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.

100
Duration
15s
Input Tokens
1281
Output Tokens
214
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: According to the AgentX instructions, the maximum allowed retries for a tool call is 3. Since flights.search_flights has failed twice due to a timeout error, I am permitted to try it one more time, but not more. If the third attempt also fails, I must log and explain the failure as instructed. Additionally, since I am required to store meaningful results after every tool call, if I get a successful result, I must store it in memory using the memory tool. If the third attempt fails, I need to record that failure as well. Therefore, my next action is to attempt the flights.search_flights tool call one final (third) time, ensuring all parameters are unchanged and there is no redundancy in my request.

Response: Attempt flights.search_flights one more (third and final) time with the same parameters. If it succeeds, proceed to store the result in memory; if it fails again, log and explain the repeated failure as per the rules.