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

1061

Output Tokens

184

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: 'What is your next action?'. Based on the context, this is part of a multi-cycle task where the user previously requested flight information from London to Paris for tomorrow. Cycle 1 established tomorrow's date as 2025-05-29 using the calendar tool. Now, in current_cycle: 3, the agent should proceed to find available flights using the 'flights' tool with the known parameters: from_city='London', to_city='Paris', date='2025-05-29'. Since the 'flights' tool is available and all required parameters are known, the next action is to call the flights tool.

Response: call flights tool with from_city='London', to_city='Paris', date='2025-05-29'