mitigation-validation
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/mitigation-validationValidate that proposed mitigations do not introduce new failure modes — a mini-FMEA on the mitigations themselves.
SKILL.md
.github/skills/mitigation-validationView on GitHub ↗
--- name: mitigation-validation description: "Tactic: Run mini-FMEA on proposed mitigations to verify they do not introduce new failure modes. Prevents mitigation-induced risks." type: tactic used-by: [failure-anticipation] strategies: [design-fmea, process-fmea, mitigation-design] --- # Mitigation Validation Tactic Validate that proposed mitigations do not introduce new failure modes — a mini-FMEA on the mitigations themselves. ## Orchestration 1. Receive proposed mitigation measures from mitigation-design-sop 2. **failure-mode-extraction** identifies potential failure modes of each mitigation: - Could the prevention measure fail? - Could the detection mechanism produce false negatives? - Could the response plan create new problems? 3. **severity-scoring** rates new failure modes 4. If any new mode scores H-priority: - Flag mitigation as risky - **mitigation-design-sop** redesigns or adds safeguards - Re-validate (max 2 iterations to prevent infinite loops) 5. **re-scoring** confirms final S/O/D with validated mitigations ## Iteration Control - Max validation iterations: 2 (prevent infinite recursion) - If still H-priority after 2 iterations: escalate to human review - Document residual risk for accepted mitigations ## Subagents Dispatched - failure-mode-extraction (mitigation failure identification) - severity-scoring (new risk assessment) - mitigation-design-sop (redesign if needed) - re-scoring (final confirmation) ## Termination Conditions - All mitigations validated as not introducing H-priority risks - Max iterations reached (escalate with documentation) - Residual risk accepted and documented