Explore and optimize simulation parameters via design of experiments (DOE), sensitivity analysis, and optimizer selection — generate Latin Hypercube, quasi-random, or factorial sample plans, rank parameter influence with sensitivity scores, recommend Bayesian optimization, CMA-ES, or gradient- based methods based on dimension and budget, and fit surrogate models for expensive evaluations.
安装
npx skills add HeshamFS/materials-simulation-skills --skill parameter-optimizationnpx skills add HeshamFS/materials-simulation-skills --skill parameter-optimization -a claude-code -gnpx skills add HeshamFS/materials-simulation-skills --skill parameter-optimization -a codex -ggemini skills install https://github.com/HeshamFS/materials-simulation-skills.git --path skills/simulation-workflow/parameter-optimizationgh skill install HeshamFS/materials-simulation-skills parameter-optimizationgit clone --depth 1 https://github.com/HeshamFS/materials-simulation-skills /tmp/HeshamFS__materials-simulation-skills
mkdir -p ~/.claude/skills ~/.agents/skills
cp -R /tmp/HeshamFS__materials-simulation-skills/skills/simulation-workflow/parameter-optimization ~/.claude/skills/parameter-optimization # Claude Code
cp -R /tmp/HeshamFS__materials-simulation-skills/skills/simulation-workflow/parameter-optimization ~/.agents/skills/parameter-optimization # Codex, Cursor, Gemini CLI, Copilot, OpenCode