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incident-response

Guide production incident handling by establishing impact, start time, and recent changes before proposing action. Document evidence for rollback requests, keep the issue updated, and distinguish service recovery from resolution that explains the incident.

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How this team handles a production incident issue — what to establish before proposing a fix, and what an agent may and may not do on its own.

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适用场景

  • Establish the impact and start time of a production incident
  • Check whether deployments align with the incident timeline
  • Prepare a rollback request with supporting evidence
  • Record the timeline and reasoning in an incident issue

包含的文件(1)

  • SKILL.md2.6 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Incident response

An incident issue is not a bug report. The goal is to stop the bleeding first and explain it second, and those two are frequently in tension.

Establish, in this order

  1. Blast radius. Who is affected and how badly. An error rate that doubled from 0.01% is not the same incident as one that doubled from 4%.
  2. When it started. Get a timestamp before you get a theory. The first timestamp people offer is usually when somebody noticed, not when it began.
  3. What changed. Call correlate_deploys with the service and a window that starts before the timestamp from step 2. An empty result is informative: it means this is probably not a deploy, and you should stop looking there.

Do not skip to step 3. A deploy that landed in the window is not automatically the cause, and the fastest way to waste an hour is to roll back the first plausible change and watch the incident continue.

Rollback

request_rollback files a change request. It does not roll anything back — a human approves it. So filing one is cheap, and you should file it as soon as you have a specific deploy and a reason, rather than waiting until you are certain.

The reason you write goes into the change record verbatim and is what the approver reads at 3am. Write the evidence, not the conclusion:

  • Good: "error rate on checkout-api went 0.2% → 6% within 90s of deploy d-4821; no other deploy in the window; the diff touches the retry path."
  • Bad: "this deploy broke checkout."

Deploys older than the configured rollback window are refused. That is deliberate: past that point a rollback is usually more dangerous than a fix forward, and it needs a human deciding, not a tool call.

What to write on the issue

Update the issue as you go rather than at the end. Someone else may be reading it to decide whether to escalate, and an issue that goes quiet for twenty minutes reads as "nobody is on this".

Keep the timeline in the issue description and the reasoning in comments. The description is what someone reads six months later during a postmortem; the comments are what your colleagues read right now.

What not to do

  • Do not change issue status to done because the error rate recovered. Recovery and resolution are different; an incident stays open until somebody explains it.
  • Do not close the loop silently. If you correlated deploys and found nothing, say so on the issue — that is a real result and it stops the next person repeating it.

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