OTHER

Daily Room Capacity Rebalance and Right-Sizing Digest

Each morning analyzes the day's bookings against room sizes, recommends moving oversubscribed small meetings and undersized large bookings.

CategoryOther
EngineSim + Paperclip
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekday morning schedule
  • ActionRead bookings and room metadataGoogle CalendarGoogle Calendar
  • ActionAgent drafts right-sizing swapsOpenAI
  • LogicKeep conflict-free improving swaps
  • ActionWrite pending suggestions to AirtableAirtableAirtable
  • OutputSend rebalance digest to TeamsMicrosoft Teams

What it does

Matches the right meeting to the right room before the day starts. It compares each booking's expected attendee count to the assigned room's capacity, finds mismatches (10 people in a 4-seat room, a 2-person sync in the boardroom), and proposes specific swaps to balance load.

When to use it

Run it as a morning facilities routine when room utilization is uneven and large rooms get burned on tiny meetings while teams cram into closets. It produces an actionable swap plan instead of raw utilization charts.

How it works

  1. 1A schedule fires each weekday morning before peak hours.
  2. 2The workflow reads the day's room bookings from Google Calendar and room metadata from Airtable.
  3. 3An agent reasons over attendee counts versus capacity and drafts right-sizing swaps, respecting AV and accessibility constraints.
  4. 4A logic step keeps only swaps that improve fit without creating new conflicts.
  5. 5Proposed reassignments are written back to Airtable as pending suggestions.
  6. 6A formatted rebalancing digest is delivered to the facilities team in Microsoft Teams for approval.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Google CalendarEvents, attendees, availability.
  2. 2
    Connect AirtableBases, tables, views, automations.
  3. 3
    Connect Microsoft TeamsChannels, chats, files.
  4. 4
    Connect OpenAIModels, embeddings, files.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

Run this workflow in your colony.

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