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

Input Tokens

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Context

Input

What is your next action?

Expected output

The next action is to call the flight tool with the date 2025-05-29,from_city: London, to_city: Paris

Model output

Reasoning: The user's request is to find information about available flights from London to Paris for tomorrow. In the past trajectory, the system has already determined tomorrow's date as 2025-05-29 by calling the calendar tool. The next logical step is to use the flights tool to find the available flights from London to Paris on the date 2025-05-29. This direct approach aligns with the instructions to be precise, avoid unnecessary loops, and stay focused on the user's goal.

Response: Next action: Call the flights tool with parameters {from_city: 'London', to_city: 'Paris', date: '2025-05-29'} to retrieve available flights for tomorrow.