Agents

You want to schedule three follow-up reminders:
• One for tomorrow,
• One for five business days later,
• One exactly two weeks later.
You are allowed to call tools in parallel, as they run in the cloud. What tool calls will you make?

First: Call **calendar.get_current_date** → {"action": "get_current_date"} and persist result as "today".

In Parallel:
• **calendar.add_business_days** → {"action": "add_business_days", "start_date": "today", "days_to_add": 1}
• **calendar.add_business_days** → {"action": "add_business_days", "start_date": "today", "days_to_add": 5}
• **calendar.add_business_days** → {"action": "add_business_days", "start_date": "today", "days_to_add": 14}

Next: For each result, persist separately using **memory.store_item** with keys like "date_plus_1", "date_plus_5", "date_plus_14".

Then: For each stored date, call **calendar.schedule_reminder** with {"action": "schedule_reminder", "date": "<calculated_date>", "reminder_text": "Follow-up"}.

Finally: Persist each reminder result separately using **memory.store_item** with keys like "reminder_tomorrow", "reminder_5bdays", "reminder_2wks".

Reasoning: Based on the task, we need to schedule three follow-up reminders at different future dates. The instructions allow parallel tool calls, so the plan is to call the calendar tool's schedule_reminder method three times: one scheduled for tomorrow, another scheduled for five business days later, and the final one scheduled for exactly two weeks later. In each call, we would include a parameter (typically an ISO-8601 datetime in 'send_at') that reflects the specific timing for each reminder. This approach follows the instruction to minimize redundant calls and to take advantage of parallel execution in the cloud.

Response: I will make three parallel calls to the 'calendar' tool using the 'schedule_reminder' method with the following parameters: (1) send_at = tomorrow's date, (2) send_at = current date plus five business days, and (3) send_at = current date plus two weeks. Each call will be logged in memory after a successful scheduling.