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

997

Output Tokens

171

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 information about available flights from London to Paris for tomorrow. The previous step involved determining tomorrow's date, which was found to be '2025-05-29' using the calendar tool. Now that we have the date, the next logical step is to use the flights tool to search for available flights from London to Paris on that date. I will prepare the parameters for the flights tool, specifying the departure city as 'London', the arrival city as 'Paris', and the date as '2025-05-29'.

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