pg_gpu
pg_gpu is a Bioinformatics & life sciences skill for AI agents, published by kr-colab in the pg_gpu repository on GitHub. Skillspace rates pg_gpu F (50/100) and it passed the safety scan; the rating is based on static analysis only.
GPU-accelerated population genetics analysis using the pg_gpu library (https://github.com/kr-colab/pg_gpu). Use this skill whenever the user wants to: load a VCF or zarr file for population genetics analysis, calculate diversity statistics (pi, Tajima's D, theta), run selection scans (iHS, XP-EHH, nSL), compute divergence/FST/dxy between populations, calculate windowed statistics across chromosomes, handle missing data, compute the site frequency spectrum, run PCA or dimensionality reduction, plot windowed stats across chromosomes, panel multiple chromosomes, or run any pg_gpu function. Always use this skill when the user references @vcf, population genetics stats, or pg_gpu commands.
- Grade
- F
- Quality
- 50 / 100
- Safety
- Passed
- GitHub stars
- 30
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
- 68 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- MIT
- Adoption
- Adopted by 0 other repositories, in 0 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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