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

1336

Output Tokens

824

Cost

$0.00

Context

Input

Of the available tools. Which ones will you need to use to successfully complete the task?

Expected output

All tools will need to be used: calendar, flights,memory

Model output

Reasoning: To complete the task 'find the cheapest flights from London to Paris for tomorrow, and return the top 3 options' while adhering to the strict agent instructions, the following steps and tools are required:

1. **Resolve the Date**: The user specifies 'tomorrow'. The `calendar` tool is needed to accurately determine the date string for tomorrow using the `get_tomorrow_date` method.
2. **Search for Flights**: The core request requires flight data. The `flights` tool is necessary to `search_flights` from London to Paris on the resolved date.
3. **Manage State/Compliance**: The instructions explicitly state: 'Always store meaningful results in memory using the memory tool. This means after every tool call, you store the results in memory.' Therefore, the `memory` tool is mandatory to store the output of the calendar and flight search operations.

Response: calendar, flights, memory