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

Input Tokens

1696

Output Tokens

197

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: The task was to add the yearly company dinner to the user's calendar and set a reminder 2 days before the event. The trajectory shows that the email with the event details was successfully found and read, the event date (2025-06-15) was extracted, calendar conflicts were checked and none were found, and the event was created with the appropriate reminder. The scratch pad confirms that all steps have been completed and the progress is at Step 6 of 6, indicating the task is fully complete. Since all goals have been achieved and no further action is required, no additional tool use or user notification is needed.

Response: Task complete. The event 'Yearly Company Dinner' has been successfully added to the calendar on 2025-06-15 with a reminder set for 2 days prior. No further action is required.