CONTENT CREATION

On-demand Loom URL chaptered into a Coda tutorial via webhook

Accepts a Loom share URL through a webhook, pulls its transcript, chapters it, generates per-section images.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWebhook receives a Loom share URLHTTP webhook
  • LogicValidate URL and extract video ID
  • ActionFetch transcript and metadata from LoomLoomLoom
  • ActionSegment transcript into chaptersOpenAI
  • ActionGenerate cover image per chapterImage generation
  • OutputReturn Coda tutorial URL in webhook responseCodaCoda

What it does

Gives you a single endpoint that converts any Loom share link into a Coda tutorial on demand. Paste a URL into a form, button, or another tool, and the webhook responds with a finished, chaptered, illustrated Coda doc — no waiting for the recording-finished event.

When to use it

Use it for older Loom videos that predate your automation, or when you want a self-serve button (internal tool, browser bookmarklet, support macro) that anyone can fire to document a specific demo right now.

How it works

  1. 1An inbound webhook arrives carrying a Loom share URL.
  2. 2A logic step validates the URL and extracts the video ID.
  3. 3A Loom action fetches the transcript and metadata for that ID.
  4. 4OpenAI segments the transcript into titled, timestamped chapters.
  5. 5generate-image creates a cover image per chapter.
  6. 6A Coda action builds the tutorial doc with sections, deep links, and images.
  7. 7The Coda doc URL is returned synchronously in the webhook response.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect HTTP webhookTrigger any URL on agent actions.
  2. 2
    Connect LoomVideo transcripts, libraries.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect Image generationManaged Nano Banana image renders, metered per image.
  5. 5
    Connect CodaDocs, packs, automations.
  6. 6
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  7. 7
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  8. 8
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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