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.

Duration

Input Tokens

1145

Output Tokens

632

Cost

$0.00

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 wants to find flight information from London to Paris for tomorrow. From the past trajectory, I have already determined that 'tomorrow' corresponds to the date '2025-05-29' using the calendar tool. Now, I have all the necessary parameters (from_city: London, to_city: Paris, date: 2025-05-29) to use the 'flights' tool to fetch the requested information. Therefore, the next logical action is to call the 'flights' tool.

Response: Action: call flights(from_city='London', to_city='Paris', date='2025-05-29')