pymoo
No security findings. Scanned 1 time, most recently 2026-10-21.
Second scanner: NVIDIA SkillSpector
SkillSpector found no issues but could not fully inspect the package, usually because SKILL.md refers to a file that is not present, so it fails closed to CAUTION instead of SAFE. Read it as "not fully checked", not as a finding. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Solves and validates single-, multi-, and many-objective optimization with pymoo, including NSGA-II, NSGA-III, MOEA/D, constraints, Pareto approximations, reference directions, and ZDT/DTLZ benchmarks for engineering and research problems.
- Package
- 14 files, 81 KB
- SKILL.md
- 1641 words, 12+ sections
- Code
- Python (5)
- Allowed tools
ReadWriteEditBash- License
- Apache-2.0 license
- Compatibility
- Requires Python 3.10+ and pymoo 0.6.2 with its NumPy, SciPy, matplotlib and autograd dependencies. Optional joblib for parallel runners, optuna for its algorithm wrapper, and dill for checkpoints. Network needed for installation only.
SKILL.md covers: Pymoo - Multi-Objective Optimization in Python · Overview · Installation · When to Use This Skill · Core Concepts · The Unified Interface · Problem Definition Styles · Problem Types · Quick Start Workflows · Algorithm Selection Guide · Single-Objective Problems · Multi-Objective Problems (2-3 objectives)
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 14 KB |
references/algorithms.md | doc | 9.2 KB |
references/constraints_mcdm.md | doc | 9.0 KB |
references/lifecycle.md | doc | 5.2 KB |
references/operators.md | doc | 4.9 KB |
references/parallelization.md | doc | 2.6 KB |
references/problems.md | doc | 7.6 KB |
references/quick_start_workflows.md | doc | 7.3 KB |
references/visualization.md | doc | 4.7 KB |
scripts/custom_problem_example.py | script | 5.0 KB |
scripts/decision_making_example.py | script | 6.0 KB |
scripts/many_objective_example.py | script | 2.3 KB |
scripts/multi_objective_example.py | script | 1.7 KB |
scripts/single_objective_example.py | script | 1.6 KB |
External hosts referenced
pymoo.org arxiv.org doi.org export.arxiv.org
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22 at commit 593377bb0487. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/K-Dense-AI/scientific-agent-skills
- Raw scan result: skills-pymoo-scan.json
- Badge for your README:
- Request a re-scan