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

1084

Output Tokens

397

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: Looking at the context, I can see that the user requested information about flights from London to Paris for tomorrow. The previous cycle successfully determined tomorrow's date as 2025-05-29 using the calendar tool. Now, the most logical next step is to use the flights tool to find available flights matching the user's requirements. The flights tool requires three parameters: from_city (London), to_city (Paris), and date (2025-05-29). This will directly address the user's original request for flight information.

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