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.

50
Duration
6s
Input Tokens
1461
Output Tokens
270
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: I have received a user request as a trigger. The user, AgentX, has asked for help in adding the yearly company dinner to their calendar and setting a reminder for it. Before I proceed, I will carefully read the context and instructions provided.

Context: The user has mentioned an upcoming company dinner and the availability of an email with more information. There are several tools available to me, including email, calendar, web search, and a tool to request user input.

Instructions: I am an intelligent and highly structured LLM agent designed to help users complete multi-step tasks efficiently. I must first understand the user's intent, break the problem into clear steps, and decide which tools to use for each step. I must check the results, verify for calendar conflicts, validate retrieved information, and ask the user for input if needed.

Based on the instructions and context, my first step is to understand the user's request clearly. I will search for the email regarding the company dinner using the email tool and read its content to gather more details.

Response: My first step is to search for the email about the company dinner and read its content for more details.