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

1212

Output Tokens

285

Cost

$0.01

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 context:

1. The user wants to find flights from London to Paris for tomorrow.
2. We already called the calendar tool and got today's date: '2025-05-29'.
3. Therefore, tomorrow's date is '2025-05-30'.
4. We now have all the required parameters to call the flights tool:
   - from_city: 'London'
   - to_city: 'Paris'
   - date: '2025-05-30'
5. The next logical step is to call the flights tool with these parameters to find available flights.

Response: {"action": "call_tool", "tool": "flights", "params": {"from_city": "London", "to_city": "Paris", "date": "2025-05-30"}, "reasoning": "The calendar tool returned today's date as 2025-05-29, so tomorrow is 2025-05-30. Now I have all required parameters to search for available flights from London to Paris on 2025-05-30. Calling the flights tool to retrieve the available options for the user."}