> For the complete documentation index, see [llms.txt](https://cc.docs.landis.cloud/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cc.docs.landis.cloud/feature-highlights/agent-details-report.md).

# Agent Details Report

The agent details report shows each agent's interactions history. Simply put, it's all the interactions an agent has interacted with in some way.

By default, your report only shows interactions that the agent answered. This setup highlights direct interactions with contacts and gives you an idea of how often and well the agent handles them. But if you want a complete picture, including missed or rejected interactions, follow these easy steps.

<figure><img src="https://1039569329-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2F-Lm5wszNs6c24n4NZ30U%2Fuploads%2F40qb9K8WzTyRvDCFyL8x%2FAgent%20Details%20Resized.gif?alt=media&amp;token=5f654744-5fe5-4c30-8d7a-7484cba3f55d" alt="" width="375"><figcaption></figcaption></figure>

#### Steps to Include More Interaction Types:

1. **Head to the Filters:** Click the filter button to explore different customization options.
2. **Turn on "Include Missed Interactions":** Just toggle that switch to include any interactions that didn’t get answered.
3. **Turn on "Include Rejected Interactions":** Flick this switch, too, to factor in interactions that got bounced.

Once you do this, your report will go beyond just answered interactions. You'll get a full view that shows all interactions, including those that were missed or rejected—ideal for a deeper dive into how interactions are being handled.


---

# 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://cc.docs.landis.cloud/feature-highlights/agent-details-report.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.