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

1m 1s

Input Tokens

3371

Output Tokens

252

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: 1. Understand the user's request: The user wants to find information about available flights from London to Paris for tomorrow. From the context, it was established that tomorrow is May 29, 2025, and I have tools available to confirm this date and find the flights. 2. Plan of action: I will use the 'calendar' tool to confirm the date, and then I will use the 'flights' tool to find available flights. 3. Iterative approach: I will follow these steps in order, keeping track of progress and using the tools provided. 4. Precise and effective path: I will avoid unnecessary loops and stay focused on the user's goal, which is to find available flights for the given date.

Response: To complete the task, I will first use the 'calendar' tool to confirm the date '2025-05-29'. After that, I will use the 'flights' tool to find available flights from London to Paris for the confirmed date. I will then provide the list of available flights as the final answer.