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 – openai/gpt-4.1-mini 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: The task is to assess the current state of progress in handling the user's request about available flights from London to Paris for tomorrow (2025-05-29) and decide if we are on track. From the context: 1) The user triggered a request for flight info. 2) The calendar tool was called and returned the correct date (2025-05-29), matching the required format. 3) The next step is to use the 'flights' tool to search flights on that date. 4) Current progress is step 2 of 4, meaning we are midway through the plan. The scratch pad shows a clear understanding of next steps and logical sequencing. All tools are available. There are no signs of errors or delays. Given these, the process is consistent with the plan and on track to complete the task efficiently without unnecessary loops or deviations.

Response: We are on track with the task. The calendar tool has correctly provided the date for tomorrow, and the next step to use the flights tool to search for available flights is well defined and ready to be executed. The plan is progressing logically and efficiently toward fulfilling the user's request.