MARKET RESEARCH
Open a Linear issue when a feature complaint spikes
Monitors incoming reviews for a sudden surge of negative mentions of one feature.
How it runs
The automated pipeline, trigger to output.
- TriggerNew reviews detected on store listingApify
- ActionPull latest review batchApify
- ActionClassify feature, sentiment, and cluster complaintsOpenAI
- LogicCheck for negative-mention spike past threshold
- ActionDraft bug summary with symptoms and quotesOpenAI
- OutputCreate triaged Linear issue for owning teamLinear
What it does
Continuously checks fresh reviews and watches for an abnormal spike in negative mentions of any single feature within a short window. When a spike clears the threshold, it summarizes the recurring symptoms, attaches representative review quotes, and opens a Linear issue routed to the team that owns that feature, so a regression becomes a tracked bug instead of scattered complaints.
When to use it
Use it when you want review sentiment to feed your engineering backlog directly. Ideal right after a release or server-side change, when a broken feature produces a fast cluster of similar one-star reviews that should become an actionable ticket.
How it works
- 1New reviews are detected on the store listing.
- 2Apify pulls the latest batch of reviews.
- 3OpenAI classifies feature and sentiment and clusters similar complaints.
- 4A logic step checks whether negative mentions of a feature spiked past the threshold for the window.
- 5On a spike, OpenAI drafts a bug summary with symptoms and quotes.
- 6Linear creates a triaged issue assigned to the feature's owning team.
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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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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