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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Context

Input

The tool call has returned an error. What should you do?

Expected output

Interpret the error and if appropriate, retry the tool call.

Model output

Reasoning: Tool error handling plan: attempt a controlled retry of the failing tool, then switch to a deterministic date calculation and proceed with alternative search methods if the primary tool is unavailable, keeping the user informed and asking for clarifications if needed.

Response: Here is the plan to handle the tool error and continue with the flight search for tomorrow: 1) Retry the failing tool (calendar) up to 3 times in this cycle to see if it recovers. If it still errors, proceed to the next step. 2) Compute tomorrow's date locally from the system date and format it as YYYY-MM-DD. 3) Use the flights tool with from_city: 'London', to_city: 'Paris', date: '<tomorrow>' to fetch available flights. 4) If flights results are returned, present the options (times, airlines, prices) concisely. 5) If the flights tool fails or returns no results, perform a web search for flights London to Paris for tomorrow and summarize best matches. 6) If needed, ask the user for clarifications (e.g., preferred airports, time window) or permission to broaden search. Note: ensure the date format matches the tool requirement (YYYY-MM-DD).