sciagent-skills

SciAgent-Skills

Benchmark: 92.0% on BixBench-Verified-50

OmicsHorizon, powered by SciAgent-Skills, achieved 92.0% accuracy on the BixBench-Verified-50 benchmark — outperforming all other systems compared. Notably, Claude Code (Opus 4.6) without skills scores 65.3%, but jumps to 92.0% simply by equipping it with these domain-specific skills (+26.7%p).

---

196 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 agent that reads markdown skill files.

What's Inside

Category	Skills	Examples
Genomics & Bioinformatics	63	Scanpy, BioPython, pysam, gget, KEGG, PubMed, scvi-tools
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, 36 guides, 35 pipelines

Installation

Prerequisites

• Claude Code CLI installed
• Git
• Python 3.12+ (only needed if you want to run validation scripts)

Step 1: Clone the Repository

git clone https://github.com/jaechang-hits/SciAgent-Skills.git
cd SciAgent-Skills

Step 2: Choose Your Setup Method

Method A: Claude Code Plugin (Recommended)

Load SciAgent-Skills as a Claude Code plugin for the current session:

claude --plugin-dir /path/to/SciAgent-Skills

To verify the plugin loaded, run /plugin inside Claude Code and check that sciagent-skills appears in the Installed tab.

Skills become available as /sciagent-skills:<skill-name>:

/sciagent-skills:scanpy-scrna-seq
/sciagent-skills:rdkit-cheminformatics
/sciagent-skills:pymc-bayesian-modeling

Or just describe your task — the agent finds the relevant skill automatically:

"Perform differential expression analysis on this RNA-seq count matrix"

Persistent installation — to load the plugin automatically in every session, use the plugin install command inside Claude Code:

/plugin marketplace add jaechang-hits/SciAgent-Skills
/plugin install sciagent-skills

Method B: Project-Level Integration

Clone into your project directory so Claude Code picks up skills via CLAUDE.md:

cd your-project
git clone https://github.com/jaechang-hits/SciAgent-Skills.git .sciagent-skills

Add to your project's CLAUDE.md:

## Scientific Skills
Reference skills in `.sciagent-skills/skills/` for domain-specific analysis.
Registry: `.sciagent-skills/registry.yaml`

Step 3: Install Dependencies

cd SciAgent-Skills
pixi install

Pixi handles the Python environment and all required packages. If you don't have pixi installed:

curl -fsSL https://pixi.sh/install.sh | bash

How Skills Work

Each skill follows a structured template:

skills/<category>/<skill-name>/
  SKILL.md          # Main skill file (300-550 lines)
  references/       # Optional deep-dive reference files
  assets/           # Optional templates, configs

A SKILL.md contains:

• Frontmatter — name, description, license (for agent discovery)
• Overview & When to Use — what the tool does and when to reach for it
• Prerequisites — packages, data, environment setup
• Quick Start — minimal copy-paste example
• Workflow / Core API — step-by-step pipeline or module-by-module API guide
• Key Parameters — tunable settings with defaults and ranges
• Common Recipes — self-contained snippets for common tasks
• Troubleshooting — problem/cause/solution table

The agent reads only the description field during planning. Full skill content is loaded on demand when relevant.

Directory Structure