> For the complete documentation index, see [llms.txt](https://docs.aicrisk.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aicrisk.com/admin/agent-scanner-defaults/topic-scanner.md).

# Topic Scanner

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<figure><img src="/files/mhDSfvUne0e4MULUrtFI" alt=""><figcaption></figcaption></figure>

**Purpose:** The Topic Scanner is designed to analyze text inputs and identify the main topics or themes discussed within the content.

**Functionality:** It employs topic modeling techniques to extract key topics from text data based on the distribution of words and their relationships.

**Implementation:** The scanner processes text inputs using probabilistic algorithms to identify clusters of words that frequently co-occur and represent coherent topics. It may also incorporate natural language understanding (NLU) techniques to infer the meaning and context of the text.

**Usage:** The Topic Scanner is utilized to understand and categorize textual content automatically.


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# 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 dynamically by asking a question.

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

```
GET https://docs.aicrisk.com/admin/agent-scanner-defaults/topic-scanner.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.