Opper

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.

Agents – cerebras/qwen-3-32b Task | Opper AI

Input Tokens

0

Output Tokens

0

Duration

0

Cost

0

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 requires determining the next action based on the provided trajectory and scratch pad. The trajectory shows that the agent has: 1) received user request to add a yearly company dinner to the calendar with a 2-day reminder, 2) searched emails and found the correct one (ID: email_12345), 3) confirmed the event date (2025-06-15), 4) verified no calendar conflicts, 5) created the calendar event (ID: event_98765) with the reminder. The scratch pad explicitly states 'All steps successfully completed.' and 'Progress: Step 6 of 6. Task complete.' Since the final step (creating the event and reminder) has been executed and no further goals or missing information are indicated, the next action is to terminate the process as the task is fully completed.

Response: The task is complete. The yearly company dinner on 2025-06-15 has been successfully added to your calendar with a reminder set for 2 days before the event. No further action is required.