SUMMARIZATION
Release-Regression Summary Commented on the GitHub PR
When a release deploys, finds the Sentry clusters it introduced and posts a summary as a comment on the merged pull request behind that release, closing the loop with the authors.
How it runs
The automated pipeline, trigger to output.
- TriggerVercel deploy webhook with release and commitVercel
- ActionResolve the commit to its merged GitHub PRGitHub
- ActionQuery Sentry for issues first-seen in the releaseSentry
- LogicBranch on whether new clusters were found
- ActionSummarize the regressions tied to the changeOpenAI
- OutputComment the summary on the GitHub PRGitHub
What it does
This workflow tells the people who shipped a change exactly what their change broke. After a release deploys, it identifies the new Sentry error clusters and posts a summary directly as a comment on the GitHub pull request associated with that release, so the authors and reviewers see the regression in the same place they discussed the code.
When to use it
Use it when you want regression feedback to reach contributors in context rather than in a shared alerts channel they might ignore. Ideal for teams who tie releases to PRs and want post-merge accountability without a manual writeup.
How it works
A Vercel deploy webhook carries the release version and the commit it was built from. The flow resolves that commit to its merged pull request via GitHub, then queries Sentry for issues first-seen in the release. If new clusters exist, the model writes a concise summary describing each one and its likely link to the change. That summary is posted as a comment on the PR with Sentry links; when no regressions are found, the flow posts a brief clean-deploy note so the absence of issues is recorded too.
Set it up
What you configure once, before turning it on.
- 1Connect VercelDeploys, runtime logs, analytics.
- 2Connect SentryErrors, performance, releases.
- 3Connect GitHubRepos, issues, pull requests, actions.
- 4Connect OpenAIModels, embeddings, files.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, 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.
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