What is llms.txt and Why Your Website Might Need One

So you've probably heard about llms.txt if you've been following the AI space lately. Think of it like robots.txt but for LLMs

The Problem It Solves

LLMs have this fundamental issue: context windows. They can only process so much text at once. When an AI tries to understand your website it runs into a few problems:

• HTML is messy - nav, ads, scripts, and actual content all mixed together
• websites are huge - most sites have hundreds of pages
• structure is all over the place - every site does things differently

Converting a complex website into something an LLM can actually use is hard. That's where llms.txt comes in

What is llms.txt?

Jeremy Howard (co-founder of Answer.AI) proposed this back in September 2024. It's basically a markdown file at your website root that gives:

• a quick overview of your site
• what each section is about
• links to the important stuff with descriptions
• context that helps AI understand what you're offering

It's a curated index built specifically for machines

The Format

It's just plain markdown. Here's the basic structure:

# Site Name

> Brief tagline or description

## About
A paragraph explaining what this site is and who it's for.

## Site Structure
- Homepage: / - What visitors find here
- Documentation: /docs - Technical guides and API references
- Blog: /blog - Articles and updates

## Key Pages
- [Getting Started](/docs/getting-started) - First steps for new users
- [API Reference](/docs/api) - Complete API documentation

## Contact
- Email: hello@example.com
- GitHub: github.com/example

Real-World Example

Here's what I use for this site:

# Jo Vinkenroye - Web Application Developer

> Building ERP systems, SaaS platforms, and modern web applications

## About
Senior developer with 13+ years of experience specializing in
React, Next.js, blockchain development, and AI integration.

## Site Structure
- Homepage: / - Overview of skills, experience, and projects
- Experience: /experience - Detailed work history
- Blog: /blog - Technical articles and project write-ups

## Blog Posts
- Building a Tamagotchi on Garmin: /blog/garmigotchi
- Ad-Forge - AI-Powered Ad Generation: /blog/ad-forge

Should You Add One?

Ok here's the honest truth: no major AI company has officially said they use llms.txt when crawling. It's a proposed standard, not an adopted one

But adoption is growing. Anthropic, Cloudflare, Vercel, Cursor - they've all implemented it. Mintlify rolled it out across all their hosted docs in late 2024

Add one if:

• you have docs or technical content
• you want to be early on something potentially important
• you're building for AI-native discovery
• it takes 10 minutes and costs nothing

Skip it if:

• your site is mostly visual content
• you're waiting for official adoption

Implementation in Next.js

If you're on Next.js with the App Router you can create a dynamic route:

// app/llms.txt/route.ts
Export async function GET() {
  const content = `# Your Site Name

> Your tagline here

## About
Your description...

## Key Pages
- Homepage: / - Main landing page
- Blog: /blog - Articles and guides
`;

  return new Response(content, {
    headers: {
      'Content-Type': 'text/plain; charset=utf-8',
    },
  });
}

For dynamic content like blog posts you can generate it programmatically:

// app/llms.txt/route.ts
Import { getAllPosts } from '@/lib/blog';

Export async function GET() {
  const posts = getAllPosts();

  const blogSection = posts
    .map(post => `- ${post.title}: /blog/${post.slug}`)
    .join('\n');

  const content = `# My Site

## Blog Posts
${blogSection}
`;

  return new Response(content, {
    headers: { 'Content-Type': 'text/plain; charset=utf-8' },
  });
}

Tools and Resources

A few tools can help you set this up:

• llms_txt2ctx - CLI for parsing and generating context
• vitepress-plugin-llms - VitePress integration
• docusaurus-plugin-llms - Docusaurus integration
• GitBook - auto-generates for all hosted docs

The Bigger Picture

Whether or not llms.txt becomes a universal standard, the problem it solves isn't going away. AI models will keep needing structured access to web content

By implementing it now you're:

1. Making your content more accessible to current AI tools
2. Prepping for potential future adoption
3. Thinking about content from an AI-first perspective

That last one might be the most valuable. As AI becomes a primary way people discover content, machine readability becomes just as important as human readability

Conclusion

llms.txt is simple and low-effort but could pay off as AI-native discovery grows. Takes minutes to implement and signals your site is ready for the AI-first web

Check out the official spec for more details, or look at how Anthropic and Vercel have done theirs