scikit-bio

scikit-bio is a skill for Claude Code from dralkh/iktinah. It costs 54 tokens per session (4,766 once invoked), scanned A, a copy of scikit-bio, MIT.

A Python toolkit for biological data, including DNA, RNA, and protein sequences, biological file formats, phylogenetic trees, and microbiome data. It also supports ecological and multivariate statistical analysis.

In plain words
What is it for?
Use it to manipulate and compare sequences, read and write formats such as FASTA and Newick, analyze phylogenetic trees, study microbiomes, and calculate diversity or ordination results.
Why use it?
It brings common bioinformatics and biological-data operations into one Python-based workflow. This reduces the need to handle sequence files, tree data, diversity measures, and related statistics separately.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to manipulate and compare sequences, read and write formats such as FASTA and Newick, analyze phylogenetic trees, study microbiomes, and calculate diversity or ordination results.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dralkh/iktinah/scikit-bio
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add dralkh/iktinah --skill scikit-bio
Clone the repo
git clone --depth 1 https://github.com/dralkh/iktinah

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for scikit-bio

README.md
[![agentmods](https://agentmods.dev/badge/skills/dralkh/iktinah/scikit-bio/github.svg)](https://agentmods.dev/skills/dralkh/iktinah/scikit-bio)
Your own site
<a href="https://agentmods.dev/skills/dralkh/iktinah/scikit-bio"><img src="https://agentmods.dev/badge/skills/dralkh/iktinah/scikit-bio/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for scikit-bio

Your own site · 80×15
<a href="https://agentmods.dev/skills/dralkh/iktinah/scikit-bio"><img src="https://agentmods.dev/badge/skills/dralkh/iktinah/scikit-bio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,766 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 92% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.04766
Opus 5 $0.00027 $0.02383
Sonnet 5 $0.00011 $0.00953
Haiku 4.5 $0.00005 $0.00477

Measured 8d ago against content hash 10a487b002b5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

scikit-bio scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

92% identical to scikit-bio — 20 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/scikit-bio/SKILL.md · 469 lines

How it starts

The opening of the file, as written. The whole thing — 469 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 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

Core Capabilities

1. Sequence Manipulation

Work with biological sequences using specialized classes for DNA, RNA, and protein data.

Key operations:

  • Read/write sequences from FASTA, FASTQ, GenBank, EMBL formats
  • Sequence slicing, concatenation, and searching
  • Reverse complement, transcription (DNA→RNA), and translation (RNA→protein)
  • Find motifs and patterns using regex
  • Calculate distances (Hamming, k-mer based)
  • Handle sequence quality scores and metadata

Common patterns:

import skbio

# Read sequences from file
seq = skbio.DNA.read('input.fasta')

# Sequence operations
rc = seq.reverse_complement()
rna = seq.transcribe()
protein = rna.translate()

# Find motifs
motif_positions = seq.find_with_regex('ATG[ACGT]{3}')

# Check for properties
has_degens = seq.has_degenerates()
seq_no_gaps = seq.degap()

Important notes:

  • Use DNA, RNA, Protein classes for grammared sequences with validation
  • Use Sequence class for generic sequences without alphabet restrictions
  • Quality scores automatically loaded from FASTQ files into positional metadata
  • Metadata types: sequence-level (ID, description), positional (per-base), interval (regions/features)

Read the full file on GitHub · 469 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 469 lines · 54 tokens per session scan A 10a487b002b5

Subscribe to this mod's changes

scikit-bio is a skill published in the GitHub repository dralkh/iktinah (77 stars, last pushed 2mo ago), licensed MIT. It adds 54 tokens to every session and 4,766 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to scikit-bio, differing in 20 lines, and is treated as a copy.

Related

Other skills, from other repositories

biopython

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use…

synthetic-sciences/openscience · 76 tokens

python-math

Small Python utilities for math and text files.

trpc-group/trpc-agent-go · 13 tokens

alterlab-anndata

Build, slice, concatenate, read, and write AnnData annotated data matrices (obs, var, X, layers, obsm, uns) — the scverse data STRUCTURE, not an analysis pipeline. Use when creating or wrangling .h5ad/zarr files, managing cell and gene annotations, concatenating batches, or handling layers/obsm/backed-mode; for the…

AlterLab-IEU/AlterLab-Academic-Skills · 133 tokens

alterlab-rdkit

Provides the RDKit cheminformatics toolkit for low-level, fine-grained molecular primitives — SMILES/SDF parsing, descriptors (MW, LogP, TPSA), fingerprints, substructure/SMARTS search, 2D/3D coordinate generation, similarity, and reaction handling. Use when custom sanitization, specialized fingerprint or descriptor…

AlterLab-IEU/AlterLab-Academic-Skills · 130 tokens

alterlab-sympy

Symbolic mathematics in Python with SymPy — solve equations algebraically, perform calculus (derivatives, integrals, limits), manipulate algebraic expressions, work with symbolic matrices, and generate executable code from formulas. Use when exact symbolic results are needed rather than numerical approximations, or…

AlterLab-IEU/AlterLab-Academic-Skills · 86 tokens

alterlab-cirq

Builds, simulates, and runs quantum circuits with Cirq, Google Quantum AI's framework for NISQ hardware, noise-aware low-level circuit design, and noise characterization. Use when targeting Google Quantum AI processors (Sycamore/Weber), designing noise-aware NISQ circuits, or running characterization experiments…

AlterLab-IEU/AlterLab-Academic-Skills · 135 tokens