> For the complete documentation index, see [llms.txt](https://academy.any2info.com/any2info-academy/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://academy.any2info.com/any2info-academy/no-code-platform/ai-studio/agents/getting-started/markdown.md).

# Markdown

In Any2Info, Markdown is used to structure **AI instructions**, especially inside System Instructions for Agents.

Markdown helps you organize text clearly so the AI understands:

* Its role
* The task
* The required output format

You do not need advanced Markdown knowledge. We mainly use it to improve structure and clarity.

***

### Why We Use Markdown

AI models perform better when instructions are clearly structured.

Using Markdown helps you:

* Separate sections (Role, Task, Context, Output)
* Define strict output formats
* Reduce ambiguity
* Improve consistency in responses

***

### Best Practice

When writing AI instructions:

* Keep sections clearly separated
* Be explicit about requirements
* Define the expected output format
* Avoid long, unstructured paragraphs

***

For a complete Markdown reference, visit:

{% embed url="<https://www.markdownguide.org/getting-started/>" %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

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

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://academy.any2info.com/any2info-academy/no-code-platform/ai-studio/agents/getting-started/markdown.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.