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

18s

Input Tokens

3598

Output Tokens

239

Cost

$0.00

Context

Input

You must find today's date so you can time-stamp a help-desk note. Which tool do you call and with what parameters?

Expected output

Use the **calendar** tool with parameters {"action": "get_current_date"}.

Model output

Reasoning: Step 1: Read the task - Need to find today's date to timestamp a help-desk note.
Step 2: Analyze available tools from context. The 'calendar' tool has 'get_current_date' method, described as part of 'Date & time utilities'. Its params_schema shows for 'get_current_date': required ['action'], properties {'action': {'const': 'get_current_date'}}, no other parameters needed.
Step 3: Confirm no other tool provides current date (database is for orders/customers/notes, email for comms, user_input for interaction, memory for storage).
Step 4: Per instructions, inspect schema first (already provided in context, no metadata method needed). This is the atomic first action: call calendar with precise params.
Step 5: After call (hypothetically), would store result in memory as e.g. 'current_date', but task asks only for tool and params.
Step 6: Efficiency: Direct match, no chaining or redundancy needed.

Response: Call the 'calendar' tool with parameters: {"action": "get_current_date"}