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
18s
Input Tokens
976
Output Tokens
178
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 has triggered a request to find available flights from London to Paris for tomorrow. From the context, I see that in the previous cycle, the calendar tool was called and returned the date '2025-05-29' as tomorrow's date. The next logical step is to use the flights tool to find available flights from London to Paris on that date. Since the tools are available and the date is known, I will proceed to call the flights tool with the parameters: from_city = 'London', to_city = 'Paris', date = '2025-05-29'. This is the direct and efficient next action to achieve the user's goal.

Response: My next action is to call the flights tool to find available flights from London to Paris on 2025-05-29.