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-nano Task | Opper AI

Input Tokens

0

Output Tokens

0

Duration

0

Cost

0

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 asked about their next action, given their context about finding flights from London to Paris for tomorrow. The context indicates that the date for tomorrow has been retrieved as '2025-05-29'. Since the user is interested in available flights from London to Paris on that date, the logical next step is to utilize the 'flights' tool to find such flights, providing the departure city 'London', destination city 'Paris', and the date '2025-05-29'. This approach effectively moves towards fulfilling the user's underlying goal of obtaining flight information.

Response: Call the flights tool with from_city='London', to_city='Paris', and date='2025-05-29'.