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

1131

Output Tokens

365

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 flights from London to Paris for tomorrow. The calendar tool was already used in a previous cycle to determine tomorrow's date (2025-05-29). The next logical step is to use the 'flights' tool with the parameters from_city='London', to_city='Paris', and date='2025-05-29' to retrieve available flight information. This directly addresses the user's request without unnecessary steps.

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