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

1621

Output Tokens

146

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: User has now provided the missing preference: reminder should be 3 days before. According to the trajectory/scratch pad, the immediately next planned step after receiving this input is to search the user’s emails for the yearly company dinner details (especially date), then read the relevant email and proceed. Therefore the next action is an email search query for the event info.

Response: Next action: proceed to the email lookup step by using the **email.search_emails** tool to find the yearly company dinner message (e.g., query: "yearly company dinner"), then read the relevant email to extract the event date/details before creating the calendar event with a **3-day reminder**.