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

1697

Output Tokens

367

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 scratch pad and trajectory show that all six steps of the task have been successfully finished: the user's request was understood, the relevant email was found and read, the event date was extracted, the calendar was checked for conflicts, and the calendar event with the appropriate reminder was created. The notes explicitly state "All steps successfully completed" and "Task complete". Therefore there are no remaining goals or pending checks, and according to the agent's instructions, once a task is complete the process should be terminated without further actions. Consequently, the next action is to do nothing.

Response: No further action is required; the task is complete.