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

404

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 answered the pending question about the reminder lead time: they want a reminder three days before the event. This satisfies the first goal (obtaining the reminder preference). According to the remaining goals in the scratch pad, the next step is to locate the event details. The agent should therefore proceed to the email search phase: use the email tool to search the user's mailbox for messages containing information about the "yearly company dinner". Once the relevant email is identified, the agent will read it, extract the event date, and continue with the subsequent steps (conflict check, calendar creation, reminder setup).

Response: Proceed to the next step by searching the user's emails for the yearly company dinner details (e.g., using the email.search_emails tool with a query like "yearly company dinner").