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.

100
Duration
12s
Input Tokens
973
Output Tokens
164
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: The user's request is to find information about available flights from London to Paris for tomorrow. From the past trajectory, we have already determined tomorrow's date as '2025-05-29' using the calendar tool. The next logical step is to use the flights tool to retrieve the flight information, as it directly matches the task requirements. The flights tool requires from_city, to_city, and date parameters. I will provide these based on the user's request and the obtained date. This is the most direct and effective path to fulfill the user's goal without unnecessary steps.

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