Tiffany Chen
Marketing
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This guide explains how to create and host llms.txt files, including the proper format structure with title, blockquote summary, and organized sections, plus how to use Mintlify's free generator tool to create starter templates. It covers hosting requirements and emphasizes that Mintlify automatically generates llms.txt, llms-full.txt, and markdown versions for all documentation to make content AI-ready out of the box.
If you're trying to set up an llms.txt file, you're probably already familiar with the standard: a lightweight way to help AI tools better index your site's content.
But knowing what it is and knowing how to write and host the file are two different things.
In this guide, we'll walk through exactly how to create an llms.txt file, including what it should contain, how to create one with Mintlify's free llms.txt generator, and where to host it.
What is llms.txt?
llms.txt is a plain Markdown file, usually placed at the root of your website.
It gives LLMs a low-noise summary of your most important content and links without needing to parse complex HTML or bloated sitemaps.
There are a few different ways you can use it. Some teams add it to their marketing site to give answer engines a clear overview of their product and messaging.
But llms.txt is especially valuable for product documentation. If your users are turning to tools like ChatGPT, Perplexity, or Gemini to get help, llms.txt helps ensure the answers they see are accurate, contextual, and grounded in your actual docs.
If you're on Mintlify, we auto-generate llms.txt (and llms-full.txt) for you out of the box.
What is an example llms.txt file format?
The anatomy of an llms.txt file follows this structure:
- Title: Site or company name (required)
- > Blockquote: Short summary, e.g. description or key benefits
- ## Sections: Key content areas
- [Link](url): Description: List important pages under each section
- ## Optional: For helpful but lower-priority resources
Here's an example of how it looks:
# PulseMetrics
> PulseMetrics helps growth teams track user behavior and campaign performance in real time.
## Product
- [Features](https://pulsemetrics.io/features): What PulseMetrics can do
- [Use Cases](https://pulsemetrics.io/use-cases): How teams use PulseMetrics
## Resources
- [Pricing](https://pulsemetrics.io/pricing): Compare plan tiers
- [Blog](https://pulsemetrics.io/blog): Product updates and analytics tips
## Optional
- [Careers](https://pulsemetrics.io/careers): Open roles at PulseMetrics
How to generate an llms.txt file
The easiest way to get started is with our free llms.txt file generator.
Just paste in your docs site URL, and we'll generate a starter file based on your structure.
With that template, you can make adjustments such as:
- Customize the section names to reflect your actual product experience
- Add brief, human-readable descriptions to help models interpret the page's purpose
- Reducing URLs - you don't need to include every URL, just the most useful and representative ones
You can treat the generated file as a starting template, then fine-tune it to match how you want your product understood by AI.
Manual vs automatic generation
| Manual | Automatic (Mintlify) | |
|---|---|---|
| Setup effort | Write and maintain the file yourself | Generated from your docs on every deploy |
| Stays in sync | Requires manual updates when content changes | Always reflects your latest published docs |
| Content control | Full control over ordering, descriptions, and structure | Generated structure follows your docs navigation |
| Includes llms-full.txt | You'd need to build a script to concatenate pages | Auto-generated alongside llms.txt |
| Markdown versions (.md) | Requires custom build step | Every page gets a .md version automatically |
| Best for | Sites where you want precise control over what AI sees | Documentation that changes frequently across many pages |
Manual generation gives you full control and works well for marketing sites or docs with stable content. Automatic generation makes more sense when your documentation changes frequently and you don't want the llms.txt file falling out of sync.
How to host your llms.txt file
Once you have the file, you need to host it so that it's discoverable by LLMs.
Place the raw Markdown file in the root directory of your site, such as example.com/llms.txt. Just like robots.txt or sitemap.xml, this file should be accessible via a direct URL.
Some tips:
- Ensure it serves as plain text or Markdown, not wrapped in HTML
- If you're using a static site generator, configure a public folder or route to expose the file
- If your docs live under a subpath (e.g., example.com/docs), you can also serve it at /docs/llms.txt
How to validate your llms.txt file
After creating your file, verify it works correctly:
- Check accessibility: Visit
yoursite.com/llms.txtin a browser. You should see raw Markdown, not an HTML page. - Verify the format: The file must start with a
#title. A blockquote summary is recommended but optional. - Test all links: Every URL in your llms.txt should return a 200 status. Broken links mean the AI gets incomplete context about your product.
- Check file size: Keep llms.txt concise. As a rough guideline, aim for under 50KB. Use llms-full.txt for comprehensive content.
Common mistakes to avoid:
- Wrapping the file in HTML instead of serving raw Markdown
- Including every URL on your site instead of curating the most important ones
- Forgetting to update llms.txt when you add or remove documentation pages
- Using relative URLs instead of absolute URLs
- Missing the required H1 title at the top of the file
Get started even faster
llms.txt is becoming the new standard for making web content accessible to AI. It's simple to adopt, but powerful in impact, especially for developer tools and product-led companies.
With Mintlify, you don't even have to think about it. We automatically generate and host /llms.txt, /llms-full.txt, and .md versions of all your pages for LLM optimization.
If you want to skip the manual setup, you can get started with Mintlify today and make your documentation LLM-ready by default.
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