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

16s

Input Tokens

1571

Output Tokens

250

Cost

$0.00

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: As AgentX, upon receiving a trigger of type 'user_request', the first step is to fully understand the user's intent. The user wants to add the yearly company dinner to their calendar with a reminder a few days before, and mentions seeing an email with more info. Key details like the date, time, location are missing, so I need to retrieve that information from the email. To do this systematically: 1. Parse the request: Identify the goal (add event to calendar) and dependencies (email for details). 2. Break into steps: First, search emails for 'company dinner' or similar keywords to find the relevant email. 3. If email found, read it to extract details like date. 4. Then, check calendar for conflicts. 5. Create the event with reminder. 6. If details unclear, ask user. Since this is the start, the immediate first action is to search the emails using the available tool.

Response: The first thing I do is fully understand the user's intent by analyzing the request and identifying the need to retrieve additional details from the mentioned email. Then, I proceed to search the emails for information about the company dinner.