Agents – novita/deepseek-v4-flash Task

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

44s

Input Tokens

2603

Output Tokens

3328

Cost

$0.00

Context

Input

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?

Expected output

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".

Model output

Reasoning: First, I need to obtain the current date to compute the target dates. I will call `calendar.get_current_date`. Then, for the five-business-day offset, I can call `calendar.add_business_days` with an offset of 5. For the other two reminders (tomorrow and two weeks later), I need to add 1 and 14 calendar days respectively. Since no tool exists to add calendar days, I will compute these dates manually after receiving the current date. Once all three target dates are known, I will make three parallel calls to `calendar.schedule_reminder` (assuming it accepts a datetime and a reminder message). After each successful schedule, I will store the reminder ID in memory using `memory.store_item` for traceability. The calls are partially parallel: `get_current_date` and `add_business_days` can run first, then the three schedule calls in parallel.

Response: The tool calls are:
1. `calendar.get_current_date` (to get today's date)
2. `calendar.add_business_days` with offset=5 (to get the date for five business days later)
3. After computing tomorrow's date (today + 1 calendar day), call `calendar.schedule_reminder` with that date and a reminder message
4. Using the result from step 2, call `calendar.schedule_reminder` with that date and a reminder message
5. After computing two weeks later (today + 14 calendar days), call `calendar.schedule_reminder` with that date and a reminder message
6. For each scheduled reminder, call `memory.store_item` with key `reminder_1`, `reminder_2`, `reminder_3` and value the returned reminder ID.

These calls can be made in parallel after steps 1 and 2 are complete and the manual computations are done.

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: First, I need to obtain the current date to compute the target dates. I will call `calendar.get_current_date`. Then, for the five-business-day offset, I can call `calendar.add_business_days` with an offset of 5. For the other two reminders (tomorrow and two weeks later), I need to add 1 and 14 calendar days respectively. Since no tool exists to add calendar days, I will compute these dates manually after receiving the current date. Once all three target dates are known, I will make three parallel calls to `calendar.schedule_reminder` (assuming it accepts a datetime and a reminder message). After each successful schedule, I will store the reminder ID in memory using `memory.store_item` for traceability. The calls are partially parallel: `get_current_date` and `add_business_days` can run first, then the three schedule calls in parallel. Response: The tool calls are: 1. `calendar.get_current_date` (to get today's date) 2. `calendar.add_business_days` with offset=5 (to get the date for five business days later) 3. After computing tomorrow's date (today + 1 calendar day), call `calendar.schedule_reminder` with that date and a reminder message 4. Using the result from step 2, call `calendar.schedule_reminder` with that date and a reminder message 5. After computing two weeks later (today + 14 calendar days), call `calendar.schedule_reminder` with that date and a reminder message 6. For each scheduled reminder, call `memory.store_item` with key `reminder_1`, `reminder_2`, `reminder_3` and value the returned reminder ID. These calls can be made in parallel after steps 1 and 2 are complete and the manual computations are done.