# What is knowledge modelling?

Knowledge modelling in Rainbird is about representing your domain of expertise, including how you make decisions, solve problems and apply your knowledge in a way that can be interpreted by our engine to reason, make decisions, and solve problems in a manner similar to yourself.

Using the Rainbird Studio, you can build models of your knowledge as a Knowledge Map (KM), without having to write any code.

The goal of building a Knowledge Map is to be able to **query** it (i.e. ask it a question) and for the reasoning engine to use the logic and data encoded within it to be able to provide you with a **query result**.

The guides in this section will help you understand the features of the Rainbird Studio necessary to build the structure and logic of a knowledge map and test it by making queries to it.

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More detailed training is available in the [Rainbird Academy](https://academy.rainbird.ai/), which provides practical examples of how you can use these features.
{% endhint %}


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# 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://docs.rainbird.ai/rainbird/knowledge-modelling/overview.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.