# Hyperflow LLMS

* Support LLMS with llms.txt and markdown generation
* Automate update of all pages and CMS content on the site
* LLMS.TXT
  * Allow customization;
    * Auto-generated page within Webflow, using collection lists, H1's etc.  
      * e.g. `/data/llms` 
    * Static exact page source ( uploaded .txt?  HTML Embed? ) 
    * Other 
* Page MD. Generate a markdown extract of every page 
  * Fully automatic
  * Accessible at e.g. `/about.md` or e.g. `/index.md` for default pages. 

## Use cases

* Improve "AI SEO" by presenting your data in a readily consumable format 
* For content-heavy public sites, improve utility of your site content by allowing users to share the `llms.txt` URL directly to an MCP server or LLM and query it. 
  * LLMS-FULL.TXT is best here, but has some challenges in the page build. 
* AI chatbots. One of the more complex challenges with AI chatbots is extracting your data and keeping it current.  Hyperflow LLMS can create a full extract of your site, ready-made for chatbot LLMs to update their content with. 

Some of my sites are very content-oriented, and I'm seeing articles I've written referenced in chatgpt responses. It feels like this is at least one direction SEO is headed?

There are three specific use cases where LLMS.TXT could theoretically benefit me;

1\. SEO / LLMO / AIO, or whatever you want to call it- the improved absorption of specific website content and backlinks to it from LLMs. Whether it's video courses, tour products, tools & solutions, consulting services...

2\. Heavy docs. In some cases the sites exist to inform, and an LLM can improve that, if it can efficiently digest the site. Literally hand it the URL to the llms.txt file and ask questions.

3\. Internal support. Some companies have huge support repositories and services directories. The support / sales team might use LLMs to look up key information, and this makes their own website content very accessible. I think website-integrated AI chatbots will begin using it to keep current as the site content is updated. New prices, new products, special offers, company news...

<https://smithery.ai/server/@thedaviddias/mcp-llms-txt-explorer>

## Decisions

Automatically convert LLMS.TXT links to the .MD version?&#x20;

## Creating Your LLMS Page

`/data/llms`&#x20;

### Headings

### Lists&#x20;

Use collection lists

> Use multiple ranges Collection Lists if you have more than 100 items.&#x20;

Inside of the collection list, you can use a custom element of `<li>` to generate markdown lists.&#x20;

Links ar best.&#x20;

## Links

Hyperflow automatically;&#x20;

* Converts the content to Markdown&#x20;
* Delivers the content at `/llms.txt`  on your site &#x20;
* Generates the X-Robots response header

## Technical Notes

<https://llmstxt.org/>

<https://langchain-ai.github.io/langgraph/llms-txt-overview/>

## Advanced&#x20;

* Securing LLMS.TXT- does this ever make sense?
* Supporting LLMS-FULL.TXT&#x20;
* Instructions on how to use with a model&#x20;

<https://github.com/thedaviddias/llms-txt-hub>


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://hyperflow.sygnal.com/apps/hyperflow-llms.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.