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

16s

Input Tokens

1040

Output Tokens

478

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: Let me analyze the current state:

1. User's original request: Find information about available flights from London to Paris for tomorrow
2. Previous actions taken:
   - Called the calendar tool to determine tomorrow's date
   - Result: Tomorrow's date is '2025-05-29'

3. Now I have all the required parameters for the flights tool:
   - from_city: London
   - to_city: Paris
   - date: 2025-05-29

4. The flights tool is available and requires exactly these three parameters (from_city, to_city, date).

The logical next step is to call the flights tool with the gathered information to retrieve the available flights for the user.

Response: Action: call flights tool with parameters {"from_city": "London", "to_city": "Paris", "date": "2025-05-29"}