LLM Visibility Checker
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, and Gemini 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, and Markdown readiness.
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, and Gemini visibility foundations
- AI model discovery and crawler access
- LLM source understanding for brand, product, and topic pages
- entity signals, topic coverage, and internal links to authority pages
- AI-readable documentation, summaries, and machine-readable 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, and internal links that explain how your website relates to the questions your audience asks.
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
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.