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

997

Output Tokens

173

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. In the previous cycle, the calendar tool was used to determine tomorrow's date, which was returned as '2025-05-29'. Now that we have the required date, the next logical step is to use the flights tool with the departure city (London), arrival city (Paris), and the travel date (2025-05-29) to retrieve available flight options. This is the most direct action to fulfill the user's request based on the current context and available tools.

Response: I will now use the flights tool to search for available flights from London to Paris on 2025-05-29.