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swestfall21swestfall21/claude-skills/reliability-incident-mode/SKILL.md

reliability-incident-mode

Skill0 starsChanged 4 months agoMITView on GitHub

How to respond to incidents and reliability issues with calm, evidence-based action. Use for production problems, outages, and hardening work.

The file

We split this skill into the rules it gives an agent

12 rules. About 0 are common, 12 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈12

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Prefer reversible mitigations over speculative changes.

    line 13
  2. Distinctive:

    Keep the team aligned on what is known, what is unknown, and what is being tried.

    line 15
  3. Distinctive:

    Test the hypothesis before treating it as fact.

    line 21
  4. Distinctive:

    Do not improvise a fix without understanding the failure mode.

    line 22
  5. Distinctive:

    Look for missing safeguards, weak observability, and unclear ownership.

    line 27
  6. Distinctive:

    Treat incident analysis as learning, not blame.

    line 29
  7. Distinctive:

    Do not declare success on intuition alone.

    line 36
  8. Distinctive:

    Add safeguards that reduce the chance of repeat failure.

    line 41
  9. Distinctive:

    Do not guess during an active incident.

    line 47
  10. Distinctive:

    Do not treat mitigation as resolution without verification.

    line 48
  11. Distinctive:

    Do not leave the team without a clear understanding of the current state.

    line 49
  12. Distinctive:

    Do not let the incident end without a learning loop.

    line 50

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Handle incidents and reliability work

Reliability engineering is about calm, disciplined response under pressure. The job is to restore stability, understand the failure, and make the system safer than it was before the incident.

Stabilize first

  • Contain the blast radius as quickly as possible.
  • Prefer reversible mitigations over speculative changes.
  • Preserve evidence of the impact while the situation is still unfolding.
  • Keep the team aligned on what is known, what is unknown, and what is being tried.

Establish facts quickly

  • Gather logs, metrics, traces, and recent change data.
  • Separate observation from inference.
  • Test the hypothesis before treating it as fact.
  • Do not improvise a fix without understanding the failure mode.

Find the root cause

  • Correlate symptoms with deploys, traffic patterns, dependency behavior, and configuration changes.
  • Look for missing safeguards, weak observability, and unclear ownership.
  • Understand the failure mechanism, not just the surface symptom.
  • Treat incident analysis as learning, not blame.

Verify recovery

  • Confirm the system is behaving as intended before declaring progress.
  • Watch for regressions after mitigation.
  • Record what changed, what improved, and what remains uncertain.
  • Do not declare success on intuition alone.

Harden after the incident

  • Improve observability where it was insufficient.
  • Add safeguards that reduce the chance of repeat failure.
  • Turn the incident into a concrete follow-up plan with ownership.
  • Make the fix durable, not cosmetic.

Non-negotiables

  • Do not guess during an active incident.
  • Do not treat mitigation as resolution without verification.
  • Do not leave the team without a clear understanding of the current state.
  • Do not let the incident end without a learning loop.

A strong reliability engineer restores service, learns from the failure, and leaves the system better prepared for the next one.

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