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Incident Learning Loop

skill-caiaffa-claude-code-ultimate-engineering-system-incident-learning-loop · by caiaffa

Convert incidents into durable standards, safeguards, templates, and design rules that reduce recurrence across the system.

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Install

$ agentstack add skill-caiaffa-claude-code-ultimate-engineering-system-incident-learning-loop

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

Mission

Ensure every serious incident improves the engineering system, not just the affected service.

When to use

  • Closing a postmortem.
  • Deciding what should become a standard.
  • Updating templates, checklists, or runbooks after incidents.
  • Propagating lessons beyond the local failure.

Handoff

  • Receives from: postmortem-reviewer (after postmortem analysis) or deep-root-cause-investigator.
  • Hands off to: principal-engineer (for standard updates), operational-excellence-enforcer (for runbook/alert updates).

The learning extraction process

For every incident, ask:

  1. What class of failure was this? (not "what happened" but "what category")
  • Examples: missing idempotency, schema migration lock, stale cache read, missing circuit breaker
  1. What invariant was violated? (check against SYSTEM_INVARIANTS.md)
  2. What standard should change? (PROJECTCONVENTIONS.md, DECISIONRULES.md, etc.)
  3. What template or checklist should be updated? (SERVICESCORECARD.md, DEFINITIONOF_DONE.md, etc.)
  4. What other services have this same exposure? (lateral scan)
  5. What review requirement should be added? (new item in code review, ADR review, etc.)

Red flags — learning is too shallow if

  • Lesson stays local to one team or service.
  • Fix applied to code but no standard or process changes.
  • Runbook improved but the design that caused the incident is unchanged.
  • Same class of failure is still possible in 3 other services.
  • Action items are all "add monitoring" without prevention.

Output format

  1. Class of failure (categorized)
  2. Systemic lesson (what the org should learn)
  3. Standards to update (specific files and changes)
  4. Templates/checklists to add or modify (specific)
  5. Other exposed services (lateral risk scan)
  6. Wider rollout plan (how to propagate the fix beyond this service)

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.