SUMMARIZATION
Slack Incident Thread to Linear Post-Mortem Tasks
When an incident thread is resolved in Slack, an LLM builds a timeline and root-cause summary, classifies severity, and on high-severity incidents creates Linear follow-up issues…
How it runs
The automated pipeline, trigger to output.
- TriggerSlack :resolved: reaction added to incident threadSlack
- ActionFetch full incident thread with message timestampsSlack
- ActionLLM builds timeline, root cause, remediation, and severityOpenAI
- LogicBranch on severity: high-sev gets full post-mortem
- ActionCreate Notion post-mortem page and Linear remediation issuesLinear
- OutputPost summary with post-mortem and issue links to threadSlack
What it does
Incident channels generate fast, chaotic threads. When responders mark an incident resolved (a :resolved: reaction or keyword), this workflow reconstructs the event: a chronological timeline, the root cause, impact, and remediation steps. It classifies severity from the thread content and branches accordingly. High-severity incidents get a full post-mortem page in Notion and tracked Linear follow-up issues; low-severity ones just get a logged summary reply.
When to use it
Use it for on-call and SRE channels where incidents are triaged in Slack and you owe a post-mortem afterward. It removes the friction of writing one from scratch and guarantees high-sev incidents always get tracked follow-ups.
How it works
- 1A resolved-reaction event on an incident thread fires the trigger.
- 2The full thread is fetched, including timestamps for the timeline.
- 3The LLM outputs timeline, root cause, impact, remediation, and a severity label.
- 4A severity branch routes the run: high-sev continues to full handling; otherwise it short-circuits to a summary reply.
- 5For high-sev, a post-mortem page is created in Notion and one Linear issue per remediation item is opened.
- 6A summary with links to the post-mortem and issues is posted back to the thread.
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.
- 4Connect NotionPages, databases, comments.
- 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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Run this workflow in your colony.
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