PERSONAL PRODUCTIVITY
Meeting Cost Estimator with Pre-Send Trim Nudge
When an organizer creates a calendar invite, it prices the meeting from each attendee's loaded hourly rate and headcount.
How it runs
The automated pipeline, trigger to output.
- TriggerNew calendar event createdGoogle Calendar
- ActionLook up attendee rates in PostgresPostgres
- LogicCompute cost and flag if over threshold
- ActionDM organizer the cost + trim nudgeSlack
- OutputLog estimate to Postgres for trendsPostgres
What it does
Every new Google Calendar event gets an instant price tag. The workflow multiplies each attendee's loaded hourly rate (pulled from a Postgres rate table) by the meeting duration, sums it across the invite list, and sends the organizer a Slack DM with the total cost and the three most expensive attendees. The goal is a gut-check moment before the meeting becomes routine.
When to use it
Run this when recurring "sync" culture is quietly eating budget and you want organizers to feel the cost at the moment of creation, not in a quarterly report. Best for orgs that already track role-based rates.
How it works
- 1A new event is created on a watched Google Calendar.
- 2Attendee emails are looked up against a Postgres `employee_rates` table to fetch loaded hourly rates.
- 3Logic computes cost = sum(rate x duration) and flags meetings over a configured threshold.
- 4For flagged meetings, a Slack DM goes to the organizer with the total, the top-cost attendees, and a one-line nudge to trim optional guests.
- 5The estimate and decision are written back to Postgres for trend reporting.
Set it up
What you configure once, before turning it on.
- 1Connect Google CalendarEvents, attendees, availability.
- 2Connect PostgresAny Postgres URL — query, write, migrate.
- 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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