + isvisible.ai. The former tests the outcome you care about; the latter tests a major prerequisite.

If you're building this yourself, I can also sketch a free/open-source “AI Docs Citation Grader” architecture (crawler → query set → LLM/answer-engine calls → citation extraction → per-page score) that you could run against an entire docs site.

Yes. If your goal is specifically “do AI assistants actually cite my docs?”, I’d separate that from generic GEO/SEO graders.

A few free/freemium options worth trying:

• GEOSource — probably the closest match. It offers free checks across ChatGPT, Perplexity, and Claude, including citation-oriented scoring and, for some scans, the AI responses that reference your site. geosource.ai
• Yogoo — free, no-signup AI visibility score; checks citation/visibility across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews. yogoo.ai
• CiteSite — useful if you want to grade individual docs for citation readiness rather than just measure current citations. It evaluates structure, content quality, authority signals, etc. citesite.net
• AI Search Visibility — URL-level audit with a free tier, focused on whether pages are likely to be cited by ChatGPT, Perplexity, Google AI Overviews and others. www.aisearchvisibility.ai

For a SaaS docs site, I'd test this way

Don't just enter your homepage. Build a small test set of 10–20 important docs and create prompts such as:

“How do I configure [your product] to do X?”

“Does [your product] support Y?”

“[Your product] vs [competitor] for Z?”

Then measure:

Prompt → AI answer → cited URLs → was the correct docs page cited?

That's more meaningful than a generic “GEO score.” AI citation results can also vary substantially between runs, so a single successful citation shouldn't be treated as proof of visibility. arxiv.org

If you're thinking of building your own free grader, I actually think there's a nice product gap here: “Paste your docs sitemap → we identify your key pages → generate realistic questions → test them across AI engines → show citation rate per URL.” That would be much more actionable for SaaS documentation than another 0–100 GEO checklist.

If you mean a free “AI citation visibility grader” for a SaaS docs site — something that checks whether ChatGPT, Claude, Gemini, Perplexity, etc. mention or cite your docs when answering product questions — there are a few approaches:

Ready-made tools (free tiers / trials)

• Ahrefs AI Visibility tools — useful for tracking brand visibility in AI-generated answers (mostly SEO-oriented).
• Semrush AI Visibility tools — similar, with AI search monitoring features.
• Profound AI visibility platform — focused specifically on how brands appear in AI answers (often more enterprise-oriented).
• Otterly.AI — tracks AI search mentions and citations.

For a SaaS docs site, though, many of these are more “brand visibility” than “are my docs the cited source?”

DIY free grader (often better for docs)

A lightweight grader can work like this:

1. Collect your important docs
   • /docs/getting-started
   • /docs/api/authentication
   • /docs/integrations/slack
   • /docs/troubleshooting/...

2. Create test prompts

Examples:

• “How do I authenticate with [Product] API?”
• “How do I configure [feature]?”
• “What are the limits of [product]?”

3. Run prompts through assistants
   • ChatGPT
   • Claude
   • Gemini
   • Perplexity

4. Score each answer

Example rubric:

5. Track regressions

A simple spreadsheet can show:

• prompt
• model
• cited URL
• citation accuracy
• date tested

If you want to build this into your SaaS

A compelling free “AI Docs Citation Grader” could output:

AI Readiness Score: 72/100

Checks:

• ✅ Docs are crawlable
• ✅ Pages have canonical URLs
• ✅ API examples are machine-readable
• ✅ FAQ answers appear in AI responses
• ❌ Authentication docs are rarely cited
• ❌ Error troubleshooting pages are missing structured answers

Useful technical checks:

• robots.txt accessibility
• sitemap coverage
• structured data
• headings/question-answer formatting
• code block clarity
• duplicate docs detection
• freshness dates

For SaaS docs specifically, I’d probably build a small internal grader first rather than rely on SEO suites: AI citation behavior changes quickly, and your customers likely care about “does the assistant recommend the right docs page?” rather than generic AI visibility.

If you’re thinking of making this a lead magnet for your docs platform, a free URL-based grader could actually be a strong acquisition tool.

Yes. If your goal is specifically “do AI assistants cite my actual documentation pages?”, I’d separate the tools into two categories:

Best free options to try

1. AI Search Visibility — probably the closest match. You can audit individual URLs and get an AI-readiness score plus prioritized fixes. The free tier currently offers 5 URL audits/month. www.aisearchvisibility.ai

2. Loamly AI Visibility Checker — better if you want to test actual buyer questions. It runs 50 prompts across ChatGPT, Claude, Perplexity, and Gemini and reports mentions, competitors, and citations. www.loamly.ai

3. Ahrefs AI Visibility Checker — very easy for a quick brand-level check; no signup required. It tests visibility across ChatGPT, Gemini, Perplexity, Copilot, and Google AI Overviews. ahrefs.com

4. SiteTest AI Visibility Checker — useful if you care more about whether your docs are technically citation-ready. It checks access, extraction, structure, and citation-worthiness, with a free A–F audit. sitetest.ai

5. AuditZap AI Visibility Checker — another good free technical checker. It checks things like AI crawler access, robots.txt, llms.txt, semantic structure, freshness, and citation signals. auditzap.io

But for a SaaS docs site, I'd test differently

A generic “is my brand visible?” score isn't quite what you want. I'd create a small docs citation grader around your key pages:

Then run 5–10 variations of each important question, rather than trusting one AI response. That's important because AI citation results are stochastic; research has found substantial variation between repeated runs of the same query. arxiv.org

If you're thinking of building this as a free grader for your own site, I actually think there's a nice product-shaped gap here: “Paste your docs URL → enter 5–10 key questions → we'll tell you which docs pages AI assistants actually cite.” That's much more actionable for SaaS documentation teams than a generic GEO score.

If your goal is "Can AI assistants find and cite my documentation?", there are a few good free or freemium options. None is perfect, but together they give a solid picture.

If you're specifically trying to determine whether individual documentation pages are being used as sources, I'd also recommend building a lightweight test harness yourself. It's surprisingly effective:

1. Pick 20–50 high-value docs pages.
2. Write 5–10 realistic questions each page should answer.
3. Query multiple assistants (ChatGPT, Claude, Gemini, Perplexity).
4. Record:
   • Was the answer correct?
   • Did it cite your docs?
   • Which URL?
   • Was another source preferred?
5. Repeat weekly to see trends.

This often reveals more than an overall "AI SEO score" because you'll find pages that are:

• never retrieved,
• retrieved but not cited,
• cited only by certain assistants,
• or consistently outranked by competitors.

For an automated, free workflow, you can also:

• Keep your prompts in a spreadsheet or JSON.
• Use APIs where available to run them on a schedule.
• Compare responses over time with a simple script.
• Score pages based on citation rate and answer accuracy.

For SaaS documentation, I'd optimize for metrics like:

• Citation rate (% of prompts that cite your docs)
• Correct answer rate
• Preferred URL (which page gets cited)
• Freshness (how quickly updates appear in AI answers)
• Competitor displacement (whether your docs replace third-party blogs)

If you're interested, I can also suggest an open-source evaluation framework (using Python and LLM APIs) that grades 100+ documentation pages automatically and outputs a dashboard.

If your goal is specifically "Are my docs actually being cited or used by AI assistants?", there are a few good free (or generous free-tier) options.

For documentation sites, I'd also recommend building a lightweight custom grader because the public tools mostly focus on brands, not specific docs pages.

A simple workflow:

1. Pick 20–50 high-value documentation URLs.
2. Generate 5–10 realistic questions each page should answer.
3. Query multiple assistants (ChatGPT, Gemini, Claude, Perplexity, etc.).
4. Record:
   • Was your documentation cited?
   • Was the correct URL cited?
   • Was the answer accurate?
   • Was another site's docs used instead?
5. Compute scores like:
   • Citation rate
   • Correct citation rate
   • Answer accuracy
   • Competitor share of citations

For example:

If you're comfortable writing a bit of code, you can automate this with:

• An LLM API to generate test questions from each doc page.
• Browser automation (or APIs where available) to collect responses.
• An LLM-as-judge to score factual correctness.
• A dashboard showing citation coverage over time.

This ends up being more actionable than a single "AI visibility score" because it tells you which documentation pages are being ignored and which questions consistently fail. Many SaaS companies use a similar approach as a regression test whenever they update documentation or launch new features.

If your goal is "Can AI assistants find and cite the documentation pages I care about?", there are a few good free or mostly free approaches.

1. Open-source AI visibility graders (my top recommendation)

• llms.txt Checker – Verifies whether your llms.txt and related files are present and valid. This doesn't measure citations directly, but it's a good baseline for AI discoverability.
• Open WebUI + scripted evaluation – You can automate prompts against different models and check whether they cite specific URLs.
• DeepEval (open source) – Built for LLM evaluation. You can create tests like:
  • "How do I configure webhooks in Product X?"
  • Pass if the response cites /docs/webhooks.
  • Fail if it hallucinates or cites an outdated page.

2. A simple DIY grader (free)

This is surprisingly effective.

1. Create 20–50 representative support questions.
2. For each question:
   • Query ChatGPT, Claude, Gemini, Perplexity, etc.
   • Record:
     • Did it answer correctly?
     • Did it cite your docs?
     • Which URL?
     • Was it the preferred page?
3. Compute metrics such as:
   • Citation rate
   • Correct page rate
   • Hallucination rate
   • Average ranking of your cited page

A spreadsheet is enough to start.

3. Promptfoo (free/open source)

Promptfoo is one of the best evaluation frameworks.

You can define tests like:

- prompt: How do I rotate API keys?
  assert:
    - contains: /docs/security/api-keys

or use regexes to verify expected citations.

It's designed for regression testing, so you can rerun it after documentation updates.

4. DeepEval

DeepEval lets you score:

• faithfulness
• retrieval quality
• correctness
• citation accuracy

If you already have a RAG pipeline, it's excellent. Even without one, you can adapt it to test public AI assistants.

5. Build a crawler + evaluator

Many SaaS documentation teams now:

• Crawl their docs
• Generate hundreds of realistic support questions
• Ask multiple AI assistants
• Score:
  • Was the answer correct?
  • Which URLs were cited?
  • Were citations current?
  • Was the newest documentation preferred?

This can be done with a few hundred lines of Python using Playwright plus an LLM API for grading.

If you specifically care about AI search visibility

Track these metrics over time:

Free stack I'd recommend

• Promptfoo for test orchestration
• DeepEval for evaluation
• A Python script to query multiple assistants
• A spreadsheet or dashboard to trend citation rates over time

This gives you a repeatable "AI documentation SEO" benchmark without paying for a commercial platform.

If you're looking for something closer to Google Search Console for AI, there are newer commercial products (such as Profound, Goodie, Peec AI, and Scrunch AI), but they generally aren't free. For most SaaS teams, an open-source Promptfoo/DeepEval setup provides much of the same validation at essentially no cost.

If your goal is specifically "Are my documentation pages being used and cited by AI assistants?", there are a few good free or freemium approaches.

1. AI Search Grader (free tier)

HubSpot AI Search Grader

Pros:

• Free
• Checks how your brand appears across major AI search systems
• Gives visibility and citation-style recommendations

Cons:

• More brand-focused than page-by-page documentation coverage.

2. Profound (limited/free demos)

Profound

Designed for:

• AI visibility
• Citation tracking
• Competitive comparisons

It's one of the better enterprise tools, though the full product is paid.

3. Goodie AI

Goodie AI

Tracks how LLMs answer prompts and whether your content is represented. Depending on current offerings, there may be a free trial or limited plan.

4. Manual benchmark (surprisingly effective)

Create a spreadsheet with:

• 20–50 important documentation pages
• 50 representative user questions

Then periodically query:

• ChatGPT
• Gemini
• Claude
• Perplexity
• Copilot

Record:

• Was your product mentioned?
• Was the correct doc referenced?
• Was a URL cited?
• Was the answer accurate?

This often gives more actionable insight than automated scores.

5. Build your own free grader

For SaaS documentation, this can work well:

1. Export your key docs and canonical URLs.
2. Create a list of representative prompts (for example, "How do I configure OAuth in Product X?").
3. Query several AI assistants via APIs where available.
4. Score:
   • Correct product identified
   • Correct documentation page cited
   • Canonical URL used
   • Answer accuracy
   • Ranking if multiple sources are mentioned

You can run this weekly in GitHub Actions at little to no cost if you keep the test set modest.

6. Watch your server logs

Many AI crawlers identify themselves. Monitor requests from:

• ChatGPT-User
• OAI-SearchBot
• ClaudeBot
• PerplexityBot
• Google-Extended

Crawler traffic doesn't prove your docs are cited, but it helps confirm they're being discovered and indexed.

My recommendation

For a SaaS docs site, I'd combine:

• HubSpot AI Search Grader for a quick visibility snapshot.
• A custom benchmark with 50–100 prompts tied to your most important docs.

A custom benchmark is repeatable, inexpensive, and measures exactly what matters: whether AI assistants actually reference the documentation pages you care about, rather than just mentioning your brand. If you're comfortable with a bit of scripting, it's possible to build a useful grader in a few hundred lines of Python or TypeScript and run it automatically on a schedule.

If you mean a free “AI visibility grader” for a SaaS documentation site — something that checks whether ChatGPT, Claude, Gemini, Perplexity, etc. are likely to cite your docs — there are a few approaches.

Free / freemium tools worth trying

1. Ahrefs Webmaster Tools
   • Good for the foundation: crawlability, indexing, backlinks, technical issues.
   • Not specifically “AI citations,” but AI assistants often rely on the same discoverability signals.

2. Google Search Console
   • Free and essential.
   • Check whether your docs are indexed, which pages get impressions, and whether important docs are discoverable.

3. Bing Webmaster Tools
   • Useful because Bing’s index is used by some AI search experiences.

4. Perplexity (manual testing)
   • Create a test set of questions your customers ask:
     • “How do I authenticate with [product]?”
     • “How do I configure webhooks?”
     • “What are the API rate limits?”
   • Record:
     • Was your domain cited?
     • Which page?
     • Was the answer accurate?
     • Were competitors cited instead?

5. Lighthouse
   • Free technical grader.
   • Helps identify issues that can prevent crawlers/AI systems from understanding docs.

If I were building a simple free internal grader for a SaaS docs site

A useful MVP could be:

Input

• Docs domain
• 20–50 customer questions
• Competitor domains (optional)

Checks

• ✅ Is the page indexed?
• ✅ Does the page answer the query directly?
• ✅ Does the page contain structured metadata?
• ✅ Does the page have headings matching user intent?
• ✅ Does an LLM answer cite the page?
• ✅ Which competitors get cited instead?

Output

AI Citation Score: 72/100

Top cited docs:
✓ /docs/authentication
✓ /docs/webhooks

Missing citations:
✗ /docs/rate-limits
  Reason: competitors explain limits more explicitly

Fix:
Add a dedicated "Rate limits by endpoint" table

A lot of current “GEO/AEO” tools focus on brand mentions rather than developer docs citation coverage, so for a SaaS docs site I’d lean toward building a lightweight crawler + prompt test harness rather than relying on a generic SEO grader.

If you want existing SaaS-focused tools, look at:

• Otterly.AI
• Profound
• Peec AI

They are more AI-search visibility oriented, though their free tiers/features may vary.

For a docs site specifically, I’d start with a spreadsheet of 50 support questions + weekly Perplexity/ChatGPT checks before paying for a platform.