SUMMARIZATION

Per-deploy Sentry regression brief to Slack

On every Vercel production deploy, pulls the new and spiking Sentry error groups, clusters them by root-cause signature.

CategorySummarization
Enginesim
Difficultyintermediate
Triggerwebhook
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerVercel deployment succeeded webhookVercelVercel
  • ActionFetch new and spiking Sentry issues for releaseSentrySentry
  • LogicCluster issues by root-cause signature
  • LogicDrop clusters below noise threshold
  • ActionSummarize each cluster into a regression briefOpenAI
  • OutputPost release-health brief to SlackSlack

What it does

Turns the raw firehose of Sentry issues that appear after a deploy into one readable verdict. It fetches every error group that is new or newly spiking since the release, groups them by shared root-cause signature (same stack frame, exception type, or culprit), and writes a short brief: what broke, how many users are hit, and whether the release looks safe.

When to use it

When you ship to production several times a day and nobody has time to babysit the Sentry issues feed. Use it to get an automatic health read on each deploy without staring at dashboards.

How it works

  1. 1A Vercel deployment-succeeded webhook fires with the new release version.
  2. 2Query Sentry for issues first seen or spiking in that release window.
  3. 3Cluster the issues by root-cause signature so duplicate symptoms collapse into one cause.
  4. 4Filter out groups below a noise threshold (few events, no user impact).
  5. 5An LLM writes a plain-English brief per cluster with severity and likely cause.
  6. 6Post the brief to the team's deploys Slack channel, tagging the release.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect VercelDeploys, runtime logs, analytics.
  2. 2
    Connect SentryErrors, performance, releases.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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