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

519

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 trigger was a request to find flights from London to Paris for tomorrow. In the first cycle, the calendar tool was used to determine tomorrow's date as '2025-05-29'. The next logical step is to directly use the 'flights' tool with the established parameters (from_city: London, to_city: Paris, date: 2025-05-29) since it is the most relevant and efficient method to retrieve flight availability. No unnecessary intermediate tools (e.g., web_search) are required here.

Response: Action: call flights tool with parameters { 'from_city': 'London', 'to_city': 'Paris', 'date': '2025-05-29' }