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

16s

Input Tokens

1034

Output Tokens

531

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 current request is a follow-up to the previous flight inquiry. The trajectory shows that the calendar tool was already used in cycle 3 to determine tomorrow's date as '2025-05-29'. Since the date is already known and the user is asking about flights for tomorrow, the next logical action is to use the flights tool with the confirmed date. The flights tool requires from_city, to_city, and date parameters. The context provides London as the departure city and Paris as the destination, with the date already determined. No additional tools are needed at this stage.

Response: Call flights tool with from_city: London, to_city: Paris, date: 2025-05-29