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 – groq/moonshotai/kimi-k2-instruct Task | Opper AI

Input Tokens

44330

Output Tokens

5168

Duration

86046.109

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 trajectory shows that all planned steps have been executed successfully: the user's email was searched, the event date was extracted, the calendar was checked for conflicts, and the event with its reminder was created. The scratch pad explicitly states 'Step 6 of 6. Task complete.' and lists the final memory keys. Since every goal is marked as completed and the agent's instructions say to terminate without notification once a task is complete, the next action is to finish the process.

Response: Terminate the process; task completed successfully.