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 38s

Input Tokens

1011

Output Tokens

248

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: <think>Alright, let's break this down step by step. The user asked about flights from London to Paris for tomorrow. In the previous cycle, we determined that tomorrow's date is 2025-05-29 using the calendar tool. Now, we need to find flight information for that date.

Looking at the available tools, we have a 'flights' tool which seems perfect for this task. The 'flights' tool requires three parameters: 'from_city', 'to_city', and 'date'. Based on the user's request, these parameters should be:
- from_city: London
- to_city: Paris
- date: 2025-05-29

Since we have all the necessary information, the next step would be to call the 'flights' tool with these parameters to get the available flights.
</think>

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