Separate page citability from retrieval evidence
Evaluate whether the page contains an answer-shaped passage while keeping rank, authority, and indexation as a distinct evidence gate.
AI Citation Readiness Checker
Free, no signup. See whether a page gives an answer engine something clear to retrieve and cite. Citability is scored separately from retrieval evidence, and page content stays in your browser.
Before
A detailed page that is unindexed or answers only after a long introduction.
After
A retrievable page with a direct first answer, named evidence, and self-contained chunks.
| Signal | SEO | Answer readiness |
|---|---|---|
| Rank | Important | A retrieval gate |
| Direct answer | Helpful | Core citability input |
| Freshness | Contextual | Per-model multiplier |
Pasted content is analyzed in your browser. A URL is sent only to the protected fetch endpoint; paste content takes priority. After a successful URL check, only its domain is remembered locally.
| Bucket | Weight |
|---|---|
| Retrievability: rank / authority / indexation / freshness / technical / AI access | 30 / 20 / 15 / 15 / 10 / 10 |
| Citability: relevance / coverage / quotability / information gain / authority | 30 / 20 / 20 / 15 / 15 |
General preserves the base checks. Named profiles add their dated required signals; unavailable pack fields remain not evaluated.
Runs entirely in your browser — nothing you paste is uploaded or stored. Page content and scoring stay in your browser. Anonymous run-level outcome counters may be used for aggregate research; URLs, domains, IPs, and identifiers are never included, and no statistic is released below 100 runs.
Sample report Built-in deterministic example
The Try an example button uses a dated, attributed paragraph answering “What does a canonical tag do?” and deliberately leaves all external evidence blank. Its honest output shape is:
Citability: a numeric local score
Retrievability: not evaluated — add rank, authority, and indexation
Citation likelihood: not computed
✓ Direct answer near the start
✓ Visible update date
✓ Author or reviewer signal
The example does not freeze a fabricated citation probability. The live deterministic engine calculates the citability number from the supplied paragraph while the retrieval gate remains closed.
How to use it
- Paste one page’s visible text or HTML and enter the exact question it should answer.
- Optionally enter rank, authority, and indexation evidence on a 0–100 scale. Leave unknown values blank.
- Select Grade page, or use the built-in example to see the output shape.
- Improve the weakest content checks, then re-run. Do not fill retrieval fields with guesses merely to obtain a citation-likelihood number.
Site passport Local context for this saved site
Local data
Saved targets, named lists, and recent check summaries remain only in this browser.
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What the results mean
- Citability — a weighted combination of lexical chunk relevance, answer coverage, quotability density, assumed information gain, and supplied authority.
- Retrievability — a weighted score only when rank, authority, and indexation evidence are all present.
- Citation likelihood — retrievability multiplied by citability; not computed when the retrieval gate is incomplete.
- Pass / warning checks — visible content patterns for an early direct answer, update date, author or reviewer signal, plus selected profile signals.
- Consumer-product context — dated qualitative priors shown as context only; every product remains not evaluated because this checker did not query it.
How it works
The local engine extracts readable blocks, creates roughly 300-token chunks, ranks them against the target question with lexical retrieval, and scores answer-shaped sentences and quotability. The scoring module combines those values with the visible weights shown above. Unknown rank, authority, or indexation remains the literal state not evaluated; the multiplication step will not run until all retrieval evidence exists.
Features
- Text or HTML input processed in the browser.
- Separate citability and retrievability stages.
- Visible weights and a strict missing-evidence gate.
- Three actionable page checks plus a question-specific chunk match.
- Built-in example that demonstrates a deliberately uncomputed outcome.
Limitations
Lexical overlap misses synonyms and semantic matches. The content checks recognize simple wording patterns rather than meaning, and technical/access values currently use fixed assumptions. Rank, authority, and indexation are user inputs and are not verified. Dated consumer-product profiles are contextual industry priors, not provider disclosures or observations from this run. The report cannot predict a citation for any query or product.
AI answers may continue to reflect cached or previously retrieved material for days to weeks after a fix. Recheck over time before treating an unchanged answer as proof that the fix failed.
Frequently asked questions
What is the difference between citability and retrievability?
Citability describes whether the pasted page contains a relevant, answer-shaped passage. Retrievability uses external evidence such as rank, authority, and indexationStoring a crawled page in the search index so it can appear in results. Crawled is not the same as indexed — Google selects what to keep, and indexing isn't guaranteed.. A page can write a strong answer that an engine never retrieves.
Why is citation likelihood not computed?
Citation likelihoodAn AI citation is the visible source link an AI answer engine shows next to its generated text — the clickable reference that credits the web page it used. A citation's presence is a separate thing from whether the cited page actually supports the statement, and from being retrieved (read behind the scenes) or merely mentioned (named without a link); citation is driven more by brand mentions and being retrievable than by traditional ranking. is gated. If rank, authority, or indexation is blank, the tool reports those inputs as not evaluated and refuses to turn missing evidence into a numeric prediction.
Is this an AI visibility score?
No. It is a transparent page-content heuristic plus optional user-supplied retrieval evidence. It does not observe an answer engine, prompt set, citation corpus, or live model behavior.
Why are consumer AI products listed as not evaluated?
The checker analyzes only the supplied page. The dated product profiles provide context, but no product-specific prompt or citation observation occurred, so the tool does not manufacture per-product scores.
What should I do with a warning?
Read the specific check, then improve the page only when the recommendation fits the query and remains accurate. A direct answer, meaningful date, and qualified author signal are useful when they are genuine, not when added mechanically.
Feature requests for Answer Ready Grader
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Where this tool helps
Common use cases
Audit visible answer-readiness signals
Check for a direct answer near the start, a meaningful date, an author or reviewer signal, and the page-profile signals that can actually be observed in the supplied text.
Prevent a fabricated citation probability
Leave unknown retrieval fields blank and preserve the honest not-evaluated state instead of filling gaps merely to obtain a headline number.
Review a page against a named profile
Apply the dated Ecommerce, News, Local, YMYL, or SaaS checklist while keeping unavailable schema and weighting fields explicitly not evaluated.
Hand actionable findings to owners
Export visible findings as ticket-ready CSV rows so editorial, technical, evidence, and measurement work can be assigned and verified.
Watch the full workflow
AI Citation Readiness Checker walkthrough
Read the transcript
AI Citation Readiness Checker
This beginner walkthrough explains what citation readiness means, runs the built-in example, shows why missing evidence stays uncomputed, demonstrates the optional evidence gate and SaaS profile, and exports the findings. The checker never queries an AI product and cannot predict a citation.
Step 1
The AI Citation Readiness Checker reviews whether one page contains a clear passage for one target question. It scores the pasted content in your browser and shows which external evidence is still missing. Think of it as an editorial and evidence checklist, not a live test of ChatGPT, Google, or another answer engine.
Step 2
Three terms matter. Citability asks whether the page contains a relevant, answer-shaped passage that is easy to quote. Retrievability asks whether outside evidence suggests that passage can be found. Citation likelihood is the tool’s conditional multiplication of those two scores. A page can be easy to quote but never retrieved, so the stages stay separate.
Step 3
Use the checker to review answer-first sections, compare a draft with a published page, explain missing evidence to a stakeholder, apply a named page checklist, or export issues to an editorial queue. It is especially useful when you want an honest not-evaluated result instead of filling gaps just to produce a headline number.
Step 4
The formula and weights are visible. Retrievability combines rank, authority, indexation, freshness, technical access, and AI access. Citability combines relevance, answer coverage, quotability, assumed information gain, and authority. The multiplication is locked until rank, authority, and indexation are all supplied. Missing evidence never becomes a guessed zero.
Step 5
Paste the visible text or HTML from one page, then enter the exact question that page should answer. General uses the base checks. Named profiles add visible signals for a page type. Rank, authority, and indexation accept values from zero to one hundred, but only when you have a real source. Leave every unknown value blank.
Step 6
Select Try an example. The fixture inserts a short, dated paragraph that names an author and explains what a canonical tag does. It also inserts the target question. The three retrieval-evidence fields deliberately stay blank, so this example teaches the honest result before it demonstrates an optional calculation.
Step 7
The example receives a citability score of fifty-three point six out of one hundred. That is a local weighted score for the supplied paragraph and question. Retrievability says not evaluated, and citation likelihood says not computed. This does not mean zero chance of retrieval or citation; it means the required outside evidence was not supplied.
Step 8
The example passes three visible checks: it gives a direct answer near the start, includes an update date, and names an author or reviewer. These are simple pattern checks. A checkmark confirms that wording was found; it does not verify that the answer is correct, the date is meaningful, or the named person has relevant expertise.
Step 9
The consumer-product section lists dated background assumptions for products such as ChatGPT, Gemini, Google AI Overviews, Perplexity, Claude, Copilot, and Grok. Every row says not evaluated because this run made no product-specific query. The low-confidence priors are research context, not simulated results, provider disclosures, or product scores.
Step 10
For teaching only, enter seventy for rank, sixty for authority, and one hundred for indexation, then grade again. These are illustrative inputs, not measurements for the canonical-tag paragraph and not recommended thresholds. In real work, record the source, date, and meaning of each value before using it.
Step 11
Now the gate is open. Retrievability is seventy-nine out of one hundred. Because authority also contributes to citability, that score changes to sixty-two point six. Multiplying the two produces a conditional citation-likelihood score of forty-nine. These values describe the supplied inputs and fixed assumptions; they are not an observed forty-nine-percent probability.
Step 12
Choose the SaaS page profile and grade again. The profile adds dated review prompts for a clear direct answer, a last-updated date, and feature evidence. Our example passes the first two and warns that feature evidence was not observed. Only add a missing signal when it is accurate and useful for the real page.
Step 13
Read the profile boundary under the checks. Schema-type guidance and profile-specific weighting are both not evaluated because this pack does not provide them. The source, as-of date, and confidence are visible. A named profile adds lexical review prompts; it does not create evidence for unsupported fields or prove meaning.
Step 14
Download findings as tickets saves a CSV containing the visible finding IDs, severities, descriptions, target question, and selected profile. In your working sheet, add an owner, proposed change, evidence source, verification method, and final decision. The export is a handoff for review, not an instruction to implement every warning.
Step 15
Behind the interface, the local engine extracts readable blocks, creates chunks of roughly three hundred tokens, ranks them against the question with lexical matching, and scores answer-shaped sentences and quotability. Lexical matching looks for related words, so it can miss synonyms, paraphrases, and meaning that a person would recognize.
Step 16
The checker does not fact-check the page, verify user-entered evidence, observe prompts, inspect citation logs, or query a live model. Technical and AI-access values use fixed assumptions. Start by improving only accurate content signals, rerun the same question, document any external evidence, and then measure real retrieval and citations with dated observations.
Improve the answer. Measure retrieval separately.
Use the content checks to improve an accurate page, leave unknown evidence blank, and document the source and date of any values you supply. Then verify real retrieval and citations with dated observations from the systems you care about. This tool organizes a review; it does not promise an AI citation.
Common issues & how to fix them
- Warning Direct answer is not near the start Fix: Place a concise, accurate answer immediately after the relevant question or section heading.
- Warning Visible update date is missing Fix: Show a truthful published or updated date and revise the content when the subject has materially changed.
- Needs review Retrieval evidence is missing Fix: Supply rank, authority, and indexation evidence before treating retrievability as evaluated.
- Warning Claims lack citation support Fix: Attach authoritative citations directly to factual claims that readers need to verify.
- Warning Citability score is low Fix: Rewrite the strongest answer passage to be direct, self-contained, specific, and supported by evidence.