PERSONAL PRODUCTIVITY

Weekly Meeting-Overload Detector with Focus-Block Proposals

Every Friday, scans each person's upcoming week of calendar events, flags weeks that cross a meeting-hours threshold.

CategoryPersonal Productivity
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerFriday 3pm weekly schedule
  • ActionFetch next week's events per personGoogle CalendarGoogle Calendar
  • LogicCompute daily load, flag overloaded days
  • ActionDraft focus-block proposals for gapsOpenAI
  • OutputPost summary + approve/decline to Slack DMSlack

What it does

This workflow runs a forward-looking audit of the coming week's calendar. It totals scheduled meeting hours per day, compares them against a configurable overload threshold (for example, more than 60% of working hours booked), and for any overloaded day it proposes concrete focus-block holds in the open gaps. The proposals are summarized in Slack so the person can approve or decline before anything touches their calendar.

When to use it

Use it when individual contributors or managers keep losing deep-work time to meeting creep and you want a proactive nudge instead of a manual weekly review. It is best for teams that already live in Google Calendar and Slack.

How it works

  1. 1A Friday afternoon schedule fires the run.
  2. 2The workflow pulls next week's events from Google Calendar for each configured person.
  3. 3It computes daily and weekly meeting load and checks each day against the overload threshold.
  4. 4For overloaded days only, an OpenAI step drafts focus-block titles and picks the largest open gaps to protect.
  5. 5The proposed blocks and the load summary are posted to the person's Slack DM with approve/decline actions.

Set it up

What you configure once, before turning it on.

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

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