tooluniverse-statistical-modeling
tooluniverse-statistical-modeling is a Statistical modelling skill for AI agents, published by mims-harvard in the ToolUniverse repository on GitHub. Skillspace rates tooluniverse-statistical-modeling D (67/100) and it passed the safety scan; the rating is based on static analysis only.
Statistical modeling — linear/logistic/ordinal/Poisson regression, ANOVA, Kruskal-Wallis, chi-square, Mann-Whitney, Cox survival, spline fits (R `ns()`), odds ratios, Cohen's d, F-statistic, p-value computation. Specializes in clinical-trial AE analysis (SDTM DM/AE), severity ordinal regression, and per-feature stat workflows.
- Grade
- D
- Quality
- 67 / 100
- Safety
- Passed
- GitHub stars
- 1,566
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 75 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 2 collections
- Scope
- Vendor-specific: built around one product. ToolUniverse plugin; workflow routed through the public tu CLI
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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