File availability
Fetches /llms.txt and /llms-full.txt with status, content type, byte count, and fallback-page detection.
AI-readable discovery
Check whether a public site exposes usable llms.txt and llms-full.txt files, then see line-level structure checks alongside robots.txt, sitemap, metadata, and AI crawler access signals.
Real checks
These pages use the same live scanner as the homepage. The difference is the focused report shown after the scan, not a separate static keyword page.
Fetches /llms.txt and /llms-full.txt with status, content type, byte count, and fallback-page detection.
Checks for a clear H1, short blockquote summary, H2 sections, Markdown links, and unfinished draft text.
Compares llms.txt with sitemap.xml, robots.txt, canonical URL, indexability, and AI crawler access.
Methodology
The scanner is intentionally conservative: public URLs only, no login bypassing, bounded fetches, no saved reports by default, and no promise of AI ranking or citation.
The checker only requests public files on the submitted URL's origin and follows a bounded redirect chain.
llms.txt is experimental, so the report grades whether the file is readable and useful, not whether AI systems will use it.
Submitted URLs are processed for the report response and are not stored as public reports by default.
Tool matrix
Use the matrix to move from a focused issue to the broader AI crawler and readiness report.
Limitations
Clear boundaries make the report more useful: it diagnoses technical readiness, not guaranteed visibility.
llms.txt adoption is still uneven across AI products.
This checker does not guarantee AI visibility, citation, ranking, or inclusion in any answer engine.
The free scan validates structure and related discovery signals; it does not recursively crawl every linked URL.
FAQ
Short answers for searchers, site owners, and technical SEO teams comparing AI readiness tools.
It checks public /llms.txt and /llms-full.txt availability, content type, basic Markdown structure, summary and section presence, Markdown links, sitemap, robots.txt, and page-level AI-readiness signals.
No. llms.txt is an experimental discovery file. A clean file can help expose important public pages, but it does not replace robots.txt, sitemap.xml, structured data, or useful content.
Yes. You can enter a domain, homepage, page URL, or direct file URL. The scanner normalizes the origin and checks the standard same-origin discovery files.
No. The current scanner is privacy-first and does not create public saved reports by default.