parameter-optimization agent skill by HeshamFS

At a glance

Before you install

Read from the skill's files at the directory's October 19, 2026 snapshot: what ships with it, what its code reads, and the terms it is published under.

• Bundled scripts: 4 script files (4 Python). Your agent may run them, so read them first.
• Tool permissions requested: Read, Write, Grep, Glob (the allowed-tools field of SKILL.md).
• License: Apache-2.0, an open-source or open-content license.

Install parameter-optimization

The skills CLI works with Claude Code, Codex, Cursor and other agents; the other routes copy the folder by hand.

npx skills add https://github.com/HeshamFS/materials-simulation-skills/tree/main/skills/simulation-workflow/parameter-optimization

tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/HeshamFS/materials-simulation-skills.git "$tmp/repo"
mkdir -p .claude/skills
cp -R "$tmp/repo/"skills/simulation-workflow/parameter-optimization .claude/skills/
rm -rf "$tmp"

python3 ~/.codex/skills/.system/skill-installer/scripts/install-skill-from-github.py \
    --repo HeshamFS/materials-simulation-skills \
    --path skills/simulation-workflow/parameter-optimization

HeshamFS/materials-simulation-skills is third-party code. Read SKILL.md and any bundled scripts before you install it.

How the author describes it

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. Use when calibrating material properties against experimental data, planning a parameter sweep, performing uncertainty quantification, or choosing an optimization strategy for a simulation with a limited evaluation budget, even if the user only says "which parameters matter most" or "how do I calibrate my model."

From the description field of SKILL.md. Agents read this line to decide when to load the skill.

Sections in SKILL.md

• Goal
• Requirements
• Inputs to Gather
• Decision Guidance
• Choosing a DOE Method
• Choosing an Optimizer
• Script Outputs (JSON Fields)
• Workflow
• CLI Examples
• Conversational Workflow Example
• Error Handling
• Verification checklist
• Common pitfalls & rationalizations
• Security
• Input Validation
• File Access

Files in the skill folder

• CHANGELOG.md
• SKILL.md
• evals/evals.json
• references/doe_methods.md
• references/optimizer_selection.md
• references/sensitivity_guidelines.md
• references/surrogate_guidelines.md
• scripts/doe_generator.py
• scripts/optimizer_selector.py
• scripts/sensitivity_summary.py
• scripts/surrogate_builder.py

Suede Skill Check: 82/100 · B

parameter-optimization passes the required frontmatter check and all seven graded checks, which cover the SKILL.md format, a declared license and a commit in the last year. Those checks earn 56 of the score’s points; the rest come from description quality, instruction depth, bundled files, maintenance and curated-list citations. How the score works.

Where this skill is cited

HeshamFS/materials-simulation-skills appears in 2 curated lists: BehiSecc/awesome-claude-skills, VoltAgent/awesome-agent-skills.

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