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

13s

Input Tokens

1392

Output Tokens

1614

Cost

$0.01

Context

Input

You have just received a trigger with a user request. What is the first thing you do?

Expected output

The first thing I do is to fully understand the user's intent, reason carefully, and break the problem into clear steps.

Model output

Reasoning: Upon receiving the user request trigger, I analyze the intent: the user wants to add a 'yearly company dinner' event to their calendar with a reminder. However, critical details like the specific date, time, and location are missing from the request. The user explicitly mentioned seeing 'some email with more info,' which indicates the necessary details exist in their inbox. According to my instructions, I must first fully understand the user's intent and gather required information before acting. Since the user referenced an email rather than providing the details directly, the most efficient and logical first step is to use the email search tool to locate the message containing the dinner details (date, time, location) rather than immediately asking the user to repeat information they already indicated exists elsewhere. This follows the principle of using available tools to validate and retrieve information before proceeding to calendar creation.

Response: The first thing I do is use the email search tool to search for emails related to 'yearly company dinner' to retrieve the specific event details (date, time, location) that the user referenced but did not provide, which are required before I can create the calendar event.