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/decompose-global-sensitivity

Estimate global main effects and interactions across uncertain inputs using screening/decomposition methods such as Morris→Sobol or an equivalent supplied method.

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de-anthropocentric-research-engine
499200 skills
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$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill decompose-global-sensitivity --agent claude-code

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  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/decompose-global-sensitivity

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Estimate global main effects and interactions across uncertain inputs using screening/decomposition methods such as Morris→Sobol or an equivalent supplied method.

SKILL.md

decompose-global-sensitivity.SKILL.md
name: decompose-global-sensitivity
description: "Estimate global main effects and interactions across uncertain inputs using screening/decomposition methods such as Morris→Sobol or an equivalent supplied method."

decompose-global-sensitivity

Purpose

Estimate global main effects and interactions across uncertain inputs using screening and decomposition.

Input contract

required: [model, uncertain_inputs, output_metric]
optional: [input_distributions, screening_method, decomposition_method]
constraints: [input distributions and sampling design must be declared]

Procedure

1. Define input ranges/distributions and the output metric. 2. Screen influential variables with Morris or an equivalent declared method. 3. Estimate main and interaction effects with Sobol or an equivalent variance decomposition. 4. Compare sensitivity rankings across sampling assumptions.

Output contract

produces: [screening_report, main_effects, interaction_effects, sensitivity_ranking]
delta_fields: [findings, evidence_updates, uncertainties, decisions]

Quality gates

  • Main and interaction effects use a declared sampling design; rankings include uncertainty and do not conflate screening with decomposition.

Failure and counterexamples

Do not report global sensitivity when ranges are arbitrary, model evaluations are invalid, or interactions were omitted without notice.

Provenance map

  • `deep-insight/variance-decomposition`: resolved.
  • `screening-then-decomposition`: resolved.
  • `morris-screening`: resolved.
  • `sobol-decomposition`: resolved.
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The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.

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