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 – fireworks/glm-4.5-air Task | Opper AI

Input Tokens

45975

Output Tokens

22413

Duration

196602.895

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: Looking at the scratch pad and trajectory, I can see that this is cycle 6 of 6, and the current step is marked as 'Final check'. All goals have been completed: received user preference, searched emails, read email to extract date, checked for calendar conflicts, created the calendar event with reminder, and recorded all relevant information in memory. The progress explicitly states 'Task complete.' Since all steps have been successfully executed and there are no pending actions or issues indicated in the scratch pad, the next action would be to acknowledge task completion and terminate the process.

Response: Task has been completed successfully. The yearly company dinner event has been added to the calendar for 2025-06-15 with a reminder set 2 days before. No further actions are needed.