ENGINEERING
On-Demand Loom Transcription via PR Comment Command
When someone comments a slash command with a Loom link on a GitHub PR, this fetches that recording's transcript, structures it into review notes, and replies on the same PR thread.
How it runs
The automated pipeline, trigger to output.
- TriggerPR comment created (GitHub event)GitHub
- LogicParse '/loom-review' command and extract URL
- ActionFetch transcript for the linked LoomLoom
- ActionStructure into review notesOpenAI
- OutputReply with notes on the PR threadGitHub
What it does
Lets any teammate attach a Loom walkthrough to a PR on demand by commenting a command like '/loom-review <url>'. The flow grabs the linked recording's transcript, turns it into structured review notes, and replies in the same thread so the spoken review becomes part of the written PR history.
When to use it
Use it when Loom links get dropped into PR comments ad hoc rather than through a fixed recording pipeline. The comment command gives reviewers explicit control over which videos become formal notes.
How it works
- 1A GitHub issue-comment event triggers when a comment contains the '/loom-review' command.
- 2A logic step parses the Loom URL and ignores comments without the command.
- 3The flow fetches the transcript for that specific Loom video.
- 4OpenAI structures it into a summary, concerns, and requested changes.
- 5GitHub posts the structured notes as a reply on the same PR thread.
Set it up
What you configure once, before turning it on.
- 1Connect GitHubRepos, issues, pull requests, actions.
- 2Connect LoomVideo transcripts, libraries.
- 3Connect OpenAIModels, embeddings, files.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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