What is llms.txt? The AI Website Standard Explained

AI is reading your website. ChatGPT, Claude, Perplexity, and dozens of other AI tools crawl web content to answer user questions. But here's the problem: most websites weren't built for AI consumption.

HTML pages are cluttered with navigation, ads, scripts, and styling that humans ignore but AI has to parse. Important content gets buried. Context gets lost. The AI sees everything except what actually matters.

llms.txt is a proposed solution. A simple markdown file that tells AI exactly what your site is about and where to find the good stuff.

This guide explains what llms.txt is, how it works, and whether you should add one to your website.

What is llms.txt?

llms.txt is a markdown file placed at the root of your website (like yoursite.com/llms.txt) that provides AI-friendly information about your content. Think of it as a welcome guide for AI visitors.

The standard was proposed in late 2024 by Jeremy Howard, co-founder of fast.ai. His reasoning was straightforward: AI models have limited context windows and struggle with complex HTML. A clean markdown summary helps them understand your site faster and more accurately.

Unlike robots.txt (which tells crawlers what not to access) or sitemap.xml (which lists all your pages), llms.txt curates your most important content specifically for AI consumption.

Here's the core idea: instead of forcing AI to parse your entire website, you provide a structured overview with links to detailed pages. The AI gets context quickly, then dives deeper where needed.

How llms.txt works

The llms.txt format follows a specific structure using markdown:

H1 heading: Your project or site name
Blockquote: A one-line summary of what you do
Paragraphs: Optional expanded context
H2 sections: Categorized lists of important pages with descriptions

Here's what our own llms.txt looks like:

# Onoma

> Onoma is an AI memory layer that gives you shared context
> across multiple AI models. Use GPT, Claude, Gemini, Grok,
> and more with one persistent memory.

Onoma solves AI context fragmentation. When you switch between
ChatGPT, Claude, and other AI assistants, you lose your
conversation history and context...

## Product

- [How Onoma Works](https://askonoma.com/how-it-works): Technical
  overview of the Cortex memory pipeline...
- [Features](https://askonoma.com/features): Spaces for automatic
  context organization...

## Get Started

- [Pricing](https://askonoma.com/pricing): Free tier with 50K tokens...
- [Download](https://askonoma.com/download): Native apps for macOS...

## Optional

- [Articles](https://askonoma.com/articles): Blog with guides...

The "Optional" section is a key feature. When an AI has limited context space, it can skip optional links and focus on the essentials. This gives you control over prioritization.

llms.txt vs llms-full.txt

Some sites also provide an llms-full.txt file. While llms.txt contains a curated overview with links, llms-full.txt compiles your entire site's content into one markdown document.

The full version is useful when someone wants to paste your complete documentation into an AI tool. Mintlify developed this approach in collaboration with Anthropic for Claude's documentation.

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

These three files serve different purposes:

robots.txt tells search engines and crawlers which pages they can or cannot access. It's about permission and exclusion.

sitemap.xml lists all your indexable pages for search engines to discover. It's about comprehensive page discovery.

llms.txt curates your most important content for AI understanding. It's about context and explanation.

They're complementary, not competitive. A website might have all three: robots.txt controlling access, sitemap.xml listing pages for traditional search, and llms.txt explaining content for AI tools.

The key difference is intent. Sitemaps say "here's everything." llms.txt says "here's what matters, and here's why."

Who's using llms.txt?

Several notable companies have implemented llms.txt:

Anthropic (Claude's creator) maintains an llms.txt file for their documentation. This is significant because it suggests the company behind one of the leading AI models sees value in the standard.

Cloudflare organizes their extensive documentation using llms.txt, with separate sections for different products like Workers, AI Gateway, and R2.

Vercel, Hugging Face, and Zapier have also adopted the format for their developer documentation.

The pattern is clear: companies with substantial technical documentation are early adopters. Their content is already structured and markdown-friendly, making implementation straightforward.

The honest truth: does llms.txt actually work?

Here's where we get real. llms.txt is a proposed standard, not an established one. No major AI provider has officially confirmed they use these files during crawling.

Semrush tested their own llms.txt implementation for three months and observed zero visits from AI crawlers (GPTBot, ClaudeBot, PerplexityBot) to the file. Their LLM traffic increased during that period, but they attributed it to other factors.

Google's John Mueller has described llms.txt as "unnecessary" according to Search Engine Journal's analysis.

Some skeptics raise valid concerns:

No official adoption: Major AI companies haven't committed to following llms.txt
Security risks: A separate file for AI could be manipulated to promote specific content
Redundancy: Well-structured HTML and existing standards might be sufficient

But there's another perspective. Companies like Anthropic wouldn't publish llms.txt files for their own documentation if they saw zero value. The standard may be ahead of official adoption.

Where llms.txt does provide value

Even without crawler support, llms.txt has practical uses:

Developer tools and IDE integrations: When you paste a URL into an AI coding assistant, some tools check for llms.txt to understand the project structure.

RAG pipelines: Teams building retrieval-augmented generation systems use llms.txt as an index for documentation.

Manual AI interactions: When asking Claude or ChatGPT about a website, you can point them to the llms.txt file directly for faster context.

The standard's value isn't purely about automated crawling. It's about making your content AI-accessible in any context.

How to create an llms.txt file

You have two options: manual creation or generator tools.

Manual creation

For most sites, manual creation takes 15-30 minutes:

Create a new file called llms.txt in your site's root directory
Add your site name as an H1 heading
Write a one-line summary as a blockquote
Optionally add a paragraph with more context
Create H2 sections for different content categories
Add 5-10 of your most important pages as markdown links with descriptions

Best practices:

Keep descriptions concise but informative
Use clear, jargon-free language
Put your most important content first
Use the "Optional" section for secondary content
Test by pasting the file into an AI and asking questions about your site

Generator tools

Several free tools can generate llms.txt from your existing content:

Firecrawl llms.txt Generator: Enter your URL and it crawls your site to generate both llms.txt and llms-full.txt files. Open source and free.

WordLift Generator: Extracts links from your header, navigation, and footer to build an llms.txt file.

llms-txt.io: Another free generator focused on GEO (Generative Engine Optimization).

WordPress plugins: Both Yoast SEO and Rank Math have added llms.txt generation features.

One caution: auto-generated files often need editing. They'll include pages you don't want prioritized and miss context that only you can provide. Use generators as a starting point, not a final product.

Should you implement llms.txt?

The honest answer: it depends on your situation.

Consider implementing if:

You have technical documentation that AI tools frequently reference
Your site already uses markdown or structured content
You can create the file in under an hour
You want to experiment with emerging standards
You're building for an AI-first audience (developers, researchers)

Maybe skip it if:

You need proven ROI before investing any time
Your site is primarily visual or e-commerce focused
You're already overwhelmed with SEO tasks
Your content changes so frequently that maintenance would be burdensome

The pragmatic approach

If you can create an llms.txt file quickly, do it. The downside is minimal (a few minutes of work), and the potential upside grows as AI tools evolve.

Don't expect immediate measurable results. Don't reorganize your SEO strategy around it. But having a clean, AI-readable summary of your site is unlikely to hurt and may help as the standard matures.

The bigger picture: AI understanding your content

llms.txt is part of a broader shift in how we think about web content. For two decades, we optimized for search engines. Now we're also optimizing for AI.

The same principles apply: clear structure, good descriptions, logical organization. But AI has different needs than traditional crawlers. It wants context, not just keywords. It benefits from explanation, not just links.

Whether or not llms.txt becomes an official standard, the underlying idea matters. Making your content accessible to AI means:

Clear, well-structured pages
Descriptions that explain purpose, not just topics
Logical organization that humans and AI can follow
Markdown or clean HTML that parses easily

These practices improve your site for everyone, not just AI crawlers.

Key takeaways

llms.txt is a simple markdown file that helps AI understand your website. Here's what to remember:

It's a proposed standard, not yet officially adopted by major AI providers
The format is straightforward: H1 title, blockquote summary, H2 sections with links
Major companies are experimenting: Anthropic, Cloudflare, and others have implemented it
Practical value exists even without crawler support, especially for developer documentation
Implementation is low-effort: 15-30 minutes for a manual file, or use free generators
The downside is minimal: If it doesn't help, you've lost little; if standards evolve, you're prepared

The question isn't whether AI will increasingly interact with web content. It will. The question is whether your content will be ready.

Start with clear, well-structured pages. Add an llms.txt if it makes sense for your site. And pay attention as the relationship between AI and web content continues to evolve.

Want to see a working example? Check out our llms.txt file for a real-world implementation.