pymoo SKILL.md skillA
pymoo from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jaechang-hits/sciagent-skills/pymoo@git:20260428.81ea2d2Pins git:20260428.81ea2d2 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jaechang-hits/sciagent-skills
- Path
skills/scientific-computing/pymoo/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260428.81ea2d2, committed Apr 28, 2026
- First version recorded
- Feb 18, 2026
- Size
- 19,550 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
Python framework for single- and multi-objective optimization with evolutionary algorithms. Define vectorized objectives and constraints; solve with NSGA-II, NSGA-III, MOEA/D, GAs, or differential evolution. Analyze Pareto fronts, visualize trade-offs, customize operators and callbacks. For engineering design, hyperparameter search, and conflicting objectives. Alternatives: scipy.optimize (single-objective, gradient), platypus, jMetalPy (Java).
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# pymoo ## Overview pymoo provides a unified API for multi-objective optimization via population-based evolutionary algorithms. Users define a problem by subclassing `Problem` or `ElementwiseProblem`, specifying objectives (`n_obj`), decision variables (`n_var`), and optional constraints (`n_ieq_constr`). Algorithms like NSGA-II and NSGA-III return a `Result` object containing the Pareto-optimal population, objective values, and decision variable values. pymoo separates problem definition, algorithm configuration, operator selection, and analysis — each component is independently replaceable. ## When to Use - Optimizing a design with two or more conflicting objectives (e.g., minimizing cost while maximizing performance) - Running evolutionary algorithms (GA, DE, PSO) as black-box optimizers when gradients are unavailable - Performing multi-objective hyperparameter search for ML models where accuracy and inference time trade off - Computing Pareto fronts for portfolio optimization or multi-criteria decision analysis - Customizing crossover/mutation operators for domain-specific solution encodings (binary, permutation, real-valued) …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/pymoo@sha256:9c080c6f05a4b970The line at the top of this page pins the label git:20260428.81ea2d2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_dsuiihkhh5ksfulx)
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Versions
The registry has recorded 2 versions of this file, between Feb 18, 2026 and Apr 28, 2026, about one every 69 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260428.81ea2d2 latest | 2026-04-28 | 81ea2d2 | 19,550 B | A | view · diff |
| git:20260218.8df1694 | 2026-02-18 | 8df1694 | 19,717 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (19550 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_dsuiihkhh5ksfulx GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/pymoo GET https://markdownregistry.com/api/v1/blob/9c080c6f05a4b9702be6337b3b649a06d8d6ed2011cdfae0d24b199b1d072959
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.
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