umap-learn
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
Applies UMAP-learn to nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows.
- Package
- 2 files, 49 KB
- SKILL.md
- 2477 words, 12+ sections
- Code
- None. Instructions only.
- License
- BSD-3-Clause license
- Compatibility
- Requires Python 3.9+ and umap-learn; optional HDBSCAN, Matplotlib, and TensorFlow with Keras 3. Network access is needed for installation, not local fitting.
SKILL.md covers: UMAP-Learn · Overview · Quick Start · Installation · Basic Usage · Scale continuous features when their units should carry equal weight · Method 1: Single step (fit and transform) · Method 2: Separate steps (for reusing trained model) · Typical Workflow · 1. Preprocess data · 2. Create and fit UMAP · 3. Visualize
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 21 KB |
references/api_reference.md | doc | 28 KB |
External hosts referenced
github.com umap-learn.readthedocs.io arxiv.org doi.org export.arxiv.org hdbscan.readthedocs.io pypi.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-umap-learn-scan.json
- Badge for your README:
- Request a re-scan