llms.txt: A New Way for AI to Read Your Site

Large language models (LLMs) like ChatGPT and Claude face a fundamental problem when crawling websites: their context windows are too small to process entire sites, and converting complex HTML pages filled with navigation, ads, and JavaScript into AI-friendly text is both difficult and imprecise. The llms.txt AI crawler standard offers a solution—a simple text file that tells AI systems exactly what content matters most on your site.

What Is llms.txt?

The llms.txt file is a proposed standard designed to help AI systems understand and use website content more effectively. Similar to how robots.txt guides search engine crawlers and sitemap.xml lists available URLs, llms.txt provides AI with a curated, structured map of your most important content.

Located at your root domain (https://yourdomain.com/llms.txt), this Markdown-formatted file gives AI crawlers a clear path to your high-value content without the noise of navigation elements, advertisements, or JavaScript-rendered components that often confuse automated systems.

The Problem llms.txt Solves

Modern websites present two major challenges for AI crawlers:

1. Technical complexity: Most AI crawlers can only read basic HTML, missing content loaded by JavaScript
2. Information overload: Without guidance, AI systems waste computational resources processing irrelevant pages like outdated blog posts or administrative sections

The llms.txt AI crawler standard addresses both issues by providing a clean, structured format that helps AI systems quickly identify and process your most valuable content.

How llms.txt Differs from robots.txt and sitemap.xml

While these files might seem similar, each serves a distinct purpose:

robots.txt: The Gatekeeper

• Purpose: Tells crawlers where NOT to go
• Format: Simple text with User-agent and Disallow directives
• Example: Disallow: /admin/

sitemap.xml: The Navigator

• Purpose: Lists all URLs available for indexing
• Format: XML with URL entries and metadata
• Example: <url><loc>https://example.com/page</loc></url>

llms.txt: The AI Guide

• Purpose: Shows AI what content matters and how it’s structured
• Format: Markdown with semantic organization
• Focus: Content meaning and hierarchy for AI comprehension

File Structure and Implementation

The llms.txt file uses standard Markdown formatting. Here’s a compact example:

# Company Name
> Brief description of what your company does

## Products
- [Product API](https://example.com/api): RESTful API documentation
- [SDK Guide](https://example.com/sdk): JavaScript SDK implementation

## Documentation
- [Getting Started](https://example.com/docs/start): Quick setup guide
- [Authentication](https://example.com/docs/auth): OAuth 2.0 flow

## Resources
- [Changelog](https://example.com/changelog): Latest updates
- [Status](https://example.com/status): Service availability

Optional llms-full.txt

For comprehensive sites, you can create an additional llms-full.txt file containing more detailed information. The main llms.txt file serves as a concise overview, while llms-full.txt provides extensive documentation, code examples, and deeper technical details.

Current Adoption and Real-World Examples

Several developer-focused companies have already implemented the llms.txt AI crawler standard:

• Mintlify: Developer documentation platform
• FastHTML: Modern web framework
• Anthropic: AI safety company (creators of Claude)
• Vercel: Frontend cloud platform
• Cloudflare: Web infrastructure and security

According to recent data, approximately 950 domains have published llms.txt files—a small but growing number that includes many influential tech companies.

Benefits and Limitations

Potential Benefits

• Improved AI comprehension: Clean, structured content helps AI understand your site better
• Computational efficiency: Reduces resources needed for AI to process your content
• Content control: You decide what AI systems should prioritize
• Future positioning: Early adoption may provide advantages as the standard evolves

Current Limitations

The biggest limitation? No major AI provider officially supports llms.txt yet. OpenAI, Google, and Anthropic haven’t confirmed their crawlers use these files. As Google’s John Mueller noted: “AFAIK none of the AI services have said they’re using llms.txt.”

This makes llms.txt largely speculative at present—though Anthropic publishing their own llms.txt file suggests they’re at least considering the standard.

When to Experiment with llms.txt

Despite current limitations, implementing llms.txt might make sense if you:

• Run a developer-focused site with extensive documentation
• Want to experiment with emerging web standards
• Have structured content that’s already well-organized
• Believe in positioning for potential future AI crawler adoption

The implementation cost is minimal—it’s just a Markdown file hosted on your server. There’s no downside beyond the time spent creating it.

Quick Implementation Steps

1. Create a new file named llms.txt
2. Structure your content using Markdown headers and lists
3. Upload to your root directory
4. Optionally create llms-full.txt for comprehensive documentation
5. Keep both files updated as your content changes

Conclusion

The llms.txt AI crawler standard represents an interesting attempt to solve real problems with AI web crawling. While major AI providers haven’t officially adopted it yet, the minimal implementation effort and potential future benefits make it worth considering for technical sites. As AI continues to reshape how people find and consume information, standards like llms.txt may become essential for maintaining visibility in AI-generated responses.

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