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

39s

Input Tokens

1081

Output Tokens

968

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 requested information about available flights from London to Paris for tomorrow. In the previous cycle (cycle 2), I used the calendar tool to determine that tomorrow's date is 2025-05-29. I now have all the required information to proceed: departure city (London), arrival city (Paris), and the travel date (2025-05-29). The flights tool is available and specifically designed for finding flight information, requiring exactly these three parameters. Since I have all necessary data and a specialized tool for the task, the most direct and effective next action is to invoke the flights tool.

Response: Call the flights tool with parameters: from_city="London", to_city="Paris", date="2025-05-29" to retrieve available flights from London to Paris on May 29, 2025.