CONTENT CREATION

Weekly Loom walkthrough digest into a Notion KB with Slack rollup

On a weekly schedule, collects all new Loom recordings, drafts a help-doc for each with extracted screenshots, files them under the right Notion knowledge-base section.

CategoryContent Creation
Enginesim
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionList new Loom recordings and fetch transcriptsLoomLoom
  • ActionDraft help-doc and propose KB section (OpenAI)OpenAI
  • ActionCapture step screenshots from each recordingLoomLoom
  • ActionFile drafts into Notion knowledge baseNotionNotion
  • OutputPost weekly digest to SlackSlack

What it does

Runs once a week to sweep up every new Loom walkthrough, turn each into a screenshot-backed help-doc draft, and file them into the correct section of your Notion knowledge base. It finishes by posting one Slack digest summarizing all the docs created that week.

When to use it

Use it when recordings pile up faster than anyone documents them and you'd rather batch the work than handle each video individually. The weekly cadence and single digest keep noise low while ensuring nothing recorded goes undocumented.

How it works

  1. 1A weekly schedule triggers the workflow.
  2. 2All Loom recordings created since the last run are listed and their transcripts fetched.
  3. 3For each recording, an OpenAI model drafts a help-doc and proposes the matching knowledge-base category.
  4. 4A screenshot is captured at each step's timestamp and embedded in the draft.
  5. 5Each draft is filed under its proposed section in the Notion knowledge base.
  6. 6A single rollup of all docs created is posted to a Slack channel.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LoomVideo transcripts, libraries.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect NotionPages, databases, comments.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  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.

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