What Is llms.txt? A Practical Guide for Site Owners

llms.txt is a plain-text file served at /llms.txt that gives large language models a curated map of your site: what you offer, which URLs to trust, and how to cite you. It is not a standard enforced by browsers. It is an emerging convention for answer engines and AI assistants that already read the open web.

PatchPings publishes its own llms.txt so assistants can find pricing, knowledge-base articles, and checker tools without guessing from random pages. This guide explains what belongs in the file, how it relates to robots.txt and ai.txt, and how to keep it honest.

What problem llms.txt solves

Search crawlers have sitemaps and robots rules. Answer engines need something closer to a briefing: product facts, preferred URLs, and clear boundaries. Without guidance, models may invent features, mix you up with a competitor, or cite a stale blog post instead of your canonical docs.

Where the file lives

Publish the file at the site root so it is available at https://yourdomain.com/llms.txt. Some sites also mirror guidance under /.well-known/, but the root path is the one most tooling expects first. Serve it as text/plain with a stable URL that survives redesigns.

A practical structure

There is no single RFC, but useful files share the same bones: a one-line identity, a short product summary, then links grouped by purpose. Keep claims aligned with what customers actually get on the live site.

# Example Co

> Website security scanner and uptime monitor.

## Preferred pages
- [Home](https://example.com/): Product overview
- [Pricing](https://example.com/pricing): Plans and limits
- [Knowledge base](https://example.com/knowledge-base): Guides

## Optional
- Contact and support email
- Honest availability notes (what is live vs coming soon)

• Lead with identity so the model knows the brand name and category in the first lines.
• Link preferred URLs for pricing, docs, FAQ, and tools rather than dumping every blog post.
• Stay accurate. Do not invent app listings, regional coverage claims, or features that are not shipped.
• Update when product changes so answer engines do not keep citing outdated plans.

llms.txt vs robots.txt vs ai.txt

• robots.txt controls crawl permission for traditional bots. It does not explain your product.
• llms.txt guides how AI systems should summarise and cite your site.
• [ai.txt](/ai.txt) (and our guide What is ai.txt?) focuses on AI crawler expectations and citation preferences in a shorter policy style.

Many sites will eventually ship more than one of these. They should not contradict each other. If robots blocks a path, do not list that path as a preferred citation in llms.txt.

How this ties to answer engine optimization

Answer engine optimization (AEO) is the broader practice of making pages easy for AI systems to quote correctly. llms.txt is one technical signal; clear H1s, FAQ structure, and accurate product pages matter more. Read What is answer engine optimization? for the full picture.

Checking and maintaining the file

1. 1Confirm /llms.txt returns 200 and text/plain from the public hostname visitors use.
2. 2Open the file and verify every link resolves without redirects to dead pages.
3. 3Re-read claims against features and pricing after each major release.
4. 4Keep a short changelog note in your deploy process so the file is not forgotten.

A security and monitoring product still needs accurate technical docs for humans. Pair llms.txt with a maintained knowledge base and, when you care about live posture, a security scan. Machine-readable guidance only helps when the human pages behind the links stay true.