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

1351

Output Tokens

281

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: Step 1: Understand the task - Identify which available tools are needed to complete the user's request of finding the cheapest flights from London to Paris for tomorrow and returning the top 3 options. Step 2: Analyze the context - Available tools are: calendar (for date handling like getting tomorrow's date), flights (for searching and filtering flight info by price, sorting, getting cheapest options), and memory (for storing results). Step 3: Map to requirements - To get 'tomorrow', use calendar tool (e.g., get_tomorrow_date). To search for flights from London to Paris on that date, filter by price, and get top 3 cheapest, use flights tool (e.g., search_flights, filter_by_price, get_cheapest_option). After obtaining results, store them using memory tool as per instructions. Step 4: Determine necessity - Calendar is needed for the date, flights is essential for the core task, memory is required post-tool calls. All three will be used logically in sequence.

Response: To successfully complete the task, I will need to use all three available tools: calendar (to determine tomorrow's date), flights (to search, filter by price, and retrieve the top 3 cheapest flight options), and memory (to store the results after tool calls).