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 indexation. A page can write a strong answer that an engine never retrieves.
Why is citation likelihood not computed?
Citation likelihood 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.
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حول الأداة
درجة صفحة قابلية الاستشهاد و اعرض ال الاسترجاع بيانات ما زال مطلوب قبل citation احتمالية يمكن يكون محسوب.
مجاني, من دون تسجيل. انظر ما إذا واحد صفحة gives واحد إجابة محرك شيء مسح إلى يسترجع و استشهد. قابلية الاستشهاد هو مُقيَّم بشكل منفصل من الاسترجاع دليل, و صفحة محتوى يبقى في الخاص بك متصفح.
الميزات
- نص أو HTML إدخال معالج في ال متصفح.
- منفصل قابلية الاستشهاد و قابلية الاسترجاع stages.
- مرئي أوزان و واحد صارم missing-evidence بوابة.
- Three actionable صفحة تحقّقات بالإضافة واحد question-specific جزء تطابق.
- Built-in مثال ذلك يوضح واحد عمدًا uncomputed نتيجة.
كيفية العمل
ال محلي محرك يستخرج readable يحظر, ينشئ roughly 300-رمز أجزاء, يرتّب هم مقابل ال هدف سؤال مع معجمي الاسترجاع, و درجات answer-shaped جمل و quotability. ال تسجيل الدرجات وحدة combines تلك قيم مع ال مرئي أوزان معروض أعلاه. غير معروف ترتيب, سلطة, أو الفهرسة يبقى ال literal حالة ليس مُقيَّم; ال multiplication خطوة سوف ليس شغّل حتى كل الاسترجاع دليل موجود.
القيود
- معجمي تداخل misses synonyms و دلالي يطابق. ال محتوى تحقّقات recognize بسيط صياغة أنماط بدلًا من معنى, و تقني/وصول قيم حاليًا استخدم ثابت افتراضات. ترتيب, سلطة, و الفهرسة هي مستخدم إدخالات و هي ليس تم التحقّق منه. مؤرّخ منتج استهلاكي ملفات تعريف هي contextual قطاع priors, ليس مزود disclosures أو ملاحظات من هذا شغّل. ال تقرير لا يمكن يتنبأ واحد citation من أجل أي استعلام أو منتج.
- إجابة أنظمة قد ذاكرة مؤقتة مجلوب صفحات و الاسترجاع فهارس, لذلك re-crawl و regeneration توقيت varies بواسطة مزود.
الأسئلة الشائعة
ما هو ال فرق بين قابلية الاستشهاد و قابلية الاسترجاع?
قابلية الاستشهاد يصف ما إذا ال ملصق صفحة يحتوي واحد ذو صلة, answer-shaped مقطع. قابلية الاسترجاع يستخدم خارجي دليل مثل باعتباره ترتيب, سلطة, و الفهرسة. واحد صفحة يمكن اكتب واحد strong إجابة ذلك واحد محرك أبدًا retrieves.
لماذا هو citation احتمالية ليس محسوب?
Citation احتمالية هو مقيّد. إذا ترتيب, سلطة, أو الفهرسة هو فارغ, ال الأداة يبلّغ تلك إدخالات باعتباره ليس مُقيَّم و refuses إلى يحوّل مفقود دليل إلى واحد رقمي تنبؤ.
هو هذا واحد AI ظهور درجة?
لا. إنه هو واحد شفاف page-content استدلالي بالإضافة اختياري user-supplied الاسترجاع دليل. إنه يفعل ليس راقب واحد إجابة محرك, مطالبة مجموعة, citation مجموعة نصوص, أو حي نموذج سلوك.
لماذا هي مستهلك AI منتجات مدرج باعتباره ليس مُقيَّم?
ال فاحص analyzes فقط ال مقدّم صفحة. ال مؤرّخ منتج ملفات تعريف وفّر سياق, لكن لا product-specific مطالبة أو citation ملاحظة حدث, لذلك ال الأداة يفعل ليس manufacture per-product درجات.
ما ينبغي I يفعل مع واحد تحذير?
اقرأ ال محدد تحقّق, ثم يحسّن ال صفحة فقط عندما ال توصية يناسب ال استعلام و يبقى دقيق. واحد مباشر إجابة, مهم تاريخ, و مؤهل مؤلف إشارة هي مفيد عندما هم هي حقيقي, ليس عندما مضاف mechanically.