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

12s

Input Tokens

976

Output Tokens

197

Cost

$0.00

Context

Input

What is your next action?

Expected output

The next action is to call the flight tool with the date 2025-05-29,from_city: London, to_city: Paris

Model output

Reasoning: The user is requesting information about available flights from London to Paris for tomorrow. Based on the previous cycle, we already have tomorrow's date determined as '2025-05-29'. The context indicates that tools available to me include a calendar tool, a flights tool, and a web search tool. Since I need to find specific flight information based on the given cities and date, the most appropriate tool to use next is the flights tool. I will call this tool with the parameters 'from_city' as 'London', 'to_city' as 'Paris', and 'date' as '2025-05-29'. This will be a direct action following the user's request and context provided without unnecessary detours.

Response: Next, I will proceed to use the flights tool with the parameters: from_city='London', to_city='Paris', date='2025-05-29'.