You are helping me build the following AI agent workflow.

## Goal
Restaurant Booking Assistant: Chat with the bot to book a table; it gathers details via conversation, saves them to Google Calendar, and emails confirmation.

## Specification
- What it does: Book a table instantly by chatting with the bot on Telegram to share your guest count, preferences, and special requests. Once you confirm the details, it automatically saves the reservation in Google Calendar and sends you an email confirmation.
- Trigger: Run manually (Manual · on demand via Telegram)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Telegram: User interaction and notifications
  - OpenAI Chat Model: Natural language conversation and data extraction
  - Google Calendar: Storing confirmed reservations
  - Gmail: Sending confirmation emails

## Known pitfalls, handle each one explicitly in your implementation
1. Time zone mismatches between the user's local time and Google Calendar can cause wrong event times so always specify the timezone explicitly in the API call.
2. Telegram message handlers may drop updates if they take too long to process so implement a quick acknowledgment reply before performing heavy LLM or calendar operations.
3. Email delivery delays can make users think their booking failed so include a unique tracking ID in the email body and log the send status immediately.

## Reference implementation
https://n8n.io/workflows/7769 (workflow template)
Fetch and inspect this before building. If it matches my stack, adapt it;
if not, rebuild the pattern with my tools.

## Process requirements
1. Before building: ask me which of the listed tools I actually use and
   what my platform is (n8n / Make / code / other). Do not assume.
2. Adapt the pattern to my answers; do not force the reference stack.
3. Address every pitfall above; tell me how you handled each.
4. Provide a test plan I can run before letting this touch real data.
5. Ask before any step that sends messages, modifies data, or spends money.

Source: https://usecasesforagents.com/use-case/restaurant-booking-assistant/ via usecasesforagents.com