conclusion-sensitivity

$npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/conclusion-sensitivity

Analyzes 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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