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

29s

Input Tokens

1345

Output Tokens

353

Cost

$0.00

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: Step 1: Understand the task - Determine the appropriate action when a tool call (calendar tool) returns an error in the context of finding flights from London to Paris for tomorrow.
Step 2: Analyze the context - User goal: flights London to Paris tomorrow. Previous action: call calendar for date -> error 'tool not available'. Tools: calendar (errored), flights (needs date YYYY-MM-DD), web_search. Scratch pad: tool ERROR, decide next. Cycle 3. Remaining: use flights tool, present results. Max retries 3.
Step 3: Follow instructions - As AgentX, after tool error: think about error, decide next action. Error indicates calendar unavailable despite 'available' status, so retry risky (likely permanent). Avoid loops. Direct path: need date for flights tool. Alternative: use web_search for current/tomorrow's date.
Step 4: Approach - Do not retry calendar (error specific). Use web_search to get date (precise query for format). Then call flights. Track in scratch pad.
Step 5: Next action - Call web_search with query to get tomorrow's date. This progresses to goal without retrying failed tool.

Response: Think about the error: The calendar tool is not available despite its status. Do not retry it to avoid loops. Instead, use the web_search tool as an alternative to determine tomorrow's date. Next action: Call web_search with query: 'What is tomorrow\'s date in YYYY-MM-DD format?' Then, use the result to call the flights tool with from_city: 'London', to_city: 'Paris', date: [retrieved date]. Update scratch pad with progress.