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claude-codescience

Babysitter sensitivity-analysis-toolkit

Comprehensive sensitivity analysis for optimization

install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/science/mathematics/skills/sensitivity-analysis-toolkit" ~/.claude/skills/a5c-ai-babysitter-sensitivity-analysis-toolkit && rm -rf "$T"
manifest: library/specializations/domains/science/mathematics/skills/sensitivity-analysis-toolkit/SKILL.md
tags
#optimization-analysis#mathematical-modeling#parametric-programming#robust-optimization#constraint-analysis
source content

Sensitivity Analysis Toolkit

Purpose

Provides comprehensive sensitivity analysis capabilities for optimization problems to understand solution robustness.

Capabilities

  • Dual variable computation and interpretation
  • Shadow price analysis
  • Parametric programming
  • Binding constraint analysis
  • Post-optimality analysis
  • Robust optimization formulations

Usage Guidelines

  1. Dual Extraction: Obtain dual variables from solvers
  2. Shadow Prices: Interpret marginal values correctly
  3. Parametric Analysis: Study solution changes with parameters
  4. Robustness: Formulate robust counterparts when needed

Tools/Libraries

  • Pyomo
  • JuMP
  • AMPL