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

1319

Output Tokens

266

Cost

$0.00

Context

Input

You attempted to call flights.search_flights, but the tool failed twice due to a timeout error. What is your next action according to the model instructions?

Expected output

Retry the flights.search_flights call one more time (maximum retries = 3), and if it fails again, log the failure and proceed with fallback steps or inform the user.

Model output

Reasoning: The user's goal is to find the cheapest flights from London to Paris for tomorrow (2025-05-29) and return the top 3 options. I have already used the calendar tool to get tomorrow's date. I then tried to call `flights.search_flights`, but it failed twice due to a timeout error. According to the instructions, I have a maximum of 3 retries for a tool call. Since the tool has failed twice, I will retry it a third time. If this attempt also fails, I will log the failure and decide on an alternative approach or report the issue. I will call `flights.search_flights` with the parameters: `from_city='London'`, `to_city='Paris'`, `date='2025-05-29'`, and `max_results=3`. After the tool call, I will store the results in memory.

Response: Retry the `flights.search_flights` tool call for the third time with the parameters: `from_city='London'`, `to_city='Paris'`, `date='2025-05-29'`, and `max_results=3`.