Group your pages under headings, add a one-line description for each, and generate a valid llms.txt file — a structured index that helps AI models like ChatGPT, Claude, and Perplexity understand what your site is about.
One page per line: Section | Title | URL | description — description is optional.
llms.txt is a proposed convention — not an official web standard, but one that's been adopted widely enough to matter — for giving AI models a clean, structured summary of a site's content at a predictable location: yoursite.com/llms.txt. Where a normal page is full of navigation, scripts, and layout markup that a model has to wade through, an llms.txt file is plain markdown: a name, a short description, and a categorized list of links, each with its own one-line summary.
robots.txt controls whether a crawler is allowed to fetch a page. sitemap.xml lists which pages exist and roughly when they changed. Neither one describes what a page is actually about — that's the gap llms.txt fills, specifically for AI models trying to understand a site's content well enough to answer questions about it or cite it accurately, rather than for traditional search engine crawling. See this post for more on how the first two differ from each other.
Upload the file to your site root so it's reachable at exactly yoursite.com/llms.txt. There's no submission step the way there is with a sitemap in Search Console — AI crawlers that support the convention check for the file directly when they visit.
No — it's one input among many, not a ranking mechanism. It makes your content easier for a supporting model to parse accurately if it does decide to reference your site, the same way a sitemap makes a page easier to discover without guaranteeing it gets indexed.
Support varies and is still evolving — this is a relatively new, community-driven convention rather than an enforced standard, so treat it as a reasonable-effort addition rather than something every AI crawler is guaranteed to read.
A sitemap is a bare list of URLs with no description of what each page contains — a crawler still has to fetch and parse every page to know what it's about. llms.txt front-loads that summary in plain text at a single, small file, which is a much cheaper way for a model with a limited context window to get an overview before deciding what (if anything) to fetch in more depth.