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

1021

Output Tokens

613

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 initial request was to find information about available flights from London to Paris for tomorrow. The previous step in the trajectory successfully identified 'tomorrow's date' as '2025-05-29' by calling the 'calendar' tool. Now that all the necessary parameters (departure city: London, arrival city: Paris, date: 2025-05-29) are available, the next logical step is to use the 'flights' tool to find the required flight information. The 'flights' tool is available and its schema matches the required parameters.

Response: call flights tool with parameters: from_city='London', to_city='Paris', date='2025-05-29'