CONTENT CREATION
Turn a new Loom recording into a chaptered ReadMe help article draft
When a Loom recording finishes processing, pull its transcript, auto-generate chapters and a structured how-to article with an LLM.
How it runs
The automated pipeline, trigger to output.
- TriggerNew Loom recording processedLoom
- ActionFetch transcript, title, and timestampsLoom
- ActionLLM generates chapters and structured articleOpenAI
- LogicSkip if transcript too short for an article
- ActionCreate unpublished draft in ReadMeReadMe
- OutputPost draft link to docs Slack channelSlack
What it does
Watches your Loom workspace for newly processed recordings, extracts the full transcript and timestamps, and uses an LLM to convert the spoken walkthrough into a clean, chaptered help article. The finished draft lands in ReadMe in unpublished state so a writer can review before it goes live.
When to use it
For support and docs teams who record product walkthroughs in Loom and want a first-draft article without manually transcribing and reformatting. Best when you'd rather edit a structured draft than write from a blank page.
How it works
- 1A new Loom recording finishes processing and fires the trigger.
- 2Fetch the recording's transcript, title, and timestamped segments from Loom.
- 3An LLM segments the transcript into logical chapters and rewrites it as a step-by-step help article with headings, removing filler words.
- 4A length check decides whether the transcript is substantial enough to warrant an article or should be skipped.
- 5Create the article as an unpublished draft in ReadMe with the embedded Loom video and generated chapters.
- 6Post the draft link to the docs Slack channel for review.
Set it up
What you configure once, before turning it on.
- 1Connect LoomVideo transcripts, libraries.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect ReadMeAPI docs, changelog, auth.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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