gpd-sensitivity-analysis

Rank input parameters by influence using analytical or numerical sensitivity analysis.

1|Updated Mar 29, 2026
One-click install
npx skills add https://github.com/CharlieGreenman/roomtemp-superconductor-gpd --skill gpd-sensitivity-analysis
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: gpd-sensitivity-analysis
Source: https://github.com/CharlieGreenman/roomtemp-superconductor-gpd/tree/main/.agents/skills/gpd-sensitivity-analysis
Command: npx skills add https://github.com/CharlieGreenman/roomtemp-superconductor-gpd --skill gpd-sensitivity-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Sensitivity analysis helps you identify which input parameters most strongly influence a chosen outcome, enabling smarter focus and resource allocation.

Core Features & Use Cases

  • Analytical and numerical sensitivity computation to produce dimensionless coefficients.
  • Parameter ranking, boundary checks, and divergence warnings to guide robust modeling.
  • Automated SENSITIVITY-REPORT generation and seamless updates to project state for transparent uncertainty budgeting.

Quick Start

Run the sensitivity-analysis workflow on your current model to obtain a ranked parameter list and a published report.

Frequently Asked Questions about gpd-sensitivity-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
What is the difference between analytical derivatives and numerical perturbations in sensitivity modeling?

Sensitivity modeling computes dimensionless coefficients either through analytical derivatives for exact mathematical evaluation or numerical perturbations for iterative input adjustment, both yielding ranked parameter lists.

How do I check boundary behavior and flag divergences during parameter ranking?

Parameter ranking includes automated boundary checks and divergence warnings to guide robust modeling, systematically evaluating edge cases and flagging unstable outputs within the sensitivity analysis workflow.

Can I use sensitivity analysis for uncertainty budgeting without external dependencies?

Sensitivity analysis generates automated SENSITIVITY-REPORT files and updates project state without external dependencies, providing structured outputs directly suitable for transparent uncertainty budgeting.

What is the best way to rank model inputs for resource allocation?

Ranking model inputs for resource allocation is best achieved through sensitivity analysis, which computes dimensionless sensitivity coefficients to highlight the parameters that most strongly impact your chosen outcome.