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

Input Tokens

3598

Output Tokens

238

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: Analyze the task - I need to find today's date to timestamp a help-desk note. Reviewing available tools, the 'calendar' tool provides date & time utilities, including 'get_current_date' which directly retrieves the current date without any additional parameters.
Step 2: Plan the next atomic action - Inspect the schema for 'calendar' confirms that 'get_current_date' requires only the 'action' parameter set to 'get_current_date'. No other tools (like database, email, user_input, or memory) are relevant for obtaining the current date.
Step 3: Act - The single tool to call is 'calendar' with parameters {'action': 'get_current_date'}.
Step 4: Reflect - This is efficient, requires no prior data, and aligns with memory discipline (results can be stored post-call if needed). No retries or escalation necessary.
Step 5: Decide - Proceed with this tool call to obtain the date for timestamping.

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