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-SkillsInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →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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