llms.txt Generator
Create an llms.txt file that gives answer engines a clean map of your site: what you do, and which pages are worth citing. Fill in your summary and links, then copy the result. Everything runs in your browser.
Rendered as the blockquote directly under the title. This is the line an answer engine is most likely to quote, so lead with what you do.
Start a section with ##. Then one link per
line as Title | URL | description. The
description is optional but tells an engine why the page matters.
# Example > Example is a hosted analytics tool for small product teams. It tracks events, funnels, and retention, and ships a free tier with no credit card. ## Core pages - [Home](https://example.com/): What the product does and who it is for - [Pricing](https://example.com/pricing): Plans, limits, and what each tier includes - [Docs](https://example.com/docs): API reference and integration guides ## Guides - [Getting started](https://example.com/guides/getting-started): Setup walkthrough in under ten minutes
Save the result as llms.txt at the root of your
domain, so it resolves at yourdomain.com/llms.txt.
Everything runs in your browser and nothing is uploaded.
What llms.txt is for
llms.txt is a Markdown file at the root of your domain that tells large language models what your site is and which pages matter. Where robots.txt says what a crawler may fetch, llms.txt says what is worth reading, in a format a model can parse without wading through nav, cookie banners, and footers. The convention comes from llmstxt.org and is read by a growing number of AI tools.
The summary does the heavy lifting
The blockquote under the title is the line most likely to be quoted back when someone asks an assistant what your product does. Lead with what you actually do and who it serves, name the concrete capabilities, and skip the positioning language. A vague summary produces vague citations.
Annotate every link
A bare list of URLs tells a model nothing about which page answers which question. The optional description after each link is what lets an engine pick your pricing page for a pricing question and your docs for an integration question. Sections group related pages so the structure itself carries meaning.
It is a hint, not an instruction
llms.txt is a young convention with no guaranteed support, and adoption varies by provider. Treat it as cheap insurance rather than a control surface: it costs one file to publish and may improve how accurately you are described, but it does not restrict how models use your content. For that you need robots.txt rules or authentication.
Frequently asked questions
llms.txt is a Markdown file at the root of a domain that describes a site for large language models. It carries a title, a one-paragraph summary, and sections of annotated links to the pages worth reading. The convention is defined at llmstxt.org and is intended to give models clean context instead of rendered HTML.
Put llms.txt at the root of your domain, so it resolves at https://yourdomain.com/llms.txt. That is the only location tools check, the same convention robots.txt follows.
No. robots.txt controls which URLs a crawler is permitted to fetch, while llms.txt describes what your site is and which pages are worth citing. They solve different problems and you can publish both. Neither one restricts how a model uses content it has already collected.
Support is not universal and no provider guarantees it, so treat llms.txt as a low-cost hint rather than a ranking lever. The reason to publish one is that it is a single file: if a model does read it, you control the summary it quotes instead of leaving that to whatever it scrapes from your homepage.
State what the product does, who it is for, and the specific capabilities that distinguish it. Name platforms, formats, and features explicitly. This paragraph is the most likely thing to be quoted verbatim when someone asks an assistant about you, so concrete beats clever.
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