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

23s

Input Tokens

3363

Output Tokens

1145

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: ANALYZE: From the context the calendar tool provides date & time utilities. Its params_schema shows get_current_date requires a single property: action with value 'get_current_date'. Following the GENERAL RULES I must inspect the schema before invoking the tool (schema inspection is satisfied by reading the provided context). PLAN: The next single atomic action is to call the calendar tool's get_current_date method. ACT: Call the calendar tool with parameters {"action": "get_current_date"}. REFLECT: The expected result is an ISO-8601 date string (e.g., '2025-08-19' given the current system date). Per memory discipline, after a successful call I will store the returned date in memory with memory.store_item using key 'current_date' and the returned value. DECIDE: After storing the date I will use it to timestamp the help-desk note (e.g., call database.write_note), but the immediate required call is the calendar get_current_date call.

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