Opper

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.

Agents – openai/gpt-5-nano Task | Opper AI

Input Tokens

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Output Tokens

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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: I will use the calendar tool to compute tomorrow's date, then the flights tool to search for London→Paris options on that date (limiting to 3 results to obtain the top 3 cheapest). I will store intermediate results in memory after the search to maintain state for subsequent steps.

Response: Required tools: calendar, flights, memory. Plan: 1) Get tomorrow's date with calendar.get_tomorrow_date. 2) Use flights.search_flights with from_city='London', to_city='Paris', date='<tomorrow>', max_results=3. 3) Optionally refine by price using get_cheapest_option or sort_by_price to ensure the top 3 cheapest. 4) Store the results in memory using memory.store_item with a clear key (e.g., 'flight_search_tomorrow_LON_PAR').