exploratory-data-analysis
exploratory-data-analysis is an Exploratory analysis & notebooks skill for AI agents, published by K-Dense-AI in the scientific-agent-skills repository on GitHub. Skillspace rates exploratory-data-analysis D (68/100) and it passed the safety scan; a judge model has also reviewed it.
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain formats are reference-only and unknown formats fail closed.
- Grade
- D
- Quality
- 68 / 100
- Safety
- Passed
- GitHub stars
- 44,723
Placed #1 of 6 in the judged category final for Exploratory analysis & notebooks.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- Low-risk patterns
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #1 of 6 in the judged category final for Exploratory analysis & notebooks.
- Trigger
78 78 - Instructions
88 88 - Specificity
92 92 - Safety
97 97 - Disclosure
88 88 - Maintenance
90 90
Best-in-class safety and maintenance: dated pinned dependencies, a fail-closed capability matrix, and explicit prohibitions on pickle/eval/network access.
What the scanner flagged
- mentions secrets in text
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- 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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