SUMMARIZATION
Slack Thread Decision Extractor to Linear
When a Slack thread is closed with an emoji reaction, an LLM reads the whole thread, extracts the decision made and every action item with its owner.
How it runs
The automated pipeline, trigger to output.
- TriggerSlack reaction (wrap-up emoji) added to threadSlack
- ActionFetch full thread: parent message plus all repliesSlack
- ActionLLM extracts decision, rationale, and owner-tagged action itemsOpenAI
- LogicSkip if no action items were extracted
- ActionCreate one assigned Linear issue per action itemLinear
- OutputPost TL;DR with issue links as a threaded replySlack
What it does
Long Slack threads bury the actual decision and the follow-ups under dozens of replies. This workflow watches for a designated "wrap-up" emoji on a thread, reads every message in it, and asks an LLM to produce a structured summary: the decision reached, the rationale, and a list of action items each tagged with an owner and due hint. Each action item becomes a Linear issue assigned to the matching person, and a clean TL;DR is posted back into the thread.
When to use it
Use it for engineering, product, or ops channels where decisions happen in-thread and then get lost. Ideal when your team already closes discussions with a reaction (for example a checkered-flag or white-check-mark) and uses Linear for execution.
How it works
- 1A reaction-added event on a watched emoji fires the trigger.
- 2The full thread (parent plus all replies) is fetched from Slack.
- 3The LLM extracts a JSON object: decision, summary, and action items with owner names.
- 4A filter drops the run if no action items were found, avoiding empty Linear noise.
- 5One Linear issue is created per action item, assigned by mapping Slack display names to Linear users.
- 6A TL;DR with links to the created issues is posted as a threaded reply.
Set it up
What you configure once, before turning it on.
- 1Connect SlackChannels, DMs, threads, mentions.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect LinearIssues, projects, cycles, triage.
- 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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This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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