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

1535

Output Tokens

297

Cost

$0.00

Context

Input

What is your next step?

Expected output

I have surpassed the maximum allowed cycles. Termination.

Model output

Reasoning: The task is 'What is your next step?'. Based on the context, this is a continuation of a multi-step task where the agent (AgentX) is handling a user request to add a yearly company dinner to the calendar and set a reminder two days before. The context shows that in the current cycle (cycle 20), the agent has already: received the user request, searched emails for 'yearly company dinner', identified the correct email, and extracted the event date (2025-06-15), and verified no calendar conflicts. However, the context ends at 'current_cycle: 20', and the next action is not yet executed. Since the event date and conflict check are complete, the next logical step is to create the calendar event with a reminder 2 days before, using the 'calendar.create_event' action. However, before doing so, the agent should ensure all required parameters are available: event_name ('Yearly Company Dinner'), date ('2025-06-15'), and reminder_days_before (2). These are known from context. No additional user input is needed at this point. Therefore, the next step is to execute 'create_event' with these parameters.

Response: Creating the calendar event for 'Yearly Company Dinner' on 2025-06-15 with a reminder set 2 days before.