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

40s

Input Tokens

1145

Output Tokens

226

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 trajectory, I can see that:
1. The user requested flight information from London to Paris for tomorrow
2. In the previous cycle, I called the calendar tool to determine tomorrow's date
3. The calendar tool returned '2025-05-29' as tomorrow's date
4. Now I have all the necessary information to search for flights

The next logical step is to use the flights tool to search for available flights from London to Paris on 2025-05-29. I have:
- Departure city: London
- Arrival city: Paris
- Date: 2025-05-29 (tomorrow's date from the calendar tool)

All required parameters for the flights tool are available, so I should proceed with calling it.

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