sensitivity-analysis
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/sensitivity-analysisIdentify which assumptions are most critical — rank by impact on conclusions.
SKILL.md
.github/skills/sensitivity-analysisView on GitHub ↗
--- name: sensitivity-analysis description: Sensitivity Analysis Campaign — identify which assumptions are most critical by measuring their impact on conclusions. 5 strategies (parameter-screening, variance-decomposition, assumption-criticality, uncertainty-propagation, decision-sensitivity), 3 tactics, 11 subagent SOPs. execution: campaign used-by: deep-insight --- # Sensitivity Analysis Identify which assumptions are most critical — rank by impact on conclusions. ## Design Philosophy This campaign is a strategy book — CC reads, internalizes, and autonomously constructs an approach. ## Strategy Routing | Signal | Strategy | |--------|----------| | 快速筛选、Morris 方法、OAT、初步排除 | → parameter-screening | | 方差分解、Sobol 指数、贡献度、交互效应 | → variance-decomposition | | 假设致命性、扰动、否定、重新推导 | → assumption-criticality | | 不确定性传播、Monte Carlo、分布、贝叶斯 | → uncertainty-propagation | | 决策敏感性、EVPI、影响图、龙卷风图 | → decision-sensitivity | ## Available Tactics - screening-then-decomposition — Morris quick screen then Sobol precise decomposition - assumption-perturbation — one-at-a-time assumption negation and re-derivation - uncertainty-cascade — Monte Carlo propagation through model ## Available SOPs **Import (5):** web-search, web-research, paper-overview, paper-search, paper-research **Subagent (11):** morris-screening, sobol-decomposition, interaction-detection, assumption-extraction, negation-definition, re-derivation, conclusion-sensitivity-measurement, distribution-assignment, monte-carlo-sampling, critical-path-identification, sensitivity-synthesis **Shared (1):** assumption-surfacing ## Context Management context-checkpoint after each strategy completes.
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