Agent skill · Data & Analytics

scikit-bio

Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.

foryourhealth111-pixelgithub.com/foryourhealth111-pixelGitHub ↗
claude-codecodexApache-2.0
Install
npx skills add foryourhealth111-pixel/Vibe-Skills --skill scikit-bio --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 14 KB
Bundled scripts: none
Path: bundled/skills/scikit-bio/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,593
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# scikit-bio ## Overview scikit-bio is a comprehensive Python library for working with biological data. Apply this skill for bioinformatics analyses spanning sequence manipulation, alignment, phylogenetics, microbial ecology, and multivariate statistics. ## When to Use This Skill This skill should be used when the user: - Works with biological sequences (DNA, RNA, protein) - Needs to read/write bi

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About this skill
What does the scikit-bio skill do?

Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.

How do I install it?

Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill scikit-bio --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From foryourhealth111-pixel/Vibe-Skills, a repository with 2,593 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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