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

977

Output Tokens

464

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: Based on the context, I can see that the user requested information about flights from London to Paris for tomorrow. In the previous cycles, we've already determined that tomorrow's date is 2025-05-29 by using the calendar tool. Now that we have all the necessary information (departure city, arrival city, and date), the logical next step is to use the flights tool to search for available flights matching these criteria.

Response: My next action is to call the flights tool with the following parameters: from_city: 'London', to_city: 'Paris', date: '2025-05-29' to find available flights for the user's requested route and date.