Strategy: Design prevention, detection, and response measures for high-priority failure modes. Produces actionable countermeasures validated via re-scoring.
Scanned 5/27/2026
Install via CLI
openskills install yogsoth-ai/de-anthropocentric-research-engine---
name: mitigation-design
description: "Strategy: Design prevention, detection, and response measures for high-priority failure modes. Produces actionable countermeasures validated via re-scoring."
type: strategy
used-by: [failure-anticipation]
tactics: [mitigation-validation]
---
# Mitigation Design Strategy
Design countermeasures for high-priority failure modes across three layers: prevention, detection, response.
## Method
1. **mitigation-design-sop** generates countermeasures for each H-priority failure:
- Prevention: eliminate or reduce occurrence
- Detection: improve ability to detect before impact
- Response: contingency plan if failure occurs
2. **re-scoring** re-evaluates S/O/D with mitigations in place
3. **mitigation-validation** runs mini-FMEA on mitigations themselves
4. Iterate until all H-priority items reach M or L after mitigation
## Budget Table
| Parameter | S | M | L |
|---|---|---|---|
| Mitigations per failure mode | 1 | 2 | 3 |
| Re-scoring rounds | 1 | 2 | 3 |
| Mitigation validation depth | shallow | standard | full FMEA |
## Orchestration
```
[H-priority failures] → mitigation-design-sop
→ re-scoring → action-priority-matrix (re-classify)
→ [still H?] → mitigation-validation → iterate
→ [M or L?] → accept, document residual risk
```
## Subagents
- mitigation-design-sop (countermeasure generation)
- re-scoring (post-mitigation S/O/D)
- action-priority-matrix (re-classification)
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