Free AI visibility tool
LLMs.txt Checker
Check whether a site has a valid llms.txt file, links key pages, and stays discoverable to AI crawlers through robots.txt.
LLMs.txt audit
Check and repair /llms.txt
Direct answer
What this tool does
LLMs.txt Checker verifies whether a domain publishes a readable /llms.txt file, whether it links canonical pages and brand facts, and whether robots.txt allows useful AI crawlers to reach it. Treat the result as a discoverability check, not a ranking guarantee; the file supports crawler guidance but does not replace schema, content quality, or citations.
File existence, structure, canonical links, brand facts, sitemap discovery, and robots access checks.
A fuller fix plan connecting llms.txt, crawler policy, schema, page rewrites, and prompt monitoring.
Output example
What a useful report should return
Illustrative sample only; these cards are not live AI answers, customer results, or competitor measurements.
File status
sample/llms.txt returns 200 with markdown sections.
Keep it concise and link only canonical public pages.
Brand facts
sampleCategory, audience, use cases, and support links missing.
Add stable facts that AI systems can reuse without guessing.
Crawler path
sampleSitemap found; OAI-SearchBot and ChatGPT-User allowed.
Avoid blocking the llms.txt path if discovery is desired.
Premium report
Unlock citation gap reports, competitor prompts, and PDF-ready client reports
Keep the free technical score, then upgrade when you need a Pro fix plan, citation-ready content briefs, saved audit history, and deeper recommendations.
What this checks
How to fix
Example report
Sample grade: Good but missing visibility signals.
Citation-ready guide
What is LLMs.txt Checker?
An llms.txt checker verifies whether a domain exposes a readable /llms.txt file, links key pages, and keeps the file discoverable through robots.txt and AI crawler access rules.
| Visibility factor | Points | Why it matters |
|---|---|---|
| AI crawler access | 20 | AI systems need permission and reachable URLs before they can evaluate your content. |
| Sitemap / llms.txt / robots health | 15 | Healthy crawl directives and canonical files reduce ambiguity. |
| Entity clarity / schema | 20 | Entity clarity helps models connect your brand, product, author, and social proof. |
| Answer extractability | 20 | Concise answers, FAQs, tables, and steps make citation more likely. |
| Citation-worthiness | 15 | Evidence, sources, comparisons, and data improve trust and answer inclusion. |
| Freshness / update signals | 10 | Visible dates and sitemap updates help AI systems avoid stale claims. |
Evidence model
How the recommendation is grounded
AI visibility work needs observable signals, not only prompt anecdotes. This page maps each recommendation back to files, structured data, visible page content, and repeatable monitoring fields.
| Signal | Method | Evidence to keep |
|---|---|---|
| Crawler access | Fetch robots.txt, sitemap.xml, llms.txt, and the homepage, then test key AI and search user agents against priority paths. | Crawler matrix, HTTP status, file content type, and blocked path list. |
| Entity clarity | Parse JSON-LD, title, meta description, H1, logo, social links, author signals, and brand facts. | Detected schema types, Organization/WebSite fields, sameAs links, and visible brand positioning. |
| Answer extractability | Check whether the page gives a direct definition, short summary, list/table structure, FAQ blocks, and source-backed claims. | H1-adjacent answer text, table/list presence, FAQ detection, and source/citation language. |
| Freshness | Compare visible dates, structured dateModified values, sitemap lastmod, and current-year evidence. | Last updated text, sitemap timestamp, and date-related metadata. |
Search intent
llms.txt checker
Users want to validate whether /llms.txt exists, has useful AI-readable sections, links core pages, and is not blocked by robots.txt.
Related long-tail searches
Page elements this query needs
Recommended fixes
How to improve LLMs.txt Checker
Related tools
Comparison
How this differs from a normal SEO check
Search rankings still matter, but AI answers add a second selection layer: the engine must be able to extract the right facts and trust the page enough to cite it.
| Approach | Covers | What to watch |
|---|---|---|
| Traditional SEO audit | Indexability, titles, descriptions, backlinks, core web vitals, and search intent. | Often misses whether AI systems can summarize, cite, and recommend the brand in generated answers. |
| Generic AI prompt test | A small set of manual prompts in ChatGPT, Perplexity, Claude, Gemini, or Google AI Overview. | Shows symptoms, but usually does not explain which technical or content signals caused the result. |
| LLMs.txt Checker workflow | Crawler access, llms.txt, schema, entity facts, extractable answers, citations, freshness, and prompt tracking. | Best used as a prioritization layer before deeper content, authority, and PR work. |
Channel coverage methodology
Prompts, citations, and source movement by channel
Use repeatable channel logs to separate technical crawl gaps from content and citation gaps. Any competitor or platform example below is a research hypothesis or illustrative comparison, not a claim about a live AI answer.
| Channel | What to inspect | Metric to log |
|---|---|---|
| AI crawler guidance | A short map of pages and brand facts. | File status, sections, canonical URLs, and robots access. |
| Core checker link | The checker adds schema, extractability, citation, and freshness context. | Use /ai-visibility-checker after file validation. |
| Crawlability link | Robots and sitemap health determine whether the file can be discovered. | Use /ai-crawlability-checker for path-level access checks. |
Competitor comparison
How to compete with Profound, Semrush, and Peec
Competitor positioning can help define long-tail checks, but it should be verified independently for each prompt and date. Citivra should win long-tail checks by showing transparent methodology, free diagnostics, and concrete fix artifacts.
Profound
Monitoring can identify missing brand mentions.
Use llms.txt as a technical foundation before buying monitoring.
Semrush AI Toolkit
SEO authority and keyword workflows.
Pair keyword demand with a clear brand facts file and citation-ready pages.
Peec AI
Competitive AI visibility tracking.
Use file health plus prompt logs to explain why competitors appear first.
Competitors and platforms
Where this fits in the AI search stack
Use the same audit structure for your domain, competitors, and category pages. The strongest opportunities usually appear where a competitor is mentioned by an AI answer but your owned pages are absent from citations.
Last updated: August 8, 2026
ChatGPT
Benefits from accessible pages, clear entity facts, fresh public sources, and pages that answer category prompts directly.
Perplexity
Often rewards pages with concise summaries, tables, dated evidence, and citation-friendly URLs.
Claude
Needs crawlable pages and clearly structured explanations that avoid burying the core answer.
Gemini
Relies on search visibility, schema, entity consistency, and Google-readable freshness signals.
Google AI Overview
Usually appears where pages already satisfy search intent and include trustworthy answer blocks.
Core topic cluster
Build the full AI visibility workflow
FAQ
Common questions
What does LLMs.txt Checker measure?
LLMs.txt Checker focuses on whether a page can be crawled, understood, summarized, and cited by AI answer systems and search engines.
How should teams use LLMs.txt Checker?
Use it to find technical blockers first, then prioritize pages that need clearer entity facts, concise answer blocks, schema, source-backed claims, and monitoring prompts.
Is this the same as traditional SEO?
No. SEO still matters, but AI visibility also depends on whether AI systems can access your pages, extract direct answers, identify brand entities, and cite reliable sources.
Do I need llms.txt?
It is not a replacement for robots.txt or schema, but it is a useful public summary that lists important pages and brand facts for AI-oriented crawlers and tools.
Should every AI crawler be allowed?
Not always. The right policy depends on your content model. This tool highlights blockers and tradeoffs so you can choose deliberately.
Can this automatically check every AI platform?
The first version focuses on technical detection and manual tracking. Automatic monitoring can be added later with platform-specific integrations.
Check llms.txt
Download a report, copy recommended fixes, generate llms.txt, or keep a manual tracking log for AI brand monitoring.