# Conclusion Sensitivity

> Map which assumptions are load-bearing by assessing how the conclusion changes if each assumption fails.

- Skill: `yogsoth-ai/conclusion-sensitivity` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add yogsoth-ai/conclusion-sensitivity`
- Raw SKILL.md: https://api.skillmd.com/api/skills/yogsoth-ai/conclusion-sensitivity/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: yogsoth-ai (https://skillmd.com/u/yogsoth-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/yogsoth-ai/conclusion-sensitivity

---


# 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

<!-- BEGIN available-tables (generated) -->

## Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use |
| --- | --- |
| spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |

<!-- END available-tables (generated) -->