GEO / AI answers · 06 min read · Updated Sep 2026
llms.txt: a contents page for machines, not a ranking trick
An llms.txt file is a curated map of the pages you want a language model to read. It does not make those pages true, and it does not replace the HTML.
Use llms.txt as a short, honest contents page for the documents you hope machines will quote.
Point at the pages that explain the work
List the homepage, the about page, and the guides that state your actual position. Give each link a one-line description. Leave out campaigns, thin tags, and pages you would not quote yourself.
Keep the file at the root and link it from robots.txt so a careful crawler can find it. Update it when you publish a cornerstone, not on every typo fix.
Do not use the file as a cloaking layer
The descriptions in llms.txt should match the pages. A file that claims services or credentials the site does not show is a second, less honest version of the business.
The file is optional context. Models will still read whatever they crawl. Blocking a crawler in robots.txt while praising the same bot in llms.txt is a confused policy.
- Curated links only.
- Descriptions that match the pages.
- A mention in robots.txt so the file is discoverable.
Keep the HTML strong anyway
If a guide is only summarised in llms.txt and the HTML is empty until JavaScript runs, you have given machines a map to a locked door. Prerender the page.
Review the file when a guide is retired so you are not advertising a 404 as a preferred source.
Questions
Does llms.txt improve rankings?
There is no evidence it is a ranking signal. It is a courtesy map for systems that choose to read it. The pages themselves still have to be good.
Where should llms.txt live?
At the root of the host, for example https://www.example.com/llms.txt, alongside robots.txt.
Continue reading
- Citation-ready passages: one claim, one boundary, one home
- Perplexity citations: why some guides are quoted and others are skipped
- Backlinks as source trails: earn the mention before asking for it
This note is part of the Hong Kong field library from My Search / Visibility, built with Itehk.