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
15s
Input Tokens
976
Output Tokens
192
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 asked about the next action to perform given the context of identifying available flights from London to Paris for tomorrow. Based on the context, the necessary steps are already partially completed: the current date (2025-05-29) has been retrieved from the calendar tool, and the user has asked about flights for the next day, 2025-05-30. The next logical step is to initiate a flight search using the flights tool, providing from_city as 'London', to_city as 'Paris', and date as '2025-05-30'. Therefore, I will prepare the parameters to call the flights tool with this data to find available flights for tomorrow.

Response: Call the flights tool with from_city 'London', to_city 'Paris', and date '2025-05-30' to find available flights from London to Paris for tomorrow.