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

21s

Input Tokens

1617

Output Tokens

446

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 provided their preference for the reminder timing - three days before the event. Looking at the scratch_pad, the agent had asked the user for this information and was waiting for their response. Now that the response has been received (3 days before), the agent can proceed to the next step in the plan: searching emails to find the yearly company dinner date. The user mentioned in the original request that they saw some email with more info about the event. Therefore, the next action is to search the user's emails for information about the yearly company dinner.

Response: The next action is to search the user's emails for information about the yearly company dinner. The agent should use the email tool with the 'search_emails' action, using a query like "yearly company dinner" to find the relevant email containing the event details and date.