LLMs.txt

Document360 automatically generates an llms.txt file for your knowledge base site — a Markdown-formatted text file that tells large language models (LLMs) like GPT, Claude, and Gemini what your content is about, helping AI agents accurately retrieve and cite your documentation when answering user questions.

What is llms.txt

llms.txt is an open standard that gives AI language models a structured way to understand what a website contains. It is a plain-text file written in Markdown, placed at the root of a site (for example, https://yoursite.com/llms.txt), and readable by both humans and machines.

The standard exists because LLMs struggle to navigate full websites the way search engines do. A sitemap lists every URL but provides no context. robots.txt tells crawlers what to skip but nothing about what remains. llms.txt fills the gap: it lists a site's key pages with titles, URLs, and short descriptions, giving AI models enough context to decide which pages to retrieve and how to represent the content in generated answers.

Why llms.txt matters for your knowledge base

Users increasingly turn to AI assistants — ChatGPT, Gemini, Copilot, and others — to find answers before visiting a website.

When to use llms.txt

• Your users use AI assistants to find answers, and you want those assistants to cite your documentation accurately rather than produce generic responses.
• You have written high-quality article descriptions and want them to contribute to AI discoverability, not just search engine snippets.
• You are preparing for a product launch and want to ensure your documentation is discoverable by AI tools from day one.

Before you begin

• To contribute to llms.txt, individual articles must have a meta description set in the AI & search descriptions (GEO/SEO) tab. Articles without a description are included in llms.txt by title only. To learn how to add a meta description, see Article SEO.
• llms.txt is only generated for public knowledge bases and public articles in mixed knowledge bases.

How llms.txt works

Document360 generates llms.txt automatically from your published articles and their GEO/SEO descriptions — you do not create or edit it manually. The file is updated whenever you publish, update, or remove articles.

The file has three parts:

• Header — the project name and a one-line tagline describing the knowledge base
• Workspace section heading — articles are grouped under the workspace name (for example, ## Document360 2.0)
• Article entries — each published article appears as a linked title followed by its meta description (if one is set)

Each article entry follows this format:

- [Article title](https://yourdomain.com/docs/article-slug.md): Meta description text.

Add a meta description for an article

To ensure an article appears in llms.txt with a description,

1. Open the article in the knowledge base portal.
2. Click the More (•••) icon in the article header and select SEO. The Article settings panel appears.
3. Select the AI & search descriptions (GEO/SEO) tab.
4. Enter a description in the Description field, or click Ask Eddy AI to generate one.
5. Click Save.

Best practices

• Write descriptions as summaries, not teasers. AI crawlers use the description to decide whether to retrieve the full article. A description like "Covers how to configure SSO using SAML 2.0 in Document360" is more useful to an LLM than "Learn about SSO in Document360."
• Prioritize high-traffic and cornerstone articles. Use Content tools > SEO description to filter articles without descriptions and address the most important ones first.
• Keep descriptions between 150 and 160 characters. This length works for both search engine snippets and llms.txt entries.
• Review AI-generated descriptions before saving. Eddy AI generates descriptions based on article content. Verify they accurately represent the article's scope and terminology before saving.
• Write descriptions that work for both SEO and GEO. The same description appears in search engine results and llms.txt — so a well-written description improves both your search ranking snippets and AI crawler context simultaneously.
• Check your documentation's AI readiness. Use Document360's Agent Score for Documentation to evaluate how well your knowledge base is optimized for AI agents.

FAQ