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

11s

Input Tokens

1658

Output Tokens

811

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 now provided the reminder timing preference (3 days before). According to the plan outlined in the scratch_pad, the agent was waiting for this user input before proceeding. The remaining goals show that the next logical step is to search emails to find the yearly company dinner date. This is step 3 of the 6-step plan. The agent should use the email.search_emails tool with a query like 'yearly company dinner' to locate the relevant email containing event details.

Response: Search the user's emails for information about the yearly company dinner to find the event date and details.