Rohoon Six Sigma
v1.8.2Provides professional Six Sigma and Lean quality management support with DMAIC/DMADV, SPC charts, capability indices, MSA, DOE, FMEA, and supplier assessment...
⭐ 1· 48·0 current·0 all-time
byWilliam@williamhyzhu
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The name/description (Six Sigma, SPC, MSA, DOE, AIAG‑VDA reports) match the included Python scripts, references, docs, and examples. Scripts implement control charts, capability, MSA, DOE, PDF/Excel report generation as claimed.
Instruction Scope
SKILL.md instructs the agent to run local Python scripts on user-provided data and to generate reports; it does not request unrelated system files, environment secrets, or network endpoints. Example commands target local files (/tmp and repo scripts).
Install Mechanism
No install spec is present (instruction-only). Code is bundled in the skill; there are no downloads from external URLs or archive extraction steps in the metadata. Dependencies are Python packages listed in requirements.txt.
Credentials
The skill declares no required environment variables, credentials, or config paths. The code uses standard local resources (fonts, /tmp) and Python libraries; nothing requests unrelated secrets.
Persistence & Privilege
The skill is not forced-always-on (always:false) and does not claim to modify other skills or system-wide settings. It will run locally when invoked and writes output files (reports), which is expected for its purpose.
Assessment
This package appears coherent with its stated purpose and does not request credentials or network access. Things to consider before installing: (1) the skill contains many Python scripts that will execute locally and will read/write files (e.g., /tmp, generated reports); run it in a controlled environment if you are unsure. (2) You must install Python dependencies from requirements.txt (numpy, scipy, pandas, reportlab, matplotlib, openpyxl). (3) The repository/source/homepage are not verified in the registry metadata (package.json points to a GitHub URL but the skill's 'source' / 'homepage' fields are empty) — if provenance matters, review the repo upstream or run tests locally (pytest) before use. (4) A few scripts insert specific sys.path entries (e.g., '/Library/Python/3.9/site-packages') or import a local generate_figure12_3 backend; inspect those files/modules to ensure they are the expected implementations. Overall the skill looks consistent and not suspicious, but as with any code bundle, review or sandbox before running on sensitive systems or data.Like a lobster shell, security has layers — review code before you run it.
aiag-vdavk97a5bwx7n5wjnrh60t0catgzs84t3t6automotivevk97a5bwx7n5wjnrh60t0catgzs84t3t6doevk97a5bwx7n5wjnrh60t0catgzs84t3t6latestvk97a5bwx7n5wjnrh60t0catgzs84t3t6leanvk97a5bwx7n5wjnrh60t0catgzs84t3t6manufacturingvk97a5bwx7n5wjnrh60t0catgzs84t3t6msavk97a5bwx7n5wjnrh60t0catgzs84t3t6quality-managementvk97a5bwx7n5wjnrh60t0catgzs84t3t6six-sigmavk97a5bwx7n5wjnrh60t0catgzs84t3t6spcvk97a5bwx7n5wjnrh60t0catgzs84t3t6statistical-analysisvk97a5bwx7n5wjnrh60t0catgzs84t3t6
License
MIT-0
Free to use, modify, and redistribute. No attribution required.