llms.txt
llms.txt is a proposed standard — a plain-text file in Markdown format placed at a domain's root (at /llms.txt) whose job is to help large language models find and understand a website's most important content. It emerged in response to the growing role of language models and AI assistants in how people access information.
How llms.txt works
The problem it addresses is practical: web pages contain plenty of material irrelevant to a model — menus, scripts, ads, footers — while the context window of AI models is limited. An llms.txt file provides a tidy, stripped-down map of the content: a short description of the site plus a list of links to key pages with notes on what each resource contains. Markdown is easy for both humans and machines to parse. A variant, llms-full.txt, is sometimes used to carry the full documentation content in a single file.
Practical application
llms.txt is especially useful for documentation sites, knowledge bases and large product sites where you want AI assistants to cite and summarize your offering accurately. It is worth distinguishing from robots.txt: robots.txt states what bots must not crawl, whereas llms.txt does the opposite — it actively highlights which content matters most and presents it in an accessible form.
Keep in mind that this is a community-proposed standard rather than an official provider requirement, so adherence depends on the specific tool. Just as an XML sitemap does not guarantee indexing, llms.txt does not guarantee a model will use it — but it is an inexpensive step toward visibility in AI-powered search.
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Najczęstsze pytania
How is llms.txt different from robots.txt?
robots.txt controls what bots may crawl and index, mainly for search engines. llms.txt is the inverse and complementary — it doesn't forbid, it points AI models to the most important content and presents it in accessible Markdown, making it easier to understand.
Is llms.txt an official standard that AI models follow?
It is a community-proposed standard, not an official requirement from any provider. Not every AI model or tool respects it. Implementing it is a low-cost bet on the future, but it does not guarantee that a given AI system will actually use the file.
