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

1117

Output Tokens

189

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 has already requested information about available flights from London to Paris for tomorrow, and the current task is to determine the next action. The context indicates that the user previously asked for this information, and the past trajectory included determining tomorrow's date using the calendar tool. The tool response returned the date '2025-05-29'. Since the date is now confirmed, the next logical step is to use the flights tool to find available flights between the cities on that date. The required parameters for the flights tool (from_city, to_city, date) are all available from the context.

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