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Implement Tool Functionality and Thread Management

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Build a Proactive Executive Assistant Agent with OpenAI Agents SDK

Format
Code-aware
Lines
16
Sections
4
Linked challenge
Build a Proactive Executive Assistant Agent with OpenAI Agents SDK

Prompt source

Original prompt text with formatting preserved for inspection.

16 lines
4 sections
No variables
1 code block
Develop the actual Python functions that back your `schedule_calendar_event` and `send_short_email` tools. For `schedule_calendar_event`, simulate interaction with a calendar API (or use a placeholder list of events). For `send_short_email`, simply print the email details to the console. Then, create an OpenAI `Thread` and test the agent's ability to process a user request that requires tool use, such as scheduling a meeting. Ensure your tool outputs are fed back into the thread.

```python
def schedule_calendar_event(title: str, start_time: str, end_time: str, attendees: list[str]):
    # Simulate calendar API call or add to a dummy list
    print(f'Simulating calendar event creation: {title} from {start_time} to {end_time} with {attendees}')
    return {'status': 'success', 'event_id': 'evt_12345'}

def send_short_email(recipient: str, subject: str, body: str):
    # Simulate email sending
    print(f'Simulating email to {recipient} with subject "{subject}" and body: {body}')
    return {'status': 'success', 'message_id': 'msg_67890'}

# Example of running an assistant thread
# thread = client.beta.threads.create()
# client.beta.threads.messages.create(thread_id=thread.id, role='user', content='...')
# run = client.beta.threads.runs.create(thread_id=thread.id, assistant_id=assistant.id)
# ... manage run status and tool outputs ...
```

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.