SUMMARIZATION
Extract Unresolved MR Concerns into Linear Follow-up Issues
On merge request approval, distills the comment thread and turns every concern that was acknowledged but not resolved into a tracked Linear issue.
How it runs
The automated pipeline, trigger to output.
- TriggerGitLab MR approved eventGitLab
- ActionFetch discussion notes with resolution stateGitLab
- ActionExtract acknowledged-but-deferred concernsOpenAI
- LogicStop if no deferred concerns found
- ActionCreate a Linear issue per deferred concernLinear
- OutputPost created-issues summary back on the MRGitLab
What it does
This workflow runs when an MR is approved and scans the discussion for concerns that reviewers flagged but the author punted on with "good catch, follow-up later". It distills each into a discrete, actionable item and files it in Linear, linked back to the MR, so deferred feedback becomes tracked work instead of a buried comment.
When to use it
Use it when your team routinely ships with "we'll fix it next sprint" promises that evaporate. It converts the soft commitments inside review threads into hard backlog items with an owner and a link.
How it works
- 1GitLab MR approval event triggers the run.
- 2The workflow pulls every discussion note and its resolution state.
- 3OpenAI identifies concerns that were acknowledged but explicitly deferred, ignoring resolved and cosmetic ones.
- 4A logic step skips the run entirely if there are zero deferred items.
- 5Each deferred concern becomes a Linear issue with the MR link and original quote.
- 6A summary note is posted back on the MR listing the created issues.
Set it up
What you configure once, before turning it on.
- 1Connect GitLabRepos, MRs, pipelines, registry.
- 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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Run it inside a business
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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