SUMMARIZATION

Quality-gate Loom demos and route weak transcripts for re-recording

When a Loom demo is chaptered into Coda, this scores the transcript for clarity and coverage with OpenAI.

CategorySummarization
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew Loom demo processedLoomLoom
  • ActionFetch transcript + chapters from Coda indexCodaCoda
  • ActionScore clarity and feature coverage with OpenAIOpenAI
  • LogicBranch on pass/fail score threshold
  • ActionFlag passing demo as published in CodaCodaCoda
  • OutputCreate Notion review card for failing demoNotionNotion

What it does

After a Loom demo is transcribed and chaptered, OpenAI scores it on clarity, audio coverage, and whether it actually demonstrates the stated feature. High-scoring demos get marked published in Coda; weak ones are routed to a Notion review queue with the specific reasons they failed.

When to use it

Use this when demo quality is uneven and bad recordings keep leaking into your searchable library. It keeps the index trustworthy by catching mumbled, incomplete, or off-topic demos before they get surfaced in search.

How it works

  1. 1A Loom webhook fires on a newly processed demo video.
  2. 2The flow fetches the transcript and existing chapter data already written to the Coda index.
  3. 3OpenAI scores the transcript 0-100 on clarity and feature coverage and returns a pass/fail with reasons.
  4. 4A logic branch splits on the score threshold.
  5. 5Passing demos are flagged published in the Coda row; failing demos create a Notion review-queue card listing the gaps for the recorder to fix.

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 CodaDocs, packs, automations.
  4. 4
    Connect NotionPages, databases, comments.
  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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