HR & RECRUITING
Interview Loop Rebalancer for Over-Scheduled Panelists
Scans every interviewer's upcoming week, flags anyone past their weekly interview cap, and reassigns surplus loops to qualified, under-booked colleagues.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily load-scan schedule
- ActionPull next-7-day interview events per panelistGoogle Calendar
- ActionRead weekly caps and skill tagsAirtable
- LogicMatch surplus loops to under-booked qualified panelists
- ActionPost proposed swaps with Confirm actionSlack
- OutputReassign invites and update load countsGoogle Calendar
What it does
It keeps interview load fair across the panel. On a daily cadence it reads each interviewer's scheduled loops for the next seven days, compares the count against a per-role cap stored in Airtable, and rebalances the overflow onto qualified colleagues who still have headroom. Proposed swaps go to the recruiting channel for a one-click confirm before any calendar changes are made.
When to use it
Use it when a few senior engineers absorb most of the interviews and burn out while others sit idle. Ideal for teams running structured loops where panelists are interchangeable within a skill tag (e.g. "backend coding", "system design").
How it works
- 1A daily schedule fires the scan.
- 2Google Calendar returns each interviewer's next-7-day interview events.
- 3Airtable supplies per-person weekly caps and skill tags.
- 4A logic step finds over-cap interviewers and matches each surplus loop to an under-booked panelist with the same skill tag.
- 5Slack posts the proposed reassignments with Confirm / Skip actions.
- 6On confirm, the calendar invite is reassigned to the new panelist and Airtable load counts are updated.
Set it up
What you configure once, before turning it on.
- 1Connect Google CalendarEvents, attendees, availability.
- 2Connect AirtableBases, tables, views, automations.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
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