> For the complete documentation index, see [llms.txt](https://docs.amesa.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.amesa.com/train-agents/analyze-agent-behavior/view-benchmark-reporting-in-the-ui.md).
# View Training Session Information
The Training Sessions page allows you to view agent systems' training in real time and analyze their performance in training.
When you begin a training session, the graphs for each trained skill agent will begin to generate. You can watch your skills learn by viewing the graphs, or you can click on the Console Output tab for detailed information about each training decision.
The shape of the curve can help you understand how your skill agents are learning. When the curve plateaus, that usually means that the skill has been successfully trained and will not learn more. If the curve shows jagged ups and downs, then the skill isn't performing consistently and has more learning to do. Sometimes this is a sign that you should go back and adjust the training settings.
The training sessions page shows a list of all the training sessions for a project in a menu on the left of the screen, allowing you to jump between different agents, as well as different training sessions for the same agent system.
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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.amesa.com/train-agents/analyze-agent-behavior/view-benchmark-reporting-in-the-ui.md?ask=&goal=
```
`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.
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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.