Generate a clean, spec-compliant llms.txt file for your website in seconds — so AI crawlers like ChatGPT, Claude and Perplexity understand your most important pages.
llms.txt is a simple Markdown file you place at the root of your domain. It gives AI assistants a curated, easy-to-read map of your most important pages — your products, docs, guides and key landing pages — without forcing them to crawl noisy HTML.
Think of it as a friendly index for large language models. A clear llms.txt helps AI engines understand what your site is about and which pages to cite, improving how your brand shows up in AI answers.
Paste your domain. We fetch your homepage and sitemap to learn your structure.
We extract your title, description and key pages, then group them into clean sections.
Grab the ready-to-use llms.txt and upload it to your site root at /llms.txt.
llms.txt is a proposed open standard that gives AI assistants and large language models a single, curated map of the content on your site that matters most. It lives as a plain markdown file at the root of your domain — for example, https://yourdomain.com/llms.txt — and it lists your most important pages with short, human-written descriptions. The idea is simple: instead of forcing an AI crawler to guess which of your thousands of URLs are worth reading, you hand it a clean, prioritized index it can ingest in one request.
The format is deliberately minimal markdown. It opens with a single H1 (# Your brand) that names the project or company, an optional blockquote (> a one-line summary) that captures what you do, then a series of H2 sections (## Docs, ## Products, ## Guides) whose bullet points are markdown links to the underlying pages. Each link can carry a short note explaining what the page covers. Because it is just markdown, an LLM can parse it instantly and the descriptions add the context a raw URL list never could.
llms.txt was proposed because the web was built for browsers and search engines, not for the limited context windows of language models. A modern site ships heavy HTML wrapped in navigation, scripts, cookie banners and ads — noise that wastes the tokens an AI has to spend reading you. llms.txt strips that away: it points the model at the signal, in a format it already understands, so it can find, understand and cite your key content far more reliably than by crawling raw HTML.
There is a companion file, llms-full.txt, that goes one step further by including the actual full text of your key pages in markdown, not just links to them. /llms.txt is the curated table of contents; /llms-full.txt is the whole book inlined. Together they let an AI either pull a quick map of your site or read your core content directly without making a single extra request — which is exactly what you want when an assistant is deciding whether to recommend you.
A practical sequence for generating, curating, structuring, hosting and maintaining the file so it earns its place in AI answers.
Use the generator above to crawl your site and produce a starting llms.txt: a title, a summary and your most linkable pages already formatted as markdown. A machine draft is the fastest way to a working file — you then edit it down to what truly matters.
Cut the file to the 20–60 URLs an AI would genuinely need to understand and recommend you: docs, product pages, pricing, key guides and your about page. Drop tag pages, pagination, login screens and thin content. A short, high-signal file beats an exhaustive one.
Open with a single # H1 naming your brand and a > blockquote that says in one line what you do and who for. This is the first thing the model reads — make it unambiguous so the AI resolves your entity correctly before it follows any link.
Group links under descriptive ## H2 headings — Documentation, Products, Guides, Company — and give each link a few words of context after it. Sections let an AI jump straight to the part of your site relevant to the question it is answering.
Deploy the file at /llms.txt so it resolves at https://yourdomain.com/llms.txt, served as text/plain or text/markdown. The root path is the convention crawlers look for — a file buried in a subfolder will not be found.
If your key pages are short and stable — documentation especially — publish an /llms-full.txt that inlines their full markdown. It lets an assistant read your actual content in one fetch instead of crawling page by page, which is ideal for context-window-limited models.
Treat llms.txt as living infrastructure. Regenerate it when you launch products, restructure docs or retire pages, and remove dead links promptly. A stale file that points to 404s teaches AI to distrust the rest of it.
Open the URL in a browser to confirm it renders as plain markdown, check that every link resolves, and watch your server logs for AI crawlers fetching it. Pair it with a clean robots.txt and sitemap.xml so every signal you send to AI engines agrees.
The vocabulary of making your site readable to AI, in plain language.
Any site whose content AI assistants might surface gains from handing them a clean map.
Developer docs are the canonical fit. An llms.txt — or a full llms-full.txt — lets ChatGPT, Claude and Perplexity read your API references and guides accurately, so the code and answers they generate about your product are correct.
Point AI at your product pages, pricing, integrations and use cases so that when a buyer asks an assistant for the best tool in your category, the model has clean, current facts about you to draw from and recommend.
Media and blogs can surface their cornerstone articles and topic hubs, helping AI find the authoritative pieces to cite rather than scraping noisy archive pages, tag listings and pagination.
Highlight category pages, buying guides, shipping and returns policies, and flagship products so AI shopping assistants describe your store accurately and surface the pages that convert.
An llms.txt is a great first step. Get your free RAIVE Score to see exactly how ChatGPT, Claude and Perplexity describe and rank you today.
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