Validate your llms.txt file before AI crawlers ever see it
Paste, upload, or fetch your llms.txt and get an instant, line-by-line audit against the official llms.txt specification — structure, headings, links and syntax, checked live in your browser.
# root heading — required # Acme Docs > one-line summary > Structured API and product docs for LLMs. ## a section — link list ## Docs - [Quickstart](https://acme.dev/start): setup guide - [API Reference](https://acme.dev/api): endpoints ## Optional - [Changelog](https://acme.dev/log): release notes
Run a live llms.txt validation
Choose an input method below. Everything runs instantly in your browser — nothing is uploaded to a server.
Validation results
📑 Document structure
🧾 Raw parsed report (JSON)
Built for the actual llms.txt specification
Not a generic linter — every rule below maps to a real requirement of the llms.txt format.
Spec-accurate H1 & blockquote checks
Confirms a single required H1 title exists and that an optional blockquote summary directly follows it, exactly as the specification defines.
Section & heading hierarchy audit
Validates that H2 sections are used correctly, detects skipped heading levels, and flags improperly nested headings.
Live link syntax & URL validation
Parses every Markdown link, checks bracket/parenthesis syntax, and verifies each URL is well-formed.
Duplicate & broken-format detection
Flags duplicate links, empty sections, malformed list bullets, and lines that break Markdown list syntax.
Instant, real-time feedback
A live listener checks your input as you type, so you catch structural issues before you even click validate.
Optional-section awareness
Recognizes the special "Optional" section used for links that can be skipped when a model needs a shorter context.
How the validator works
Four steps, all running client-side — your file content never leaves your browser.
Provide your file
Paste raw text, upload a .txt/.md file, or fetch it live from a public URL.
Parse the structure
The parser walks the document line by line, identifying the H1, blockquote, H2 sections and link lists.
Run spec checks
Each element is checked against llms.txt rules: required title, valid links, correct list syntax and more.
Get an actionable report
See a score, categorized errors and warnings, a structure tree, and a downloadable report.
What is an llms.txt file, and why does it need validating?
An llms.txt file is a short, plain-text Markdown document that sits at the root of a website, right alongside robots.txt and sitemap.xml. Its job is simple: give large language models a clean, curated map of a site's most useful pages, instead of leaving an AI crawler to dig through navigation menus, ads and boilerplate HTML. As more assistants and AI search engines pull context directly from websites, having a correctly structured llms.txt file has quietly become part of a modern technical SEO checklist, sitting next to sitemap and robots configuration rather than replacing them.
The format itself is deliberately minimal. A valid llms.txt file starts with a single H1 heading naming the project or site, optionally followed by a short blockquote summary and a few lines of plain context. Beneath that, H2 headings group related links into sections, and each link follows a simple Markdown pattern with an optional note describing what it leads to. A special "Optional" section is reserved for links that can be safely skipped when a model only has room for a shorter context window. It reads more like a well organized README than a technical config file, which is exactly the point — it needs to be easy for both humans and machines to scan.
Because the format is so lightweight, small mistakes are easy to make and easy to miss: a missing H1, a link with unmatched brackets, a heading level that jumps from H2 straight to H4, or a URL that isn't actually valid. None of these throw a visible error on your site the way a broken HTML tag might, so they can sit unnoticed for months. Running your file through a dedicated llms txt checker before publishing — and again after every content update — is the fastest way to confirm your AI llms file will actually parse the way you intend.
How to validate llms.txt syntax the right way
Start by generating or drafting your file, then run it through an llms syntax checker that understands the actual specification rather than a generic Markdown linter. Paste the raw content, upload the file directly, or point the checker at your live URL, and review each flagged issue by severity. Fix errors first — a missing title or malformed link — then work through warnings like duplicate entries or empty sections. A quick llms.txt example is often the fastest way to see the expected shape before you write your own from scratch.