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

1759

Output Tokens

303

Cost

$0.01

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: Based on the context and the scratch pad, the agent was waiting for the user to specify how many days in advance they wanted the reminder. The user has replied 'Three days before is fine.' Now that the agent has this information, the next logical step according to the remaining goals in the scratch pad is to search the user's emails to find the date and details of the yearly company dinner.

Response: The next action is to use the email tool's 'search_emails' action with a query like 'yearly company dinner' to find the email containing the details and date of the upcoming event.