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

1033

Output Tokens

168

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's request is to find information about available flights from London to Paris for tomorrow. The context provides the past trajectory and the current cycle. In the past trajectory, the user asked about flights from London to Paris for tomorrow, and the first action was to call the calendar tool to determine tomorrow's date. The calendar tool returned '2025-05-29'. Now, the next logical step is to use the flights tool to find available flights from London to Paris for the date '2025-05-29'. Therefore, the next action should be to call the flights tool with the appropriate parameters.

Response: The next action is to call the flights tool with the parameters: from_city='London', to_city='Paris', and date='2025-05-29'.