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.
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.
Step by step
- Configure the Cal.com webhook to POST booking events to the agent's endpoint.
- Map the incoming JSON payload fields to specific column headers in the target Google Sheet.
- Implement a deterministic date parser that converts ISO 8601 strings into local time zone formats using standard library functions.
Where the LLM does the work
- Generate the natural language logic for identifying and filtering out 'blank' or 'irrelevant' rows based on evolving HR definitions of valid data.
- Draft the error handling messages that explain why a specific booking was skipped during cleanup to ensure transparency for non-technical HR staff.
Watch out for
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.
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.
Tools that fit
HTTP Request API Retrieve booking details from Cal.com
Code LLM Format dates and clean data records
The agent brief
Everything your agent needs, including the gotchas. Copy it and go.
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
Frequently asked questions
Can I use a different Calendar than Cal.com?
Yes. Cal.com is only the example calendar in this recipe. The same flow works with Calendly, Eventbrite and Google Calendar. Swap the calendar connection and keep the rest of the setup as written.
Want this running in your business?
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.
Who it's for
Built for HR and recruiting teams who need a repeatable first pass, not a one-off.