You are helping me build the following AI agent workflow.

## Goal
Interview Scheduling and Data Cleanup: Syncs Cal.com interview bookings to Google Sheets, formats times for Riyadh timezone, and auto-cleans blank or unmatched entries.

## Specification
- What it does: You get a clean, Riyadh-time formatted schedule in Google Sheets as soon as you book an interview on Cal.com. The agent matches applicants by email and instantly removes any blank or unmatched entries to keep your data accurate.
- Trigger: Triggered by an event (Event · on new interview booking)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Cal.com: Fetch interview bookings
  - Google Sheets: Store and update applicant data
  - HTTP Request: Retrieve booking details from Cal.com
  - Code: Format dates and clean data records

## Known pitfalls, handle each one explicitly in your implementation
1. Timezone mismatches between Cal.com and Google Sheets can cause interview times to appear off by several hours so always normalize timestamps to UTC before formatting.
2. Email matching logic might fail on typos or aliases causing missed syncs so add a fuzzy match fallback or manual review queue for low-confidence matches.

## Reference implementation
https://n8n.io/workflows/5481 (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/automate-interview-scheduling-and-data-cleanup/ via usecasesforagents.com