AI AGENTS
Sentry Regression Bisect to Pinpoint Commit MR
On a Sentry regression (resolved issue reopens), an agent git-bisects to find the introducing commit and opens a GitLab MR with a reverting test and the blamed change.
How it runs
The automated pipeline, trigger to output.
- TriggerSentry regression alert (resolved issue reopens)Sentry
- ActionFetch failing event and prior resolution commitSentry
- ActionBuild repro script in shell sandboxShell
- ActionRun git bisect against the reproShell
- LogicProceed only if bisect converges on one commit
- OutputOpen GitLab MR with guard test and blamed commitGitLab
What it does
Targets regressions specifically. When Sentry reopens an issue that was previously marked resolved, the agent treats it as a regression and runs an automated git bisect against a reproduction script to find the exact commit that reintroduced the bug. It then opens a GitLab MR that links the offending commit, adds a guard test, and proposes the fix or revert.
When to use it
Use it when regressions keep slipping back into a fast-moving service and you want the introducing commit identified automatically rather than by hand.
How it works
- 1Sentry fires a regression alert when a resolved issue reopens.
- 2The agent retrieves the failing event details and the prior resolution commit from the Sentry issue.
- 3It clones the repo and builds a one-shot repro script from the captured payload in a shell sandbox.
- 4The agent runs `git bisect run` against the repro to isolate the introducing commit.
- 5Logic gate: proceed only when bisect converges on a single commit.
- 6It writes a regression-guard test and opens a GitLab MR naming the blamed commit and author.
Set it up
What you configure once, before turning it on.
- 1Connect SentryErrors, performance, releases.
- 2Connect GitLabRepos, MRs, pipelines, registry.
- 3Connect ShellRun sandboxed commands inside the workspace.
- 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.
More AI Agents workflows
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When a Sentry issue is resolved, the agent finds the matching Confluence runbook page and proposes an inline update with the verified fix.
Stale Doc-PR Chaser for Runbook Gaps
On a daily schedule the agent finds runbook doc PRs that were opened from resolved incidents but never reviewed, summarizes what each one fixes.
Resolved Incident to Public Troubleshooting Doc
For customer-facing errors resolved in Sentry, the agent drafts a sanitized troubleshooting entry and opens a PR to your ReadMe documentation.
On-Call Runbook Gap Closer: Resolved Sentry Issues to Doc PRs
An agent reads each newly resolved Sentry issue, compares the actual fix against your existing runbook, and opens a GitHub PR adding the missing remediation steps.
Weekly On-Call Doc-Gap Digest
Each week the agent reviews every Sentry issue resolved in the last 7 days, ranks the ones whose runbook coverage is missing or thin.
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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