LLM Visibility Checker
LLM Visibility Checker is a tool that analyzes whether large language models such as ChatGPT, Claude, Gemini, Perplexity, Grok, and Google AI Overviews can discover, understand, and reference your website.
Check whether AI models and answer engines can discover, understand, and connect your website with the topics your audience searches for.
An LLM visibility checker reviews whether AI models such as ChatGPT, Claude, Perplexity, Gemini, Grok, and Google AI Overviews can access pages, understand entities and topics, and connect a website with relevant user questions.
TruboRank AI helps improve LLM visibility foundations through AI model discovery checks, crawler access review, entity and topic clarity, content structure guidance, llms.txt, Link headers, Markdown readiness, AI crawler signals, AEO, and GEO.
Supported AI Platforms
TruboRank AI does not claim control over any AI platform. It evaluates the visibility foundations that make a website easier for AI search systems, AI crawlers, and large language models to find, parse, summarize, and cite.
| Platform | How TruboRank AI Evaluates Visibility |
|---|---|
| ChatGPT | Checks crawl access, GPTBot-related access signals, clear answers, entity clarity, source pages, and content that may support ChatGPT-style responses. |
| Claude | Reviews whether public pages are crawlable, semantically clear, well-structured, and useful as source material for Claude-style research and summaries. |
| Gemini | Checks Google-oriented discovery foundations such as indexable pages, sitemap signals, structured data, canonical clarity, and answer-ready content. |
| Grok | Reviews public access, source clarity, concise explanations, topical authority signals, and internal links that help AI systems understand brand and topic relationships. |
| Perplexity | Evaluates citation-readiness signals including crawlable source pages, direct answers, factual summaries, canonical URLs, and pages that match research-style prompts. |
| Google AI Overviews | Checks SEO foundations, structured data, canonical tags, passage clarity, entity relationships, and AEO content that can support AI-generated search summaries. |
Common LLM Visibility Problems
Most LLM visibility problems come from access, structure, or meaning gaps. A page may exist for users but still be difficult for AI crawlers and answer systems to discover, interpret, or reference.
- robots.txt: Robots rules can accidentally block GPTBot, ClaudeBot, PerplexityBot, Googlebot, or other AI crawlers from important public pages.
- sitemap.xml: A weak or missing sitemap makes it harder for crawlers to find important URLs, especially deep product, documentation, and intent pages.
- llms.txt: A missing llms.txt file removes a useful machine-readable guide that can point AI agents toward authoritative pages and Markdown resources.
- Markdown accessibility: Markdown alternatives can make long pages, docs, and guides easier for LLMs and AI agents to parse cleanly.
- canonical tags: Incorrect canonical tags can confuse source selection and cause AI systems to associate answers with the wrong URL.
- structured data: Schema does not guarantee citations, but it can reinforce entities, FAQs, products, organizations, and page meaning for search systems.
- Link headers: Link headers can expose sitemaps, service documents, and alternate Markdown resources to crawlers and AI agents.
- blocked AI crawlers: AI visibility can be limited when GPTBot, ClaudeBot, PerplexityBot, or related crawlers are blocked without a clear policy decision.
- Poor semantic structure: Long, vague sections without direct answers, summaries, or clear headings make extraction and citation harder.
- Missing entity relationships: AI systems need to understand how your brand, products, services, topics, locations, and proof points relate to each other.
Check your website's AI discoverability signals.
Run a free scan for robots.txt, sitemap discovery, Link headers, Markdown readiness, and AI bot access.
What this checker analyzes
- ChatGPT, Claude, Perplexity, Gemini, Grok, and Google AI Overviews visibility foundations
- AI model discovery and crawler access for GPTBot, ClaudeBot, PerplexityBot, and related AI crawlers
- LLM source understanding for brand, product, service, and topic pages
- entity signals, topic coverage, semantic structure, and internal links to authority pages
- AI-readable documentation, summaries, structured data, llms.txt, Link headers, and Markdown resources
Why it matters
LLM visibility depends on more than technical access. AI models and answer engines need clear entity signals, consistent topic coverage, useful summaries, structured data, and internal links that explain how your website relates to the questions your audience asks. Strong AI discoverability supports AI Visibility, AI Search Optimization, AEO, and GEO work.
Common issues
- Brand pages buried in navigation
- No concise summaries or clear entity descriptions
- Missing documentation links or topic hubs
- Blocked crawlers or weak machine-readable resources
- No internal links that connect the brand with relevant topics
- Weak canonical tags, structured data, or entity relationships
How to use this checker
Start with a live scan of your website URL. Review the status of each signal, then fix the highest-impact blockers first. Technical blockers should usually be handled before content optimization because AI systems need access before they can evaluate page quality.
- Run the free scan on your homepage or a high-value page.
- Review crawl access, sitemap discovery, headers, and AI-readable resources.
- Open each warning and confirm whether it affects important public content.
- Fix server-level issues such as robots.txt, Link headers, and content types.
- Improve page-level content with direct answers, summaries, FAQs, and internal links.
- Re-run the scan after changes to verify the result.
What a strong result looks like
A strong result means important pages are crawlable, key resources are discoverable, and the content gives AI systems enough structure to understand the topic quickly.
- robots.txt allows the crawlers you want to support.
- sitemap.xml exposes important URLs.
- headers or HTML links point to useful AI-readable resources.
- content includes concise answers and supporting context.
Who should use it
This checker is useful for founders, marketers, SEO teams, developers, agencies, and technical content teams that want to improve AI search readiness without guessing.
It is especially useful before launching new landing pages, documentation, product pages, comparison pages, or AI visibility campaigns.
Implementation checklist
- Confirm the page returns a successful HTTP status.
- Confirm the page is not blocked by robots.txt.
- Make sure the page appears in your sitemap or is internally linked.
- Add direct answer content for the primary user question.
- Add related links to nearby AEO, GEO, llms.txt, or AI crawler topics.
- Document technical changes so they can be repeated across the site.
How Pro helps fix it
Pro helps build LLM visibility foundations with intent page ideas, entity clarity improvements, internal linking suggestions, and AI-friendly content structure prompts.
FAQ
Does this track AI mentions?
This page focuses on readiness and visibility foundations, not guaranteed mention tracking.
What improves LLM visibility?
Clear pages, crawl access, answer summaries, topical coverage, and machine-readable resources can help.
Should brands create intent pages?
Often yes. Intent pages can help AI systems map questions to focused source material.
What is LLM visibility?
LLM visibility is the degree to which large language models can discover, understand, retrieve, summarize, and potentially reference a website as a useful source.
How is LLM visibility different from AI visibility?
LLM visibility focuses on large language models and AI assistants. AI visibility is broader and can include AI search results, AI Overviews, answer engines, crawler activity, and generated recommendations.
How do I check if ChatGPT can see my website?
Start by checking whether important pages are crawlable, whether GPTBot is allowed by your robots.txt policy, whether pages are internally linked, and whether the content clearly answers relevant questions.
Can a checker guarantee ChatGPT citations?
No. ChatGPT citations and recommendations are controlled by the platform. A checker can identify blockers and improve source readiness, but it cannot guarantee inclusion.
Does robots.txt affect LLM visibility?
Yes. Robots rules can allow or block specific crawlers. If important AI or search crawlers cannot access public pages, visibility and source discovery may be weaker.
Does llms.txt help LLM visibility?
llms.txt can help by giving AI agents a concise map of important pages, documentation, and Markdown resources. It should support, not replace, sitemap and internal linking.
Why does Markdown matter for AI search?
Markdown can reduce parsing friction for AI agents by presenting content in a clean, text-first format with headings, links, lists, and summaries.
Do canonical tags affect AI citations?
Canonical tags can influence which URL is treated as the preferred source. Clear canonical signals reduce confusion when similar pages or duplicate URLs exist.
What content helps AI systems cite a page?
Useful source pages usually include direct answers, concise summaries, factual support, clear headings, entity context, FAQs, comparison information, and stable URLs.
Is LLM visibility the same as SEO ranking?
No. SEO ranking focuses on search result placement. LLM visibility focuses on whether AI systems can understand and use your content in answers, summaries, citations, or recommendations.
How does AEO support LLM visibility?
AEO supports LLM visibility by making answers easier to extract through direct definitions, question-led headings, concise passages, FAQs, and structured explanations.
How does GEO support LLM visibility?
GEO supports LLM visibility by improving topic coverage, entity clarity, comparison content, intent pages, and source usefulness for generative answers.
Which AI crawlers should I know about?
Common crawler names include GPTBot, ClaudeBot, PerplexityBot, Googlebot, Google-Extended, Bingbot, and other AI or search-related user agents.
Why is my website invisible in AI search?
Common reasons include blocked crawlers, missing sitemap coverage, vague content, weak internal links, no direct answers, missing entity context, and poor machine-readable resources.
What pages should I optimize first for LLM visibility?
Start with your homepage, product or service pages, pricing page, comparison pages, documentation, FAQs, and high-intent pages that answer buyer or research questions.
How often should I recheck LLM visibility?
Recheck after publishing important pages, changing robots.txt, updating sitemap or canonical rules, adding llms.txt, or restructuring content for AI Search Optimization.