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SciAgent Skills

197 bioinformatics & life science skills for Claude Code and AI agents — BixBench 92.0% accuracy. RNA-seq, single-cell, drug discovery, proteomics, and more. Powers OmicsHorizon.

Install

$/plugin marketplace add jaechang-hits/SciAgent-Skills

Install command taken from the project's README or registry entry. Always review code before running it.

SciAgent-Skills

Turn your AI coding agent into a life sciences expert — 199 bioinformatics skills for Claude Code covering RNA-seq, single-cell analysis, genomics, proteomics, drug discovery, and more. Boosted BixBench from 65% to 92%. Open source.

SciAgent-Skills is the largest open-source skill library for scientific AI agents. It equips Claude Code (and any markdown-compatible agent) with domain-specific knowledge for computational biology, bioinformatics, cheminformatics, and biostatistics — no fine-tuning required, just plug in and analyze.

Keywords: bioinformatics AI agent, Claude Code skills, scientific computing, RNA-seq analysis, single-cell RNA-seq, drug discovery pipeline, protein structure prediction, computational biology tools, life science automation, BixBench benchmark

Benchmark: 92.0% on BixBench-Verified-50

BixBench is a benchmark for evaluating AI agents on real-world bioinformatics tasks. SciAgent-Skills achieved 92.0% accuracy on BixBench-Verified-50, the highest among all tested systems:

System BixBench-Verified-50 Accuracy
Claude Code (Opus 4.6) + SciAgent-Skills 92.0%
Claude Code (Opus 4.6) baseline 65.3%

Simply equipping Claude Code with these domain-specific skills yields a +26.7 percentage point improvement — no fine-tuning, no custom model, just structured scientific knowledge.

Try It Now — HyperLab

Want to try these skills without any setup? HyperLab (하이퍼랩) is the web platform powered by SciAgent-Skills. Sign up and start analyzing your bioinformatics data directly in your browser — RNA-seq, proteomics, drug screening, and more.


199 ready-to-use scientific skills for AI coding agents — covering genomics, proteomics, drug discovery, biostatistics, scientific computing, and scientific writing.

Each skill is a self-contained SKILL.md file with runnable code examples, key parameters, troubleshooting guides, and best practices. Designed for Claude Code, but compatible with any AI agent that reads markdown skill files (setup guides below).

What's Inside

Category Skills Examples
Genomics & Bioinformatics 65 Scanpy, BioPython, pysam, gget, KEGG, PubMed, scvi-tools, Bakta, Roary
Structural Biology & Drug Discovery 26 RDKit, AutoDock Vina, ChEMBL, PDB, DeepChem, datamol
Scientific Computing 24 Polars, Dask, NetworkX, SymPy, UMAP, PyG, Zarr, SimPy
Cell Biology 15 pydicom, histolab, FlowIO
Biostatistics 12 scikit-learn, statsmodels, PyMC, SHAP, survival analysis
Scientific Writing 21 Manuscript writing, peer review, LaTeX posters, slides, figure guides
Systems Biology & Multi-omics 11 COBRApy, LaminDB, Reactome, STRING
Proteomics & Protein Engineering 10 ESM, UniProt, PyOpenMS, matchms, HMDB
Lab Automation 6 Opentrons, Benchling
Data Visualization 5 Plotly, Seaborn
Molecular Biology 3 CRISPR sgRNA design, gene expression, cloning

Skill types: 72 toolkits, 53 database connectors, 37 guides, 37 pipelines

Installation

Prerequisites

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