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

1805

Output Tokens

279

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 provided the necessary information: 'Three days before is fine.' This corresponds to the 'reminder_days_before' parameter, which was the missing piece of information from the previous step (Step 2 of 6 in the scratchpad).

The plan outlined in the scratchpad is:
1. Asked user for how many days before the event they want the reminder (Completed by user input).
2. Search emails to find the yearly company dinner date (Next action).
3. Read the email to extract event details.
4. Add the event to the calendar and check for conflicts.
5. Notify the user if conflicts exist.
6. Add the reminder as per user preference.

Since the reminder preference (3 days) is now known, the next logical step is to proceed with finding the event details, which requires searching the emails for 'yearly company dinner'.

Therefore, the next action is to use the `email.search_emails` tool with a relevant query.

Response: The next action is to search the user's emails for information regarding the yearly company dinner to find the event date. I will use the `email.search_emails` tool with the query 'yearly company dinner'.