robustness-check

Analyze model robustness via parameter perturbation sensitivity and equilibrium stability.

Updated Jan 26, 2026

Search Tags:#robustness #dynamical-systems #monte-carlo #sensitivity-analysis #tornado-diagram #phase-plane

Ready to run

npx skills add https://github.com/SPIRAL-EDWIN/MCM-ICM-2601000 --skill robustness-check

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: robustness-check
Source: https://github.com/SPIRAL-EDWIN/MCM-ICM-2601000/tree/main/.github/skills/robustness-check
Command: npx skills add https://github.com/SPIRAL-EDWIN/MCM-ICM-2601000 --skill robustness-check

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides systematic robustness analysis for models by evaluating sensitivity to parameter perturbations, stability of equilibria, and reliability under uncertainty.

Core Features & Use Cases

Tornado Diagram: identify parameters with the largest impact on outputs.
Phase Plane Analysis: visualize vector fields, equilibria, and trajectories for dynamical systems.
Monte Carlo Robustness: quantify outcome variability under random parameter perturbations.
Use Case: verify that a climate- or economy-model remains stable when inputs vary within plausible ranges and prepare sensitivity reports for review.

Quick Start

Run robustness_check on your model with a base parameter set to generate sensitivity, phase-plane plots, and robustness statistics; review outputs in results/robustness/.

Frequently Asked Questions about robustness-check

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

FAQPage Schema

How do I perform sensitivity analysis on a dynamical system model?▼

Sensitivity analysis for dynamical systems tests parameter perturbations and equilibrium stability by generating tornado diagrams and phase-plane plots to identify which parameters have the largest impact on model outputs.

What is the best way to check model robustness under parameter uncertainty?▼

Model robustness under parameter uncertainty is checked using Monte Carlo simulations to quantify outcome variability under random parameter perturbations, producing reproducible robustness statistics and reports.

Can I generate tornado diagrams and phase-plane plots for iterative models?▼

You can generate tornado diagrams and phase-plane plots for iterative models to visualize vector fields, equilibria, and trajectories, verifying that outputs remain stable when inputs vary within plausible ranges.

How do I prepare reproducible sensitivity reports for model review?▼

Reproducible sensitivity reports are prepared by running robustness checks on a base parameter set to generate plots and statistics, which can be included directly in methods sections and decision briefs.

Does robustness analysis work for climate and economic models?▼

Robustness analysis applies to climate and economic models by verifying that the model remains stable when inputs vary within plausible ranges and by quantifying outcome variability under random parameter perturbations.