Is it llm.txt or llms.txt?

llms.txt — plural, because it addresses LLMs (large language models) collectively. llm.txt is a common misspelling; the spec, and every implementation that reads the file, expects /llms.txt at your site root.

What is llms.txt in simple terms?

llms.txt is a plain Markdown file placed at yoursite.com/llms.txt that gives AI assistants a curated summary of your site: what it is, and links to your most important pages. Think of it as a sitemap written for language models instead of search engine crawlers.

Is llms.txt an official standard?

No — it's a community proposal introduced by Jeremy Howard in September 2024. No AI company has formally committed to using it, but adoption among sites is growing and it costs almost nothing to add.

Where does the llms.txt file go?

At the root of your domain: https://yoursite.com/llms.txt. It must be served as plain text (Markdown), not HTML.

Does llms.txt replace robots.txt or sitemap.xml?

No. robots.txt controls which crawlers may access your site, sitemap.xml lists URLs for search indexing, and llms.txt curates and describes your key content for AI consumption. They complement each other.

What is llms.txt? — GeoPromptTracker

llms.txt is a Markdown file, served at the root of a website (/llms.txt), that gives AI language models a concise, structured summary of a site's purpose and most important pages — designed to be read directly by a model instead of crawled and parsed from HTML.

Where the spec came from

The llms.txt proposal was published in 2024 by Jeremy Howard (co-founder of Answer.AI and fast.ai). The core problem it addresses: HTML pages are built for browsers and human visual scanning — navigation bars, ads, cookie banners, JavaScript-rendered widgets — none of which is useful to a language model trying to quickly understand what a site is and where its key content lives. Large documentation sites are especially painful for a model's limited context window to crawl page by page.

llms.txt solves this with a plain-text, link-based table of contents a model can read in one pass. Adoption has grown quickly among developer-tool companies: Anthropic, Vercel, Cloudflare, Stripe, and others publish their own.

The format

An llms.txt file follows a specific Markdown structure:

# Site Name

> A one-sentence summary of what this site/product is.

Optional additional context paragraph — anything a model should
know before reading further.

## Section Name

- [Link title](https://example.com/page): optional short description
- [Another link](https://example.com/other-page)

## Another Section

- [Docs](https://example.com/docs): the full documentation

The required elements:

Element	Rule
H1	Exactly one, the site or project name
Blockquote	A single-sentence summary, directly after the H1
H2 sections	One or more, grouping related links
Links	Markdown format `- [title](url): description`

A real-world example

Here's a trimmed example in the style used by developer-tool companies:

# Acme API

> Acme is a REST API for sending transactional email.

## Documentation

- [Quickstart](https://acme.dev/docs/quickstart): get your first email sent in 5 minutes
- [API Reference](https://acme.dev/docs/reference): full endpoint documentation
- [Webhooks](https://acme.dev/docs/webhooks): event notification setup

## Guides

- [Deliverability best practices](https://acme.dev/guides/deliverability)
- [Migrating from SendGrid](https://acme.dev/guides/migrate-sendgrid)

Notice what's absent: no marketing copy, no pricing page, no blog archive. A good llms.txt is curated, not exhaustive — it should read like a table of contents a busy expert would hand a new colleague, not a full sitemap dump.

How to create one

Write your one-sentence summary first. This is the single most important line in the file — it's what a model reads before anything else. Be concrete: "Acme is a REST API for sending transactional email" beats "Acme helps businesses communicate better."
Pick 2-5 sections that group your most important pages — commonly Documentation, Guides, API Reference, or Product/Pricing for a marketing site.
List only pages worth an AI assistant knowing about. Skip legal boilerplate, individual blog posts (link to a blog index instead, if at all), and anything duplicated elsewhere.
Add a one-line description to each link when the title alone isn't self-explanatory.
Publish it at your domain root: https://yoursite.com/llms.txt, served as plain text, the same way robots.txt is.

Our llms.txt Generator builds this structure for you from a simple form, and can prefill link sections from your sitemap.xml.

Checking your work

Once published, run your file through our llms.txt Validator — it fetches the live file and checks the structural rules above (H1, blockquote position, H2 sections, link format) automatically.

Does it actually help?

Adoption among AI platforms reading llms.txt at query time is still uneven and evolving — it isn't yet a universal standard the way robots.txt is. But the cost of publishing one is close to zero: a single static file, no infrastructure changes, no downside. As more AI browsing tools and agent frameworks add llms.txt support, sites that already have a well-structured file are positioned to benefit immediately rather than scrambling to catch up.

What is llms.txt? Spec, examples, and how to create one