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

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Context

Input

Asses the current state and decide if we are on track or not

Expected output

We are on track

Model output

Reasoning: Assessing the current state of the flight search task: 1) We've successfully completed step 1 by retrieving tomorrow's date (2025-05-29) using the calendar tool. 2) The date is in the correct format (YYYY-MM-DD) as required by the flights tool. 3) We're currently at cycle 3 and step 2 of 4 total steps. 4) The next logical action is to call the flights tool with London as departure city, Paris as arrival city, and date 2025-05-29. 5) We have all required parameters to proceed with the flights search. Based on this assessment, we are on track to complete the task.

Response: On track. We have successfully obtained tomorrow's date (2025-05-29) through the calendar tool and are now ready to use the flights tool with the required parameters (London to Paris on 2025-05-29). We are currently at cycle 3, step 2 of 4, following the planned progression.