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 – gcp/gemini-2.5-flash-lite Task | Opper AI

Input Tokens

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Output Tokens

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Duration

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Cost

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Context

Input

What is your next step?

Expected output

I have surpassed the maximum allowed cycles. Termination.

Model output

Reasoning: The user wants to add a company dinner to their calendar and set a reminder. The trajectory indicates that the agent has already identified the event date (2025-06-15) and verified no calendar conflicts. The next logical step is to create the event in the calendar with the specified reminder. The `calendar` tool has a `create_event` action that can be used for this purpose. The `event_name` would be 'Yearly Company Dinner' and the `date` is '2025-06-15'. The user requested a reminder 'a couple days before', which can be translated to `reminder_days_before=2`.

Response: {"tool_code": "print(calendar.create_event(event_name='Yearly Company Dinner', date='2025-06-15', reminder_days_before=2))"}