networkx
No security findings. Scanned 1 time, most recently 2026-10-21.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Creates, analyzes, and visualizes complex networks and graphs in Python with NetworkX. Use when working with network/graph data structures, computing graph algorithms (shortest paths, centrality, clustering), detecting communities, generating synthetic networks (random, scale-free, small-world), reading/writing graph file formats, or drawing network topologies. Common applications include social, biological, transportation, and citation networks.
- Package
- 7 files, 82 KB
- SKILL.md
- 1855 words, 12+ sections
- Code
- None. Instructions only.
- License
- 3-clause BSD license
- Compatibility
- Requires Python >=3.12 (excluding 3.14.1) and NetworkX 3.7. NumPy, SciPy, pandas and Matplotlib support numerical, tabular and drawing examples; optional integrations need their own packages. No credentials; network needed only for installation or remote data.
SKILL.md covers: NetworkX · Overview · When to Use This Skill · Core Capabilities · 1. Graph Creation and Manipulation · Create empty graph · Add nodes (can be any hashable type) · Add edges · 2. Graph Algorithms · Same distance model for route and length · Degree centrality · Betweenness centrality
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 17 KB |
references/algorithms.md | doc | 13 KB |
references/generators.md | doc | 9.8 KB |
references/graph-basics.md | doc | 7.6 KB |
references/io.md | doc | 15 KB |
references/review.md | doc | 6.1 KB |
references/visualization.md | doc | 14 KB |
External hosts referenced
networkx.org arxiv.org docs.momepy.org docs.scipy.org doi.org export.arxiv.org github.com plotly.com pyvis.readthedocs.io
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-networkx-scan.json
- Badge for your README:
- Request a re-scan