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 – groq/moonshotai/kimi-k2-instruct Task | Opper AI

Input Tokens

44330

Output Tokens

5168

Duration

86046.109

Cost

0

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 model instructions, the maximum number of retries for a tool call is 3. The flights.search_flights tool has already failed twice due to a timeout error, so one retry remains. The next action, therefore, is to attempt the same flights.search_flights call one more time. If it fails again, I must log and explain the failure and stop further attempts, since the retry limit will have been reached.

Response: Execute one final retry of flights.search_flights({"from_city":"London","to_city":"Paris","date":"2025-05-29","max_results":20}). If this third attempt also times out, report the persistent failure to the user and terminate the search.