What is LLMs-Full.txt?

The llms.txt proposal aims to guide LLMs toward high-value pages using a markdown file of curated links. Many teams go a step further by publishing a llms-full.txt file that contains the actual content of those pages, not just the links.

Want to understand the llms.txt standard first? Read our full explainer here →

The rationale behind LLMs-Full.txt

LLMs-Full.txt is an unofficial format for consolidating important web content, like API docs, onboarding guides, or support pages, into a single markdown file. It’s not part of the llms.txt standard. 

Dev-facing companies tend to add it to reduce friction for AI agents that can’t easily crawl or parse modern websites. It lives at /llms-full.txt and contains long-form content in this format:

# Page Title
Source:https://link_url

Markdown content of the page.

# Next Page Title
Source:https://link_url

Markdown content of the page.

Each section:

• Starts with an H1 (# Page Title)
• Includes a Source: line linking to the original URL
• Is followed by the full markdown version of the page’s content

Use cases

Modern websites aren’t built for language models. They use JavaScript-heavy frontends, distribute context across many pages, and include visual markup that doesn’t translate well to tokens.

LLMs-Full.txt tries to bypass that:

For dev tools, help centers, and technical platforms, it acts like a “pre-baked” context file—ready for ingestion.

Practical considerations

LLMs-Full.txt is most commonly used by:

• RAG pipelines: Easier to embed, chunk, and semantically search
• AI IDEs: Load full SDK docs into tools like Cursor or Claude Code
• Chatbots: Populate help centers or in-product assistants with long-form answers
• Custom GPTs: Serve as a backend for Q&A without hitting a live website

If you already write in markdown and control your CMS or docs stack, adding a llms-full.txt file is low lift.

Why it’s not a standard

Let’s be clear: this is not part of the llms.txt proposal. The llms.txt standard recommends two things:

1. Publishing a /llms.txt file with curated links
2. Hosting markdown versions of individual pages at yourdomain.com/page.md

It does not specify llms-full.txt. This is an emergent practice adopted by teams trying to simplify AI ingestion.

No major AI platform has confirmed support. OpenAI, Anthropic, Google, and Meta do not currently fetch or prioritize llms-full.txt in their crawlers.

Limitations to Consider

Despite its convenience, LLMs-Full.txt has real tradeoffs:

1. Token Limits

Most LLMs have strict context windows (e.g. 128K tokens for GPT-4-Turbo). If your file exceeds that, parts may be ignored or truncated.

2. Duplication Risk

Markdown versions can drift from their HTML counterparts. If the source content changes and the file isn’t regenerated, users (or models) may be working from outdated material.

3. SEO & UX Gaps

There’s no built-in way to link back to original styled pages. If a chatbot cites the llms-full.txt URL, users may land on a raw text file with no navigation or design.

How to Generate One

Several tools automate llms-full.txt creation:

• Mintlify – for sites already using their doc engine
• Firecrawl – crawls and compiles markdown versions
• dotenvx – CLI to output markdown files from local projects

Manual creation is also possible, but you’ll need to maintain:

• Clean and consistent markdown formatting
• A clear mapping to source URLs
• An update workflow to prevent content drift

Should You Use It?

LLMs-Full.txt is a workaround. A smart one, but a workaround nonetheless.

It’s worth experimenting with if:

• Your content is already written in markdown
• You serve developers, support teams, or AI tool users
• You’re exploring Generative Engine Optimization (GEO) and want tighter control over what models ingest

It’s not a requirement. And without adoption from LLM providers, there’s no guarantee it will be fetched, parsed, or prioritized.

Treat it like progressive enhancement: helpful when feasible, disposable when not.

At daydream, we help growth-minded teams future-proof their content for LLM-powered discovery. From structured indexing to token-aware formatting, we ensure your site is readable, retrievable, and relevant across AI-native platforms like ChatGPT, Gemini, and Perplexity.

Want to make your content part of the answer? Let’s chat.

References:

1. https://www.firecrawl.dev/blog/How-to-Create-an-llms-txt-File-for-Any-Website
2. https://github.com/AnswerDotAI/llms-txt
3. https://zeo.org/resources/blog/what-is-llms-txt-file-and-what-does-it-do
4. https://llmstxt.org/
5. https://github.com/thedaviddias/llms-txt-hub