PERSONAL PRODUCTIVITY
Quarterly meeting-cancellation recommendation brief
Quarterly, the agent gathers a full quarter of recurring-meeting data, reasons over attendance, agenda quality, and cost together.
How it runs
The automated pipeline, trigger to output.
- TriggerQuarterly schedule fires
- ActionRead quarter of events and cost ledgerGoogle Calendar
- LogicAgent reasons over attendance, agenda, and cost
- ActionWrite recommendation brief to Coda docCoda
- OutputPost executive summary to SlackSlack
What it does
Produces a judgment call, not just a list. Once a quarter the agent assembles a quarter's worth of recurring-meeting signals from the calendar and the running Coda cost ledger, weighs declining attendance, chronic missing agendas, and accumulated cost against each other, and writes a reasoned brief that recommends a specific action per meeting: cancel, merge into another, shorten, or keep. Each recommendation includes the why.
When to use it
Use it for the quarterly operating review when you want a defensible, narrative recommendation to bring to leadership rather than a raw metrics dump. Best when you already have the monthly cost ledger feeding it.
How it works
- 1A quarterly schedule fires.
- 2The agent reads the quarter's recurring events from Google Calendar and the cost history from the Coda ledger.
- 3It scores each meeting on attendance trend, agenda presence, and cost.
- 4It reasons across the signals to choose cancel, merge, shorten, or keep per meeting with rationale.
- 5It writes the brief back to a Coda doc and posts the executive summary to Slack for the review.
Set it up
What you configure once, before turning it on.
- 1Connect Google CalendarEvents, attendees, availability.
- 2Connect CodaDocs, packs, 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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