Free llms.txt generator: create AI-optimized documentation files

Companies breaking through AI-driven discovery have implemented an llms.txt file. Vercel reports that 10% of new signups now come from ChatGPT, and teams like Anthropic, Supabase, and Windsurf see users finding their products through LLM-powered search.

An llms.txt file gives AI systems structured guidance on how to index and interact with your site, making this kind of discovery possible. Making your documentation discoverable to AI tools like ChatGPT, Claude, and Perplexity doesn’t need to soak up hours of manual work. By pasting your documentation URL into our free llms.txt generator, you’ll get a properly formatted starter file based on your structure in seconds—no signup required.

Get started with your llms.txt now

This guide walks through what the generator creates, why llms.txt matters for AI-driven growth, and three approaches to generating and maintaining your llms.txt file.

What this llms.txt generator creates

Our free llms.txt generator analyzes your documentation structure and creates a lightweight Markdown file optimized for LLM consumption.

The tool outputs AI-optimized documentation with your site title, a blockquote summary, organized content sections, and key page links with descriptions. This structure follows the llms.txt format specification while making it easy for you to customize based on your documentation specifications.

Example llms.txt

Think of it as a starting template. The generator handles the formatting and structure, giving you a foundation you can refine to match exactly how you want AI tools to understand and present your product.

Manual vs automatic llms.txt generation

Creating an llms.txt file manually gives you full control over the content and structure, which is useful for highly customized documentation. However, that process is time-consuming and error-prone, especially for large or frequently updated docs.

Our automatic llms.txt generator simplifies this process by analyzing your existing documentation and generating a compliant file in seconds. You get a correctly structured, AI-ready llms.txt file without worrying about formatting or missing metadata, while still having the flexibility to tweak it manually if needed.

Why llms.txt matters for AI discoverability

As AI-powered search becomes a common way for developers to find tools, having documentation that LLMs can read is critical. Vercel went from less than 1% to 10% of signups coming from ChatGPT in six months. That represents thousands of developers receiving accurate answers from an AI assistant based on Vercel’s documentation and converting to paid customers.

When Anthropic asked us at Mintlify to implement llms.txt for our documentation, it reinforced what we were seeing across our customer base: AI assistants are becoming a primary discovery channel for technical products. To test our hypothesis, we’ve tracked LLM crawler behavior and observed consistent traffic from ChatGPT, Claude, and Perplexity crawlers accessing llms.txt files multiple times per week.

This matters for your documentation because AI needs structured, accurate information to provide the right answer to users. Without llms.txt, the AI might pull from outdated Stack Overflow threads, competitor documentation, or even hallucinate an answer entirely.

An llms.txt file creates a direct line between your documentation and the AI tools your users rely on. It directs LLMs to read the right complex HTML files and marketing-heavy pages.

Three ways to generate llms.txt files

You’ve got a few solid options for creating and maintaining your llms.txt file, depending on your team’s size, resources, and how much hands-on control you want.

Use an llms.txt generator

Best for: Small documentation sites, teams getting started with llms.txt, or anyone who wants immediate results without writing code.

How it works: Use our free llms.txt generator tool to create your initial file. Paste in your docs URL, download the generated template, customize the sections and descriptions, and host it at your root domain.

Benefits:

• No technical setup required
• Get started quickly
• Full control over content and structure
• Works with any hosting platform

Tradeoffs: When you add new pages or restructure your docs, you'll need to update the llms.txt file manually. For documentation that changes frequently, this can become a maintenance burden.

Script-based automation (DIY approach)

Best for: Engineering teams comfortable with scripting, documentation sites with frequent updates, or teams wanting automated updates without committing to a platform.

How it works: If you're already running build scripts or CI/CD pipelines for your documentation, you can integrate llms.txt generation directly into that workflow. A build script reads your documentation structure and outputs a formatted file on each deploy.

Example script-based automation

This works well with static site generators like Docusaurus, Next.js, or VitePress, where you can hook into the build process.

Benefits:

• Automatically stays in sync with your docs
• Full control over generation logic
• No ongoing manual updates

Tradeoffs: Requires engineering effort to build and maintain. Generation logic must be updated as your docs evolve.

Platform-native automation

Best for: Teams who want zero-maintenance AI optimization, documentation platforms handling multiple products, or companies treating docs as a strategic growth channel.

How it works: By using Mintlify’s built-in llms.txt generator, every time you publish documentation changes, the platform regenerates your llms.txt file — along with llms-full.txt and markdown variants optimized for different AI use cases.

Benefits:

• No scripts or configuration to maintain
• Always stays in sync with live documentation
• Supports multiple AI-optimized formats out of the box

Tradeoffs:

• Requires using a documentation platform
• Less low-level control than a fully custom script, however Mintlify customers are able to override the generated llms.txt with manual updates If you're in high-growth mode and documentation is becoming a user discovery channel, this approach removes llms.txt from your maintenance burden entirely — freeing up engineering time to build products instead of maintaining doc infrastructure.

How to implement your llms.txt file

Once you've generated your file using any of the methods above, you need to make it accessible to AI tools. Here's the implementation process:

Step 1: Save your file as plain markdown Name it exactly llms.txt—no .md extension or alternate naming. The file should contain only Markdown-formatted text.

Step 2: Place it at your root domain Host the file at yourdomain.com/llms.txt, similar to how robots.txt and sitemap.xml work. AI tools expect to find it at this standard location.

Step 3: Ensure it serves as plain text The file should render as raw Markdown, not wrapped in HTML. If you're using a static site generator, configure your public folder or routes to expose the file directly.

Step 4: Handle subdomain documentation If your docs live at docs.yourdomain.com or yourdomain.com/docs, you can also host the file at that subpath (e.g., /docs/llms.txt).

Step 5: Verify accessibility Navigate to your llms.txt URL in a browser. You should see plain Markdown text, not a 404 or HTML-wrapped version.

Choosing your llms.txt approach

The right generation method depends on your documentation maintenance pattern and how aggressively you're pursuing AI-driven discovery.

Choose the manual llms.txt generator if you have a small documentation site that doesn't change frequently, or if you're just getting started with AI optimization and want the simplest path forward. You can create your llms.txt file quickly and start capturing AI search traffic almost immediately.

Choose script-based automation if you already have build pipelines in place, your documentation updates regularly, and your team has the engineering bandwidth to maintain generation scripts. This gives you control while eliminating manual updates.

Choose platform-native automation if you want AI optimization handled automatically, you're managing documentation at scale, or you'd rather invest engineering time in your product than documentation infrastructure. This is the zero-maintenance option.

Whether you're using our free llms.txt generator or automating with scripts, implementing llms.txt is one of the most effective ways to improve how AI tools surface and represent your product. The question isn't whether to do it, but how quickly you can get it live.

Already using Mintlify? Your llms.txt files are automatically generated and hosted.

Not using Mintlify yet? Learn more about maintaining documentation that stays AI-optimized by default.

Looking beyond llms.txt? Model Context Protocol (MCP) servers represent the next evolution of AI-native documentation, enabling even deeper integration with AI assistants.