PERSONAL PRODUCTIVITY

Overlapping Meeting Merge-Candidate Finder

Weekly, compares recurring meetings across the team to find series with heavily overlapping attendee lists and similar topics.

CategoryPersonal Productivity
Enginesim
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule
  • ActionFetch all recurring series with attendeesGoogle CalendarGoogle Calendar
  • LogicBuild attendee sets and topic signatures
  • LogicCompute pairwise overlap, keep candidates above threshold
  • OutputPost proposed merge pairings to SlackSlack

What it does

This workflow hunts for redundant recurring meetings that could be combined. Each week it collects all recurring series, builds an attendee set and a topic signature for each (from titles and descriptions), and compares every pair. When two series share most of their attendees and cover similar ground, the flow proposes them as a merge candidate. The owner gets a Slack message listing each suggested pairing with the overlap percentage and a recommended single replacement slot.

When to use it

Use this when the same group of people sits in three different standing meetings that all blur together. Instead of manually diffing calendars, you get an automated shortlist of "these two could be one meeting," which is the fastest way to reclaim hours without cutting any real coverage.

How it works

  1. 1A weekly schedule triggers the audit.
  2. 2The flow fetches all recurring series from Google Calendar with their attendees and descriptions.
  3. 3It builds attendee sets and topic signatures, then computes pairwise overlap.
  4. 4A filter keeps only pairs above the attendee-overlap and topic-similarity thresholds.
  5. 5Proposed merge pairings are posted to Slack with overlap scores and a suggested consolidated time.

Set it up

What you configure once, before turning it on.

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

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