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

10s

Input Tokens

1081

Output Tokens

642

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 wants to find flights from London to Paris for tomorrow. In the previous cycle, I successfully used the calendar tool to determine that tomorrow's date is 2025-05-29. Now I have all the required parameters to search for flights: departure city (London), arrival city (Paris), and travel date (2025-05-29). The flights tool is available and requires exactly these three parameters. Therefore, the next logical action is to call the flights tool with these parameters to retrieve available flight information.

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