python-bio-classes

python-bio-classes is a skill for Claude Code, Codex from Pavel-Kravchenko/Bioinformatics. It costs 69 tokens per session (3,399 once invoked), scanned A, original, no licence file.

Python object-oriented patterns for representing genes, DNA, RNA, and proteins as structured records. The records can validate values, compare objects, and parse formats such as FASTA and GFF.

In plain words
What is it for?
Use it to model biological records, create validated sequence classes, parse FASTA or GFF data, and apply inheritance or dataclasses in Python.
Why use it?
Structured objects keep sequence data and its rules together instead of spreading them across separate variables and functions. This can make larger bioinformatics programs easier to maintain.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit Use it to model biological records, create validated sequence classes, parse FASTA or GFF data, and apply inheritance or dataclasses in Python.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/pavel-kravchenko/bioinformatics/python-bio-classes
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 Pavel-Kravchenko/Bioinformatics --skill python-bio-classes
Clone the repo
git clone --depth 1 https://github.com/Pavel-Kravchenko/Bioinformatics

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 python-bio-classes

README.md
[![agentmods](https://agentmods.dev/badge/skills/pavel-kravchenko/bioinformatics/python-bio-classes/github.svg)](https://agentmods.dev/skills/pavel-kravchenko/bioinformatics/python-bio-classes)
Your own site
<a href="https://agentmods.dev/skills/pavel-kravchenko/bioinformatics/python-bio-classes"><img src="https://agentmods.dev/badge/skills/pavel-kravchenko/bioinformatics/python-bio-classes/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 python-bio-classes

Your own site · 80×15
<a href="https://agentmods.dev/skills/pavel-kravchenko/bioinformatics/python-bio-classes"><img src="https://agentmods.dev/badge/skills/pavel-kravchenko/bioinformatics/python-bio-classes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,399 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 unknown No closer match found 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 $0.00069 $0.03399
Opus 5 $0.00034 $0.01699
Sonnet 5 $0.00014 $0.00680
Haiku 4.5 $0.00007 $0.00340

Measured 6d ago against content hash 865acd74bff0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

python-bio-classes 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 6d 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.

Skills/python-bio-classes/SKILL.md · 315 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

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. 6d ago First seen · 315 lines · 69 tokens per session scan A 865acd74bff0

Subscribe to this mod's changes

python-bio-classes is a skill published in the GitHub repository Pavel-Kravchenko/Bioinformatics (5 stars, last pushed 2mo ago), with no licence file. It adds 69 tokens to every session and 3,399 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

astropy

Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.

K-Dense-AI/scientific-agent-skills · 56 tokens

bioservices

Unified Python interface to 40+ bioinformatics services. Use when querying multiple databases (UniProt, KEGG, ChEMBL, Reactome) in a single workflow with consistent API. Best for cross-database analysis, ID mapping across services. For quick single-database lookups use gget; for sequence/file manipulation use…

K-Dense-AI/scientific-agent-skills · 73 tokens

cobrapy

Constraint-based metabolic modeling (COBRA). FBA, FVA, gene knockouts, flux sampling, SBML models, for systems biology and metabolic engineering analysis.

K-Dense-AI/scientific-agent-skills · 38 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

pennylane

Hardware-agnostic quantum ML framework with automatic differentiation. Use when training quantum circuits via gradients, building hybrid quantum-classical models, or needing device portability across IBM/Google/Rigetti/IonQ. Best for variational algorithms (VQE, QAOA), quantum neural networks, and integration with…

K-Dense-AI/scientific-agent-skills · 98 tokens

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