SUMMARIZATION

Zoom Webinar Recording to Chaptered ReadMe How-To Article

When a Zoom webinar recording finishes processing, transcribe it, segment it into timestamped chapters with a TL;DR, and publish a structured how-to article to ReadMe as a draft.

CategorySummarization
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerZoom recording completedZoomZoom
  • ActionFetch transcript + metadataZoomZoom
  • LogicSkip if no usable transcript
  • ActionSegment into chapters + TL;DROpenAI
  • ActionAssemble chaptered Markdown
  • OutputCreate ReadMe draft articleReadMeReadMe

What it does

Turns a finished Zoom webinar into a publish-ready how-to article in ReadMe. It pulls the cloud recording, runs the transcript through a summarizer that splits the talk into logical chapters with start timestamps, writes a short TL;DR at the top, and creates a ReadMe draft page so a docs editor only has to review, not author.

When to use it

Use it for recurring product webinars, training sessions, or office hours where the recording is the source of truth but nobody has time to hand-write docs. Best when you want every webinar to leave behind a searchable article instead of an orphaned video link.

How it works

  1. 1A Zoom recording-completed event fires for the webinar.
  2. 2The flow fetches the recording's transcript (VTT) and metadata from Zoom.
  3. 3A guard checks the recording is long enough and has a usable transcript; trivial or empty recordings are skipped.
  4. 4OpenAI segments the transcript into ordered chapters, each with a heading and a clickable timestamp, then drafts a TL;DR.
  5. 5The chapters and TL;DR are assembled into Markdown.
  6. 6The article is published to ReadMe as a draft page for editor review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ZoomMeetings, recordings, transcripts.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect ReadMeAPI docs, changelog, auth.
  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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