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Detection Scoring
ASecurityRate detectability 1-10 (inverted: 10 = hardest to detect). Estimates how likely current controls would catch the failure before impact.
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- Added June 1, 2026
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npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill detection-scoring --agent claude-codeAre you the author of Detection Scoring?
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[](https://www.skillsdirectory.com/skills/yogsoth-ai-detection-scoring)---
name: detection-scoring
description: "Rate detectability 1-10 (inverted: 10 = hardest to detect). Estimates how likely current controls would catch the failure before impact."
execution: subagent
prompt: ./prompt.md
input: failure_modes (string), chains (string)
used-by: [failure-anticipation]
---
# Detection Scoring
Rates each failure mode's detectability on an inverted 1-10 scale (10 = hardest to detect).
## Execution
Subagent — spawned via subagent-spawning/spawn-agent.
## Why Subagent
Detection assessment requires reasoning about observability and monitoring independent of severity/occurrence. Isolated context ensures unbiased evaluation.
## Input
- **failure_modes**: Failure mode catalog
- **chains**: Effect chains (to assess where detection could occur)
## Output
- **scores**: List of (failure_mode_id, detection_score, justification)
- **detection_gaps**: Modes with no current detection mechanism
Files in this skill
- SKILL.md
- prompt.md
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