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AI Search Readiness Report

Free, no signup. Five foundations—permission, extractability, renderability, operability, and commerce readiness—feed a four-stage explanation of whether an AI system can retrieve, use, cite, and accurately represent one page. These stay independent rather than becoming one invented AI score.

Built by Patrick Stox

Five separate tests · registry 2026-07-29

Crawler access is only the first layer

Permission

Is the crawler allowed?

Extractability

Are useful facts present in raw HTML?

Renderability

Does JavaScript successfully expose them?

Operability

Can an agent identify and use semantic controls?

Commerce readiness

Do page, schema, feed and checkout facts agree?

HTML remains primary. llms.txt, UCP, and other protocol files are optional distribution layers and cannot compensate for inaccessible or unextractable HTML.

Validate a protocol response

Upload verified-bot log evidence

Expected columns: crawler, timestamp, url, status, verification. A user-agent string alone is never treated as verified identity.

No log evidence uploaded.

Method note: stage weights are provisional and visible. An unavailable check never becomes a pass or a zero; it lowers the stage’s confidence instead. This observation describes the named consumer product at the recorded query time. A model API with search is an execution surface, not a proxy for the provider’s consumer product. Results can correlate, but they are not interchangeable.

General preserves the base readiness run. Named profiles add required page-signal checks; unavailable schema guidance and weights are shown as not evaluated.

Add observed answer evidence and retrieval-path inputs

When supplied, this also enables one bounded retrieval-off brand observation. It is not a query of ChatGPT, Gemini, or another consumer search product.

Checks run from our server; we fetch the URL you enter and don't keep the results. 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.

Feedback
Report a bug

Found something broken in Ai Search Readiness Report? Let us know what happened — this goes straight to a private triage queue, not a public list.

What will be sent 
 No tool inputs, uploads, pasted source, complete results, query parameters, or URL fragments are attached automatically. You can edit or remove the selected passage above. Browser and anti-abuse metadata is processed for spam prevention. 
  
 
  
 
 
  
 
 
   
 
 
Sample report Honest output shape
 
Suppose the public files and page HTML are fetchable, while rendered-page evidence and the optional AI-probe budget are unavailable. A faithful report does not fill those gaps with zeros:
 
Retrieve · scored from the crawler evidence that was evaluated · reduced confidence
Use · not evaluated where rendering or additional inputs are required
Cite · evaluated modules shown individually; unavailable modules excluded
Believe · not evaluated when the current run has no supporting module evidence
 
This is a static explanation of state handling, not a captured score for a named site. Live numeric results depend on the entered URL and the modules available during that run.
 
 
 
How to use it
  1. Enter the complete URL of one public page and choose its profile.
  2. Complete the anti-abuse check and select Run readiness report.
  3. Start with the four-stage summary, then expand each stage to see evaluated and unavailable modules.
  4. Fix explicit access or content findings first. Re-run after publishing, while allowing for provider-specific cache lag.
 
 
 
       
     
     
 
What the results mean
  • Retrieve — whether an answer system can discover and fetch the page.
  • Use — whether the available page content is usable by the evaluated modules.
  • Cite — signals related to selecting and attributing a page as a source.
  • Believe — signals related to identity, support, and accurate representation.
  • Confidence — how much of the provisional stage weight was actually evaluated.
  • Not evaluated — unavailable evidence, never an inferred pass or error.
 
How it works
A protected run receives a bounded request budget, compares browser and GPTBot responses, fetches robots.txt and public agent-discovery files through SSRF-guarded endpoints, models retrieval chunks from the captured HTML, and checks the exact URL against recent Common Crawl indexes. It also evaluates answer structure, citations, entity facts, and parseable freshness evidence. If you supply a brand, one named Workers AI observation is added with model and query-time attribution. Each evaluated numeric module contributes its published provisional weight; unavailable evidence remains reason-coded not evaluated.
 
Features
  • Four-stage funnel instead of a universal composite score.
  • Visible per-module weights, findings, and fix links.
  • Per-crawler/model breakdown when a module has that evidence.
  • Reason-specific unavailable states for fetch, render, AI, timeout, and input limits.
  • Protected, bounded network runs and shareable URL state.
 
Limitations
Weights are provisional. The chunk, freshness, and entity-fact checks are deterministic approximations over captured HTML, while the optional brand check is one retrieval-off Workers AI observation. A fetch from this service can differ from a provider’s geography, identity, cache, or index. The report does not query commercial answer products, observe their private retrieval systems, or guarantee retrieval, use, attribution, or factual treatment.
 
Frequently asked questions
Why are there four stages instead of one AI readiness score?
Retrieval, use, citation, and accurate representation can each report errors independently. Keeping them separate prevents a strong content signal from hiding an access error or an unavailable module.
What does not evaluated mean?
The module had no usable evidence because it needs another input, exceeded a budget, timed out, failed to fetch, or does not apply. It is excluded from the stage score and lowers confidence rather than becoming zero.
Does a strong report guarantee AI citations?
No. The report checks observable page and access signals. It cannot see every provider’s index, ranking, generated answer, cache, or source-selection system.
Why can a recent fix take time to appear?
Answer systems may cache fetched pages, retrieval indexes, or generated responses. Re-crawl and regeneration timing varies by provider, so this report can verify the current public page without proving that a provider has refreshed its copy.
What modules does the current public run evaluate?
The public run checks crawler and edge access, recent Common Crawl presence, public agent-discovery signals, modeled chunk usability, answer and citation evidence, freshness, entity facts, and—when you provide a brand—a bounded retrieval-off model observation. An unavailable dependency remains not evaluated.
 
 
Next stepQuotability & Entity-Preserving Rewriter — generate the corrected version.

People also explore
ToolAI-Crawler Access CheckerToolChunk TesterToolAI Content AuditArticleAI Search OptimizationArticleGenerative Engine Optimization (GEO)ArticleAI Crawlers
 
 
 
Feature requests for Ai Search Readiness Report
 

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ツールについて
AIクローラーがページを取得できるかを独立に確認し、将来の利用、引用、表現に関するチェックのうち利用できないものを示します。
段階ごとの重みを表示し、単一のAIスコアにまとめず、取得と証拠の状態を分けて報告します。
機能
  • AIクローラーの取得可否
  • 利用、引用、表現チェックの段階表示
  • 段階ごとの重みと未確認理由
  • 単一スコアを避けた独立レポート
仕組み
指定URLとrobots設定を確認し、許可された取得、表現、引用に関する段階を個別に評価します。観測できた証拠、未確認の理由、段階の重みを分けて表示します。
制限事項
  • レポートは取得した公開応答と設定に基づくもので、AIシステムの将来の利用、引用、回答品質、トラフィックを保証しません。
  • クローラー、robots、キャッシュ、ネットワークの変化で結果が変わる可能性があります。
よくある質問
AI検索で引用されることを保証しますか？
いいえ。取得可能性と構造的な手掛かりを確認しますが、AIの選択、引用、回答、トラフィックを保証しません。
1つのAIスコアで順位を表しますか？
いいえ。段階ごとの重みと証拠を表示し、単一スコアへの過度な集約を避けます。
ログイン後のページを調べられますか？
公開URLに限ります。認証情報、非公開コンテンツ、ユーザー固有の状態を推測しません。