Agents

AI agent reasoning and tool selection tests planning, tool choice, and self-diagnosis capabilities. These skills are crucial for autonomous ticket triage systems and complex agent workflows where models must decide which tools to use, plan multi-step processes, and diagnose when things go wrong. This represents some of the most challenging tasks as they require open-ended reasoning and decision-making.

Duration

12s

Input Tokens

1635

Output Tokens

156

Cost

$0.00

Context

Input

Looking at the trajectory and the scratch pad, what is the next action?

Expected output

The task is complete, the agent process will end

Model output

Reasoning: Based on the context provided, it seems that all tasks related to the user's request have been successfully completed. The user requested the yearly company dinner to be added to the calendar with a reminder set two days before the event. The email was searched, the correct email was identified, the event date was extracted, no calendar conflicts were found, and the event was created with the reminder set correctly. The current step in the scratch pad indicates a final check, and all goals are marked as completed. Therefore, the task cycle is complete, and there are no further actions required.

Response: All steps and goals related to the user's request have been completed. No further action is necessary. Task complete.