SUMMARIZATION
Weekly Sentry Regression-Trend Report to Notion
Each week, summarizes which deploys introduced the most new error clusters, compares against prior weeks for trend, and publishes a written quality report to a Notion page.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly scheduled run
- ActionPull the week's releases and first-seen issues from SentrySentry
- LogicAggregate new-cluster counts and compute trend vs prior weeks
- ActionWrite the regression-trend reportOpenAI
- OutputPublish the report to a dated Notion pageNotion
What it does
This workflow rolls a week of deploy regressions into a written quality report. It tallies how many new error clusters each release introduced across the week, summarizes the worst offenders, and compares the totals against recent weeks so the team can see whether release quality is improving or slipping. The finished narrative is published to Notion as a durable record, not a fleeting chat message.
When to use it
Use it when engineering leadership wants a recurring, readable view of release stability rather than raw dashboards. Good for teams running weekly quality or reliability reviews who need a written artifact with trend context.
How it works
A weekly scheduled run pulls every release from the past seven days out of Sentry along with the issues first-seen in each. The flow aggregates new-cluster counts per release and per day, then reads the prior weeks' stored totals to compute the trend direction. The model writes the report: the week's headline, the releases that caused the most new clusters with short summaries, and a paragraph on how this week compares to the trailing average. The report is written to a dated Notion page and the week's totals are saved for next week's comparison.
Set it up
What you configure once, before turning it on.
- 1Connect SentryErrors, performance, releases.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect NotionPages, databases, comments.
- 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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