Opper

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.

Agents – openai/gpt-5 Task | Opper AI

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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: We asked the user how many days in advance they prefer the reminder and received the answer: 3 days. Per the plan, once we have the reminder preference, the next step is to find the event details by searching the user's emails for the yearly company dinner information. This requires using the email tool to locate the relevant email(s), then we can read the most relevant one to extract the exact date and details before creating the calendar event and setting the reminder.

Response: Next action: Use the email tool to search for the yearly company dinner email, e.g., email.search_emails with a query like: "yearly company dinner" OR "annual company dinner" OR "company dinner" OR "year-end dinner". Then read the top relevant result to extract the event date and details.