MARKET RESEARCH
Review-to-Linear: Auto-File Top Feature Requests as Roadmap Issues
Mines app-store reviews for feature requests, deduplicates them against existing Linear issues, and files new requests as Linear issues with verbatim quotes and a vote count.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule fires
- ActionPull past-week reviewsApify
- ActionExtract and canonicalize feature requestsOpenAI
- LogicMatch against existing Linear issuesLinear
- OutputCreate new issue or bump votes + priorityLinear
What it does
This workflow closes the loop between user reviews and your engineering backlog. It detects feature requests buried in reviews, checks whether each is already tracked in Linear, opens a new issue for genuinely new asks, and bumps an existing issue's vote count and priority when reviewers keep requesting the same capability.
When to use it
Use it when product wants user demand to flow directly into the roadmap tool engineers live in, without a PM manually copying quotes. Best for teams that triage in Linear and want demand-weighted prioritization.
How it works
- 1A weekly schedule starts the run.
- 2Apify pulls the past week of reviews.
- 3OpenAI extracts only the feature-request reviews and normalizes each into a short canonical request title.
- 4A logic step searches Linear for an existing matching issue.
- 5If none exists, create a Linear issue with the verbatim quote and source link; if one exists, increment its vote count in a custom field and raise priority past thresholds.
- 6The created or updated issues form the output the roadmap team reviews.
Set it up
What you configure once, before turning it on.
- 1Connect ApifyActors, scrapers, datasets.
- 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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