Graph Analysis
v1.0.0Analyze graphs and networks using Python NetworkX — centrality, shortest paths, community detection, and visualization.
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byOwen Ciantar@owenciantar
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description (graph analysis with NetworkX) lines up with the instructions: building graphs, metrics, paths, community detection, visualization. Required tools (python3, pip) in the metadata are reasonable for this purpose.
Instruction Scope
Instructions tell the agent to read user-provided CSV/JSON files and save PNGs — this is expected for a data-analysis skill. The SKILL.md does not instruct reading system credentials or unrelated paths. It does recommend installing packages and inferring source/target columns from user data, so users should be aware the agent will access files the user supplies.
Install Mechanism
This is an instruction-only skill (no install spec), but the README tells operators to run `pip install networkx matplotlib numpy --break-system-packages`. Installing from PyPI is normal for Python tools, but `--break-system-packages` can alter system Python environments and is risky — prefer using a virtual environment. No downloads from arbitrary URLs or archive extraction are present.
Credentials
No environment variables, credentials, or config paths are requested. The skill does not ask for unrelated secrets or broad access tokens.
Persistence & Privilege
Skill is not forced always-on and does not request elevated agent-level persistence or modify other skills. Autonomous invocation is allowed (platform default) but not combined with any broad privileges here.
Assessment
This skill is essentially a how-to for doing graph analysis with NetworkX and appears coherent. Before installing/running: 1) run the pip installs inside a virtualenv or conda environment instead of using `--break-system-packages`; 2) verify the louvain/community function you need is available in your NetworkX version (some setups require an extra community package); 3) be mindful that the skill's examples read user CSV/JSON files and write PNGs — only provide data you want analyzed or shared; 4) the skill metadata declares files (scripts/*) that are not present in the package — that mismatch is benign but worth confirming the repo/source you obtained; 5) if you will run this in an environment with sensitive system data, sandbox the execution and review any concrete code before granting file access.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.
Runtime requirements
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