Scikit Bio

If you're doing microbiome or phylogenetic analysis in Python, this skill gives Claude hands-on access to scikit-bio's core toolkit. It handles the usual sequence operations (DNA/RNA/protein manipulation, FASTA/FASTQ I/O, alignments), but the real strength is in microbial ecology workflows: calculating alpha and beta diversity metrics, UniFrac distances, building phylogenetic trees from distance matrices, and running ordination analyses like PCoA. The pair_align engine replaced the old alignment methods in 0.7.0, so you get modern global/local alignment with configurable gap penalties in one function. Good fit when you need to move beyond basic sequence work into community ecology statistics or when you're already knee-deep in microbiome data and need to calculate diversity metrics or run PERMANOVA tests.

skills.sh installs: 2.1K
GitHub stars: 56.6K
last updated: Aug 21, 2026

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Install

$ npx -y skills add k-dense-ai/scientific-agent-skills --skill scikit-bio --agent claude-code

Installs into .claude/skills of the current project.

Files

scikit-bio

Overview

Targets scikit-bio 0.7.4. Use it for sequence manipulation, alignment, phylogenetics, microbial ecology, and multivariate statistics. Native tests exercise small synthetic fixtures; examples with filenames or undefined inputs are workflow templates. See review evidence and boundaries.

When to Use This Skill

This skill should be used when the user:

Works with biological sequences (DNA, RNA, protein)
Needs to read/write biological file formats (FASTA, FASTQ, GenBank, Newick, BIOM, etc.)
Performs sequence alignments or searches for motifs
Constructs or analyzes phylogenetic trees
Calculates diversity metrics (alpha/beta diversity, UniFrac distances)
Performs ordination analysis (PCoA, CCA, RDA)
Runs statistical tests on biological/ecological data (PERMANOVA, ANOSIM, Mantel)
Analyzes microbiome or community ecology data
Works with protein embeddings from language models
Needs to manipulate biological data tables