Best use case
sensitivity-analysis-toolkit is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Comprehensive sensitivity analysis for optimization
Teams using sensitivity-analysis-toolkit should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/sensitivity-analysis-toolkit/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How sensitivity-analysis-toolkit Compares
| Feature / Agent | sensitivity-analysis-toolkit | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Comprehensive sensitivity analysis for optimization
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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
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