Free tool
llms.txt Generator
Generates a ready-to-publish llms.txt from your site's sitemap and metadata. llms.txt is how you tell AI engines what your site is and which pages matter, part of the technical floor of your AI search visibility.
How to publish it
- 1Review and edit the draft. It is a starting point built from your sitemap, not a finished file: cut pages a buyer or model does not need, and add a one-line note after each important link.
- 2Serve it at yourdomain.com/llms.txt as plain text, UTF-8. Most stacks handle this with a static file in the public directory.
- 3Keep it current. When key pages change, launch or move, regenerate or edit the file so the map still matches the site.
- 4Check the rest of the floor. The crawler access check verifies AI bots can read you at all, and the free AI visibility check shows whether the engines actually recommend you. Where they do not, the Honeyb agent does the work.
Want to get recommended by AI?
Check your AI search visibility, then let the Honeyb agent write, fix, and earn what gets you recommended. Free to start.
Frequently asked questions
What is llms.txt?
llms.txt is a proposed plain-markdown standard: a file at /llms.txt that gives large language models a curated map of a site, with its name, a one-line summary and links to the pages that matter most. It is an emerging convention rather than an official spec, but a growing set of AI crawlers and developer tools already fetch it when they visit a domain.
Does llms.txt improve AI search visibility?
It is one layer of the technical floor, not a ranking switch. No engine guarantees reading it, but publishing one costs minutes, several AI toolchains fetch it today, and a curated map of your best pages beats letting crawlers guess which of your URLs matter. The rest of the floor is crawler access and structured data, and those together decide whether engines can read and understand you at all.
What should go in it?
Your name, a one-line summary of what the site is, and the pages a buyer or a model should read first: pricing, product, docs and your key guides. Not every URL. Curation is the point, because a file that lists everything tells a model nothing about what matters. Add a short note after each important link so the model knows why it is there.
How is this different from robots.txt or a sitemap?
robots.txt says what bots may read, a sitemap lists everything that exists, and llms.txt says what matters and what the site actually is. They complement each other: access rules, a full inventory, and a curated summary an AI agent can use to orient itself in one fetch. A complete technical floor has all three in place and consistent.
Free to start
Get recommended by AI search models.
Run a free AI search visibility check, then let the Honeyb agent do the work that gets you into the answers.
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