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

1160

Output Tokens

413

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 fulfill the user's request ('find the cheapest flights from London to Paris for tomorrow, and return the top 3 options'), the agent must:
1. Determine the exact date for "tomorrow" – this requires the **calendar** tool (method get_tomorrow_date or similar) to obtain a correctly formatted date string.
2. Search for flights between the two cities on that date, filter/sort them by price, and extract the top three cheapest options – this is handled by the **flights** tool (methods search_flights, filter_by_price, sort_by_duration, get_cheapest_option, etc.).
3. Preserve the retrieved flight information for later reference or further processing – the **memory** tool is used to store the flight list with a clear key, satisfying the rule that every meaningful result must be saved.
Thus, the minimal and sufficient set of tools to complete the task are: **calendar**, **flights**, and **memory**.

Response: You will need to use the following tools: calendar, flights, and memory.