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.

Input Tokens

Output Tokens

Duration

Cost

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: The user's task is to identify which tools are required to fulfill the request 'I need to find the cheapest flights from London to Paris for tomorrow, and return the top 3 options'.

1.  **Determine the date 'tomorrow'**: This requires a tool capable of date manipulation. The 'calendar' tool has methods like 'get_tomorrow_date' which directly addresses this need.
2.  **Search for flights**: The core of the request is to find flights. The 'flights' tool is specifically designed for this with methods like 'search_flights', 'filter_by_price', and 'get_cheapest_option'. The parameters 'from_city', 'to_city', and 'date' align perfectly with the user's request.
3.  **Store results**: The agent's instructions explicitly state: 'Always store meaningful results in memory using the memory tool.' Therefore, the 'memory' tool will be needed to store the flight search results.

Response: To successfully complete the task, I will need to use the following tools:

1.  **calendar**: To determine the date for 'tomorrow'.
2.  **flights**: To search for flights, filter by price, and retrieve the top options.
3.  **memory**: To store the retrieved flight information as per the agent's instructions.