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scientific-pkg-pymoo

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Packaged view

This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.

Stars
10
Hot score
84
Updated
March 20, 2026
Overall rating
C4.0
Composite score
4.0
Best-practice grade
B70.4

Install command

npx @skill-hub/cli install jackspace-claudeskillz-scientific-pkg-pymoo

Repository

jackspace/ClaudeSkillz

Skill path: skills/scientific-pkg-pymoo

Multi-objective optimization framework. NSGA-II, NSGA-III, MOEA/D, Pareto fronts, constraint handling, benchmarks (ZDT, DTLZ), for engineering design and optimization problems.

Open repository

Best for

Primary workflow: Design Product.

Technical facets: Full Stack, Designer.

Target audience: Development teams looking for install-ready agent workflows..

License: Unknown.

Original source

Catalog source: SkillHub Club.

Repository owner: jackspace.

This is still a mirrored public skill entry. Review the repository before installing into production workflows.

What it helps with

  • Install scientific-pkg-pymoo into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
  • Review https://github.com/jackspace/ClaudeSkillz before adding scientific-pkg-pymoo to shared team environments
  • Use scientific-pkg-pymoo for development workflows

Works across

Claude CodeCodex CLIGemini CLIOpenCode

Favorites: 0.

Sub-skills: 0.

Aggregator: No.

scientific-pkg-pymoo | SkillHub