hikaruegashira/agent-skills
Overview
This skill is an autonomous incident-handling meta-skill that drives structured response from initial detection through recovery and post-incident analysis. It reduces impact, shortens mean time to recovery, and embeds repeatable prevention measures. It operationalizes triage, root-cause analysis, phased recovery, and post-mortem documentation.
How this skill works
The skill inspects incident signals and executes a playbook: it visualizes affected components and users, performs layered why-why (root cause) analysis, recommends a recovery strategy (rollback, hotfix, feature-flag, or compatibility layer), and orchestrates phased restoration steps. After recovery it generates a post-mortem with timeline, root cause, detection/mitigation gaps, and prioritized preventive actions, plus an ADR-style decision record.
When to use it
- On production outages or degraded service (SEV1/SEV2)
- When errors or regressions appear after deployments or config changes
- For recurring or unclear failures that need root-cause analysis
- When multiple subsystems interact and failure patterns are composite
- To formalize recovery and capture decisions after incident resolution
Best practices
- Always start by visualizing impact: components, affected users, and severity
- Use layered why-why analysis to drive to a single actionable root cause
- Select recovery strategy based on immediacy and risk (rollback vs hotfix vs compatibility)
- Define phased recovery steps with rollback criteria before making changes
- Document decisions and trade-offs in an ADR-style record immediately after incident
- Run a post-mortem that focuses on system fixes and process improvements, not blame
Example use cases
- API gateway change causes 502s for user endpoints — visualize impact, set SEV, and choose rollback or compatibility layer
- ECS tasks crash on start — perform why-why to reveal network/SG misconfig and restore connectivity
- RDS migration fails — follow phased restore from snapshots, test in staging, and validate metrics before cutover
- Lambda timeouts under load — detect composite pattern (VPC cold start + connection pool exhaustion) and implement proxy/concurrency fixes
- Post-incident, generate ADR noting chosen recovery approach, rationale, residual risks, and assigned follow-ups
FAQ
Pick the strategy that minimizes user impact and risk: prefer rollback for immediate recovery when safe; use hotfix for small well-contained fixes; use compatibility layers for broad client compatibility issues.
How do I know when to roll back versus continue fixes in prod?
Define rollback criteria beforehand: new errors, data integrity issues, or failure to meet recovery milestones should trigger immediate rollback.
7 skills
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