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

1630

Output Tokens

492

Cost

$0.00

Context

Input

The user has replied: "Three days before is fine."  According to the plan for the yearly company-dinner task, what is the next action?

Expected output

Call email.search_emails with a query such as "yearly company dinner" (optionally including the current year) to locate the relevant email(s) containing the event details, and store the returned email_id(s) for the subsequent email.read_email step.

Model output

Reasoning: The user has responded to the question about reminder preferences with "Three days before is fine." Looking at the scratch pad, the current step was to wait for user input about reminder timing, and this has now been received. The remaining goals in order are: (1) Search emails to find the yearly company dinner date, (2) Read the email to extract event details, (3) Add the event to the calendar and check for conflicts, (4) Notify the user if conflicts exist, and (5) Add the reminder as per user preference (3 days). Since the user has confirmed the 3-day reminder preference, the next logical action is to proceed with goal #1: search emails to find information about the yearly company dinner. This aligns with the trajectory that was waiting for user input before searching emails for event details.

Response: Thank you for confirming! I'll set a reminder 3 days before the event. Now let me search for emails about the yearly company dinner to find the event date and details.