data_cleaning
data_cleaning is an Exploratory analysis & notebooks skill for AI agents, published by UCSB-NLP-Chang in the Skill-Usage repository on GitHub. Skillspace rates data_cleaning C (73/100) and it passed the safety scan; the rating is based on static analysis only.
Clean messy tabular datasets with deduplication, missing value imputation, outlier handling, and text processing. Use when dealing with dirty data that has duplicates, nulls, or inconsistent formatting.
- Grade
- C
- Quality
- 73 / 100
- Safety
- Passed
- GitHub stars
- 45
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 97 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 5 other repositories, in 4 collections
Not checked 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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