LLMS.TXT V2 SPECIFICATION VALIDATOR

Is Your llms.txt Actually Usable as an AI Knowledge Surface?

llms.txt is an emerging machine-readable knowledge-directory proposal. HTML&HTML validates structure, links and v2 discovery relationships without claiming it is a Google Search ranking requirement.

v2 SpecificationLink Reachabilityrel=describedbyStrict Grammar

Free llms.txt validation

Enter a domain to test /llms.txt discovery, syntax, and link reachability.

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Public HTTP/HTTPS surfaces only. Private or local targets fail closed.

HTML&HTML / LLMS.TXT

Precise syntax, link health, and agent discovery.

Evaluated with proposal-grade governance according to official community specifications.

01 / SYNTAX

Header & Structure

Verifies single H1, blockquote summary, and formatted markdown section lists.

02 / LINKS

Link Probe Verification

Probes linked documentation URLs to ensure they return HTTP 200 without broken redirects.

03 / DISCOVERY

HTTP & HTML Discovery

Checks rel=describedby Link headers and HTML link elements pointing to your llms.txt file.

EPISTEMIC BOUNDARY

Honest standard governance

llms.txt is an evolving community proposal, NOT an official IETF or W3C web standard. We never claim it guarantees AI rankings.

DISCLOSURE

We test real HTTP status codes on linked files rather than guessing their existence.

FAQ

Frequently Asked Questions

What is the difference between llms.txt and llms-full.txt?

llms.txt serves as a concise directory of curated markdown links, while llms-full.txt contains the aggregated full text of documentation for direct model ingestion.

How should llms.txt be discovered?

Through root placement (/llms.txt) and via rel='describedby' Link headers or link elements on key HTML pages.

Why did my llms.txt fail validation?

Common causes include missing H1, missing blockquote summary, unbulleted link entries, or linked URLs returning 404/500 errors.

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Your customer asks AI ‘who should I choose?’ Is your website in the consideration set?

llms.txt interest is real, but the claim must be precise. Google Search does not use llms.txt for AI Search visibility. HTML&HTML validates it as an emerging machine-readable knowledge surface without treating it as a replacement for sitemaps, robots.txt, crawlable HTML or internal links.

BE DISCOVERABLE BY AI

robots.txt, sitemaps, canonicals, indexability and AI crawler access form the discovery foundation.

BE UNDERSTANDABLE

GEO, AEO, LLMO, entity graphs, schema and answer extractability reduce machine ambiguity.

BE SOURCE-READY

RAG/retrieval, original information, E-E-A-T, freshness and evidence support source eligibility.

TURN OPPORTUNITY INTO DEMAND

AAO, accessible journeys, intact links, measurable referrals and clear CTAs connect AI discovery to commercial action.

Recommendations, rankings, citations, traffic, customers and revenue are not guaranteed. HTML&HTML measures website-side technical and content blockers; it does not claim control over external AI systems.