biopython

biopython is a skill for Claude Code, Codex from foryourhealth111-pixel/Vibe-Skills. It costs 81 tokens per session (3,427 once invoked), scanned A, a copy of biopython, Apache-2.0.

A Python toolkit for biological computing, especially work with DNA, RNA, proteins, structures, and evolutionary relationships. It also reads common biology file formats and connects to databases such as NCBI.

In plain words
What is it for?
Parsing FASTA, FASTQ, GenBank, and structure files, manipulating sequences, running BLAST and alignments, accessing NCBI, and analysing phylogenetic trees.
Why use it?
It provides established tools for common molecular-biology data tasks instead of requiring each operation to be implemented from scratch.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Parsing FASTA, FASTQ, GenBank, and structure files, manipulating sequences, running BLAST and alignments, accessing NCBI, and analysing phylogenetic trees.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/foryourhealth111-pixel/vibe-skills/biopython
About the project

Vibe-Skills is a collection and routing system that helps AI agents discover, select, and coordinate specialized skills for completing tasks. It is intended for agents that need to organize workflows across many installed capabilities. The catalogue entries are skills and an agent belonging to this system.

foryourhealth111-pixel/Vibe-Skills · 3,235 stars · on GitHub

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 foryourhealth111-pixel/Vibe-Skills --skill biopython
Clone the repo
git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills

Made for: Claude Code, Codex.

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 biopython

README.md
[![agentmods](https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/biopython/github.svg)](https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/biopython)
Your own site
<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/biopython"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/biopython/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 biopython

Your own site · 80×15
<a href="https://agentmods.dev/skills/foryourhealth111-pixel/vibe-skills/biopython"><img src="https://agentmods.dev/badge/skills/foryourhealth111-pixel/vibe-skills/biopython.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 81 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,427 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00081 $0.03427
Opus 5 $0.00041 $0.01714
Sonnet 5 $0.00016 $0.00685
Haiku 4.5 $0.00008 $0.00343

Measured 11d ago against content hash b0ee0eb8b344, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

biopython 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 11d 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 biopython — 13 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.

bundled/skills/biopython/SKILL.md · 440 lines

How it starts

The opening of the file, as written. The whole thing — 440 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Biopython: Computational Molecular Biology in Python

Overview

Biopython is a comprehensive set of freely available Python tools for biological computation. It provides functionality for sequence manipulation, file I/O, database access, structural bioinformatics, phylogenetics, and many other bioinformatics tasks. The current version is Biopython 1.85 (released January 2025), which supports Python 3 and requires NumPy.

When to Use This Skill

Use this skill when:

  • Working with biological sequences (DNA, RNA, or protein)
  • Reading, writing, or converting biological file formats (FASTA, GenBank, FASTQ, PDB, mmCIF, etc.)
  • Accessing NCBI databases (GenBank, PubMed, Protein, Gene, etc.) via Entrez
  • Running BLAST searches or parsing BLAST results
  • Performing sequence alignments (pairwise or multiple sequence alignments)
  • Analyzing protein structures from PDB files
  • Creating, manipulating, or visualizing phylogenetic trees
  • Finding sequence motifs or analyzing motif patterns
  • Calculating sequence statistics (GC content, molecular weight, melting temperature, etc.)
  • Performing structural bioinformatics tasks
  • Working with population genetics data
  • Any other computational molecular biology task

Do not use this skill as a catch-all for single-cell analysis, bulk RNA-seq differential expression, biological database evidence tables, protein language model training, metabolic flux modeling, or flow-cytometry file parsing. Those surfaces are either owned by another retained bio-science skill or intentionally no longer exposed as separate bundled route owners.

Core Capabilities

Biopython is organized into modular sub-packages, each addressing specific bioinformatics domains:

  1. Sequence Handling - Bio.Seq and Bio.SeqIO for sequence manipulation and file I/O
  2. Alignment Analysis - Bio.Align and Bio.AlignIO for pairwise and multiple sequence alignments
  3. Database Access - Bio.Entrez for programmatic access to NCBI databases
  4. BLAST Operations - Bio.Blast for running and parsing BLAST searches
  5. Structural Bioinformatics - Bio.PDB for working with 3D protein structures
  6. Phylogenetics - Bio.Phylo for phylogenetic tree manipulation and visualization
  7. Advanced Features - Motifs, population genetics, sequence utilities, and more

Read the full file on GitHub · 440 lines

Files

What ships with it

7 files 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. 11d ago First seen · 440 lines · 81 tokens per session scan A b0ee0eb8b344

Subscribe to this mod's changes

biopython is a skill published in the GitHub repository foryourhealth111-pixel/Vibe-Skills (3,235 stars, last pushed 10d ago), licensed Apache-2.0. It adds 81 tokens to every session and 3,427 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to biopython, differing in 13 lines, and is treated as a copy.

Related

Other skills, from other repositories

data-scientist

Data science across machine learning, statistical modeling, and experimentation. Use when selecting ML algorithms, engineering features, designing A/B tests, evaluating model performance, or building predictive pipelines.

borghei/Claude-Skills · 40 tokens

statistical-analyst

Applied statistics for business and product questions — test selection, assumption checks, power planning, effect sizes with intervals, multiplicity correction. Use when interpreting an experiment, sizing a study, or vetting a claim.

borghei/Claude-Skills · 48 tokens

jupyter-live-kernel

Use a live Jupyter kernel for stateful, iterative Python execution via hamelnb. Load this skill when the task involves exploration, iteration, or inspecting intermediate results — data science, ML experimentation, API exploration, or building up complex code step-by-step. Uses terminal to run CLI commands against a…

braxtonROSE4/zorro-agent · 76 tokens

neuroskill-bci

Connect to a running NeuroSkill instance and incorporate the user's real-time cognitive and emotional state (focus, relaxation, mood, cognitive load, drowsiness, heart rate, HRV, sleep staging, and 40+ derived EXG scores) into responses. Requires a BCI wearable (Muse 2/S or OpenBCI) and the NeuroSkill desktop app…

braxtonROSE4/zorro-agent · 82 tokens

sparse-autoencoder-training

Provides guidance for training and analyzing Sparse Autoencoders (SAEs) using SAELens to decompose neural network activations into interpretable features. Use when discovering interpretable features, analyzing superposition, or studying monosemantic representations in language models.

braxtonROSE4/zorro-agent · 58 tokens

research-paper-writing

End-to-end pipeline for writing ML/AI research papers — from experiment design through analysis, drafting, revision, and submission. Covers NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Integrates automated experiment monitoring, statistical analysis, iterative writing, and citation verification.

braxtonROSE4/zorro-agent · 64 tokens