AI retrieval access
Checks whether major AI search/retrieval crawlers are blocked by robots.txt for the submitted URL path.
AI visibility readiness
AI Search Visibility Checker
Start an AI visibility investigation with a public access baseline, then use the measurement checklist below to collect actual citation evidence. This tool does not query answer engines or measure your brand’s current visibility.
Put the report to work
How to measure actual AI visibility
Complete these steps in your own analytics, logs, and answer-engine sessions. This scanner does not collect those observations.
- Choose a stable sample. Write a small set of questions your intended readers ask. Keep branded and unbranded questions separate; avoid leading a model by mentioning your site in every prompt.
- Record each observation. Save the date, product/model, locale, exact prompt, whether web search was enabled, answer text or screenshot, and the exact cited URLs. Distinguish an unlinked brand mention from a citation to your page.
- Repeat with the same setup. Report cited runs divided by tested runs for this sample, with the sample size and dates. It is not a universal market-share or ranking estimate; answers and source choices vary.
- Investigate missing citations. Match the scan’s robots policy to verified crawler logs and HTTP/WAF events. A passing policy alone cannot prove the engine downloaded, indexed, or selected the page.
- Connect answers to outcomes. Track referral sessions and conversions separately from citation observations. Use the AEO page audit for technical fixes, and repeat the same prompt sample after a documented change.
Google’s AI search features need no special AI text file or special schema. Its normal search requirements still apply. See Google’s guidance on AI features and our scope and scoring explanation.
Included checks
What you can check
Use the findings to decide which page or discovery-file changes to make first.
Page understanding
Reports title, H1, canonical, noindex directives, readable initial HTML, and syntax errors in any published JSON-LD. It does not grade factual quality or fully validate schema.org markup.
Discovery foundations
Checks declared sitemaps and the conventional fallback. llms.txt files are shown as optional experiments outside the readiness score.
Methodology
How to read your report
Review the observed signals and check details before changing your site.
View check and scoring details
Record a public baseline
Keep the exact source URL, scan timestamp, matched bot rules, and HTTP result so you can compare later changes with the same evidence.
No false visibility claims
The report separates readiness from live AI answer visibility so the result stays honest and reproducible.
Measure citations separately
Use a repeatable prompt sample and record cited URLs. Keep bot visits, answer mentions, linked citations, and referral sessions as separate measures.
Related tools
Choose your next check
Check a specific bot policy or explore another part of your page’s search readiness.
AI Crawler CheckerRun the full crawler access scan for robots.txt, AI bots, headers, page signals, sitemap, and llms.txt.llms.txt CheckerValidate AI-readable discovery files and see how they align with sitemap and crawler policy.AEO CheckerCheck technical Answer Engine Optimization readiness from public page and discovery signals.AI Search Visibility CheckerReview whether a URL has the technical foundations AI search systems need before any ranking or prompt testing.MethodologyUnderstand the scoring model, limitations, bot list, and public-scan boundary.
Scope of the report
Scope of the report
- This page does not query ChatGPT, Gemini, Claude, Perplexity, Copilot, or Google AI Overviews.
- It cannot prove whether a brand appears in AI answers.
- It is useful as a technical prerequisite check, not as a complete AI visibility monitoring platform.
FAQ
Common questions
Short answers for searchers, site owners, and technical SEO teams comparing AI readiness tools.
Is this a real AI search visibility checker?
It is a technical baseline checker with a measurement workflow. It does not check live answers, return a citation share, or confirm indexing. Use the scan to identify access issues, then collect answer evidence separately.
Why build this page if broad AI visibility is hard to measure?
Broad AI visibility is difficult to prove from one scan. This page focuses on technical prerequisites that can be checked from a public URL, so the result stays concrete.
What should I do after this scan passes?
Use the result as a baseline, then test real AI prompts, track cited sources, and improve content authority, freshness, and topical coverage.
Does the scan save my URL?
No. Scans are not saved as public reports.