> For the complete documentation index, see [llms.txt](https://docs.umbraco.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.umbraco.com/umbraco-engage-ai/using-umbraco-engage-ai/asking-engage-questions.md).

# Asking Engage Questions

Umbraco Engage AI's tools answer the same way whether you ask from the Copilot sidebar or from Copilot Workspace. Pick whichever surface fits how you work.

The following prompts ran against a demo Engage installation, using an agent with Instructions similar to the [Installation](/umbraco-engage-ai/getting-started/installation.md) example, with the Engage Read permission granted. Answers come from live data each time you ask, so your own numbers will differ from these examples.

* **"What campaigns do we have set up?"** Lists configured campaigns.
* **"Which campaign is giving us the best return right now?"** Campaign performance.
* **"Which channels should I double down on?"** Top traffic sources.
* **"Who are our visitor personas?"** Persona discovery.
* **"Why would a visitor end up classified as a 'Window Shoppers'?"** Explains how a persona is scored.
* **"Should I end any of my running tests yet, or keep waiting for more data?"** A/B test status. On a site with no test configured, this comes back with what to consider before launching one, rather than reporting who's winning.


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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.umbraco.com/umbraco-engage-ai/using-umbraco-engage-ai/asking-engage-questions.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.