scholar-eda
scholar-eda is an Exploratory analysis & notebooks skill for AI agents, published by joshzyj in the open-scholar-skill repository on GitHub. Skillspace rates scholar-eda D (61/100) and it passed the safety scan; the rating is based on static analysis only.
Conduct exploratory data analysis (EDA) before hypothesis testing. Run when the user has a dataset and needs to load data, build the analytic sample, diagnose missing data, inspect distributions, visualize relationships, check collinearity, and produce a publication-ready Table 1 and pre-analysis memo. Produces figures (PDF/PNG) and tables (HTML/docx/TeX). Saves output to disk. Works after /scholar-data and before /scholar-analyze.
- Grade
- D
- Quality
- 61 / 100
- Safety
- Passed
- GitHub stars
- 102
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
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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