# Source: https://llmstxt.org/index.md

# The /llms.txt file
Jeremy Howard
2024-09-03

## Background

Large language models increasingly rely on website information, but face
a critical limitation: context windows are too small to handle most
websites in their entirety. Converting complex HTML pages with
navigation, ads, and JavaScript into LLM-friendly plain text is both
difficult and imprecise.

While websites serve both human readers and LLMs, the latter benefit
from more concise, expert-level information gathered in a single,
accessible location. This is particularly important for use cases like
development environments, where LLMs need quick access to programming
documentation and APIs.

## Proposal

<figure>
<img src="logo.png" class="lightbox floatr" width="150"
alt="llms.txt logo" />
<figcaption aria-hidden="true">llms.txt logo</figcaption>
</figure>

We propose adding a `/llms.txt` markdown file to websites to provide
LLM-friendly content. This file offers brief background information,
guidance, and links to detailed markdown files.

llms.txt markdown is human and LLM readable, but is also in a precise
format allowing fixed processing methods (i.e. classical programming
techniques such as parsers and regex).

We furthermore propose that pages on websites that have information that
might be useful for LLMs to read provide a clean markdown version of
those pages at the same URL as the original page, but with `.md`
appended. (URLs without file names should append `index.html.md`
instead.)

The [FastHTML project](https://fastht.ml) follows these two proposals
for its documentation. For instance, here is the [FastHTML docs
llms.txt](https://www.fastht.ml/docs/llms.txt). And here is an example
of a [regular HTML docs
page](https://www.fastht.ml/docs/tutorials/by_example.html), along with
exact same URL but with [a .md
extension](https://www.fastht.ml/docs/tutorials/by_example.html.md).

This proposal does not include any particular recommendation for how to
process the llms.txt file, since it will depend on the application. For
example, the FastHTML project opted to automatically expand the llms.txt
to two markdown files with the contents of the linked URLs, using an
XML-based structure suitable for use in LLMs such as Claude. The two
files are: [llms-ctx.txt](https://fastht.ml/docs/llms-ctx.txt), which
does not include the optional URLs, and
[llms-ctx-full.txt](https://fastht.ml/docs/llms-ctx-full.txt), which
does include them. They are created using the
[`llms_txt2ctx`](https://llmstxt.org/intro.html#cli) command line
application, and the FastHTML documentation includes information for
users about how to use them.

The versatility of llms.txt files means they can serve many purposes -
from helping developers find their way around software documentation, to
giving businesses a way to outline their structure, or even breaking
down complex legislation for stakeholders. They’re just as useful for
personal websites where they can help answer questions about someone’s
CV, for e-commerce sites to explain products and policies, or for
schools and universities to provide quick access to their course
information and resources.

Note that all [nbdev](https://nbdev.fast.ai/) projects now create .md
versions of all pages by default. All Answer.AI and fast.ai software
projects using nbdev have had their docs regenerated with this feature.
For an example, see the [markdown
version](https://fastcore.fast.ai/docments.html.md) of [fastcore’s
docments module](https://fastcore.fast.ai/docments.html).

## Format

At the moment the most widely and easily understood format for language
models is Markdown. Simply showing where key Markdown files can be found
is a great first step. Providing some basic structure helps a language
model to find where the information it needs can come from.

The `llms.txt` file is unusual in that it uses Markdown to structure the
information rather than a classic structured format such as XML. The
reason for this is that we expect many of these files to be read by
language models and agents. Having said that, the information in
llms.txt follows a specific format and can be read using standard
programmatic-based tools.

The llms.txt file spec is for files located in the root path `/llms.txt`
of a website (or, optionally, in a subpath). A file following the spec
contains the following sections as markdown, in the specific order:

- An H1 with the name of the project or site. This is the only required
  section
- A blockquote with a short summary of the project, containing key
  information necessary for understanding the rest of the file
- Zero or more markdown sections (e.g. paragraphs, lists, etc) of any
  type except headings, containing more detailed information about the
  project and how to interpret the provided files
- Zero or more markdown sections delimited by H2 headers, containing
  “file lists” of URLs where further detail is available
  - Each “file list” is a markdown list, containing a required markdown
    hyperlink `[name](url)`, then optionally a `:` and notes about the
    file.

Here is a mock example:

``` markdown
# Title

> Optional description goes here

Optional details go here

## Section name

- [Link title](https://link_url): Optional link details

## Optional

- [Link title](https://link_url)
```

Note that the “Optional” section has a special meaning—if it’s included,
the URLs provided there can be skipped if a shorter context is needed.
Use it for secondary information which can often be skipped.

## Existing standards

llms.txt is designed to coexist with current web standards. While
sitemaps list all pages for search engines, `llms.txt` offers a curated
overview for LLMs. It can complement robots.txt by providing context for
allowed content. The file can also reference structured data markup used
on the site, helping LLMs understand how to interpret this information
in context.

The approach of standardising on a path for the file follows the
approach of `/robots.txt` and `/sitemap.xml`. robots.txt and `llms.txt`
have different purposes—robots.txt is generally used to let automated
tools know what access to a site is considered acceptable, such as for
search indexing bots. On the other hand, `llms.txt` information will
often be used on demand when a user explicitly requests information
about a topic, such as when including a coding library’s documentation
in a project, or when asking a chat bot with search functionality for
information. Our expectation is that `llms.txt` will mainly be useful
for *inference*, i.e. at the time a user is seeking assistance, as
opposed to for *training*. However, perhaps if `llms.txt` usage becomes
widespread, future training runs could take advantage of the information
in `llms.txt` files too.

sitemap.xml is a list of all the indexable human-readable information
available on a site. This isn’t a substitute for `llms.txt` since it:

- Often won’t have the LLM-readable versions of pages listed
- Doesn’t include URLs to external sites, even though they might be
  helpful to understand the information
- Will generally cover documents that in aggregate will be too large to
  fit in an LLM context window, and will include a lot of information
  that isn’t necessary to understand the site.

## Example

Here’s an example of `llms.txt`, in this case a cut down version of the
file used for the FastHTML project (see also the [full
version](https://www.fastht.ml/docs/llms.txt)):

``` markdown
# FastHTML

> FastHTML is a python library which brings together Starlette, Uvicorn, HTMX, and fastcore's `FT` "FastTags" into a library for creating server-rendered hypermedia applications.

Important notes:

- Although parts of its API are inspired by FastAPI, it is *not* compatible with FastAPI syntax and is not targeted at creating API services
- FastHTML is compatible with JS-native web components and any vanilla JS library, but not with React, Vue, or Svelte.

## Docs

- [FastHTML quick start](https://fastht.ml/docs/tutorials/quickstart_for_web_devs.html.md): A brief overview of many FastHTML features
- [HTMX reference](https://github.com/bigskysoftware/htmx/blob/master/www/content/reference.md): Brief description of all HTMX attributes, CSS classes, headers, events, extensions, js lib methods, and config options

## Examples

- [Todo list application](https://github.com/AnswerDotAI/fasthtml/blob/main/examples/adv_app.py): Detailed walk-thru of a complete CRUD app in FastHTML showing idiomatic use of FastHTML and HTMX patterns.

## Optional

- [Starlette full documentation](https://gist.githubusercontent.com/jph00/809e4a4808d4510be0e3dc9565e9cbd3/raw/9b717589ca44cedc8aaf00b2b8cacef922964c0f/starlette-sml.md): A subset of the Starlette documentation useful for FastHTML development. 
```

To create effective `llms.txt` files, consider these guidelines:

- Use concise, clear language.
- When linking to resources, include brief, informative descriptions.
- Avoid ambiguous terms or unexplained jargon.
- Run a tool that expands your `llms.txt` file into an LLM context file
  and test a number of language models to see if they can answer
  questions about your content.

## Directories

Here are a few directories that list the `llms.txt` files available on
the web:

- [llmstxt.site](https://llmstxt.site/)
- [directory.llmstxt.cloud](https://directory.llmstxt.cloud/)

## Integrations

Various tools and plugins are available to help integrate the llms.txt
specification into your workflow:

- [`llms_txt2ctx`](https://llmstxt.org/intro.html#cli) - CLI and Python
  module for parsing llms.txt files and generating LLM context
- [JavaScript Implementation](./llmstxt-js.html) - Sample JavaScript
  implementation
- [`vitepress-plugin-llms`](https://github.com/okineadev/vitepress-plugin-llms) -
  VitePress plugin that automatically generates LLM-friendly
  documentation for the website following the llms.txt specification
- [`docusaurus-plugin-llms`](https://github.com/rachfop/docusaurus-plugin-llms) -
  Docusaurus plugin for generating LLM-friendly documentation following
  the llmtxt.org standard
- [Drupal LLM Support](https://www.drupal.org/project/llm_support) - A
  Drupal Recipe providing full support for the llms.txt proposal on any
  Drupal 10.3+ site
- [`llms-txt-php`](https://github.com/raphaelstolt/llms-txt-php) - A
  library for writing and reading llms.txt Markdown files
- [`VS Code PagePilot Extension`](https://dmux.github.io/pagepilot) -
  PagePilot is a VS Code Chat participant that automatically loads
  external context (documentation, APIs, README files) to provide
  enhanced responses.

## Next steps

The `llms.txt` specification is open for community input. A [GitHub
repository](https://github.com/AnswerDotAI/llms-txt) hosts [this
informal
overview](https://github.com/AnswerDotAI/llms-txt/blob/main/nbs/index.qmd),
allowing for version control and public discussion. A [community discord
channel](https://discord.gg/aJPygMvPEN) is available for sharing
implementation experiences and discussing best practices.