conclusion-sensitivity
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/conclusion-sensitivityAnalyzes which assumptions critically affect conclusions
- Identifies load-bearing assumptions that impact decision outcomes
- Uses subagent execution to isolate and test each assumption
- Evaluates sensitivity by simulating failure of each assumption
- Produces a structured sensitivity map with robustness ratings
SKILL.md
.github/skills/conclusion-sensitivityView on GitHub ↗
--- name: conclusion-sensitivity description: Map which assumptions are load-bearing by assessing how the conclusion changes if each assumption fails. execution: subagent prompt: ./prompt.md input: assumptions[], challenges[] used-by: [steel-manning] --- # Conclusion Sensitivity Maps the relationship between assumptions and conclusions — identifying which assumptions are load-bearing (conclusion changes if they fail) versus decorative (conclusion holds regardless). Produces a sensitivity map for decision-makers. ## Execution Spawns a subagent that takes all extracted assumptions and their challenges, then maps conclusion sensitivity to each. ## Why Subagent - Sensitivity analysis requires holistic view across all assumptions simultaneously - Must consider interaction effects between assumptions - Isolation ensures objective assessment without motivated reasoning ## HARD-GATE Output must include: - Sensitivity rating for every assumption - Identification of critical assumptions (conclusion-changing) - Interaction effects between assumptions - Overall decision robustness rating
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