ENGINEERING

Design-review action items to GitHub issues

Parses a finished Zoom architecture review for follow-up action items, then opens a labeled GitHub issue for each one with assignee and context so commitments made on the call…

CategoryEngineering
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerZoom recording completed for review meetingZoomZoom
  • ActionFetch transcript from ZoomZoomZoom
  • ActionExtract action items with ownersOpenAI
  • LogicFilter vague or duplicate items per loop
  • OutputCreate labeled GitHub issue per action itemGitHubGitHub

What it does

Listens for completed Zoom architecture-review recordings and mines the transcript for concrete action items - the "someone needs to spike X" and "we'll benchmark Y" commitments. Each item becomes its own GitHub issue in the target repo, tagged and assigned, so the follow-ups don't evaporate when the call ends.

When to use it

Use it when design reviews generate plenty of TODOs that never make it into the tracker. Ideal for teams whose engineering work lives in GitHub and who want every spoken commitment to land as a trackable issue automatically.

How it works

  1. 1A Zoom recording-completed event triggers for the review meeting.
  2. 2Pull the transcript text from the Zoom API.
  3. 3An LLM extracts a list of action items, each with a suggested owner and one-line context.
  4. 4A logic loop iterates the extracted items, filtering out vague or duplicate statements.
  5. 5For each valid item, create a GitHub issue with an "architecture-review" label, the owner mapped to a GitHub handle, and a link back to the recording.

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 GitHubRepos, issues, pull requests, actions.
  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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