SUMMARIZATION

Loom Standup Action Items into Linear Issues

Transcribes new standup Looms, pulls out concrete action items and their assignees, and creates or updates matching Linear issues so commitments don't get lost in video.

CategorySummarization
Enginesim
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew Loom standup uploadedLoomLoom
  • ActionGet transcript from LoomLoomLoom
  • ActionExtract action items with assignees and due datesHugging FaceHugging Face
  • LogicMatch against existing Linear issuesLinearLinear
  • OutputCreate new issues or comment on matchesLinearLinear

What it does

When a standup Loom is posted, this workflow converts spoken commitments into tracked Linear work. It transcribes the video, isolates explicit action items ("I'll wire up the webhook by Thursday"), maps each to an assignee, and creates a Linear issue, or comments on an existing one if the work is already tracked.

When to use it

Use it when verbal commitments in async standups never make it to your tracker. This closes the gap between what people say they'll do and what's actually in the backlog.

How it works

  1. 1A new Loom standup upload triggers the run.
  2. 2Loom returns the transcript.
  3. 3A Hugging Face model extracts action items, each with an assignee and any stated due date.
  4. 4A logic step checks Linear for an existing matching issue by title similarity and assignee.
  5. 5New action items become Linear issues; matches get a progress comment linking back to the Loom timestamp.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LoomVideo transcripts, libraries.
  2. 2
    Connect Hugging FaceModels, datasets, spaces — the open-source hub.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  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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