Skillget

SciAgent-Skills

agent
SUMMARY

Life sciences computational skills for scientific AI agents

README.md

SciAgent-Skills

187 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 12 Manuscript writing, peer review, LaTeX posters, slides
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: 39 toolkits, 19 database connectors, 9 guides, 7 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

SciAgent-Skills/
├── .claude-plugin/
│   └── plugin.json        # Claude Code plugin manifest
├── skills/                 # All 187 skills organized by category
│   ├── genomics-bioinformatics/
│   ├── structural-biology-drug-discovery/
│   ├── scientific-computing/
│   ├── cell-biology/
│   ├── biostatistics/
│   ├── scientific-writing/
│   ├── systems-biology-multiomics/
│   ├── proteomics-protein-engineering/
│   ├── lab-automation/
│   ├── data-visualization/
│   └── molecular-biology/
├── templates/              # Skill authoring templates
├── registry.yaml           # Index of all skills
├── CLAUDE.md               # Skill authoring guide
└── scripts/
    └── validate_registry.py

Example Use Cases

Drug Discovery Pipeline

"Search ChEMBL for EGFR inhibitors with IC50 < 100nM, filter with Lipinski rules using RDKit, dock top candidates with AutoDock Vina"

Uses: chembl-database-bioactivity → rdkit-cheminformatics → autodock-vina-docking

Single-Cell RNA-seq Analysis

"Load 10X data, QC filter, normalize, cluster, find marker genes, and annotate cell types"

Uses: anndata-data-structure → scanpy-scrna-seq

Bayesian Biostatistics

"Fit a hierarchical Bayesian model to this clinical trial data with patient-level random effects"

Uses: pymc-bayesian-modeling → matplotlib-scientific-plotting

Protein Structure Analysis

"Get the AlphaFold structure for UniProt P04637, assess confidence, find high-confidence binding regions"

Uses: uniprot-protein-database → alphafold-database-access

Contributing

Adding a New Skill

  1. Read CLAUDE.md for the full authoring workflow
  2. Classify your topic (pipeline / toolkit / database / guide)
  3. Pick a category from the table above
  4. Use the appropriate template from templates/
  5. Add the entry to registry.yaml
  6. Validate: python scripts/validate_registry.py

Skill Templates

Template Use When
SKILL_TEMPLATE.md Linear input→process→output pipeline (e.g., DESeq2)
SKILL_TEMPLATE_TOOLKIT.md Collection of independent modules (e.g., RDKit)
SKILL_TEMPLATE_PROSE.md Conceptual guide, decision frameworks (e.g., statistical test selection)

Requirements

  • Python 3.12+ (for validation scripts)
  • No runtime dependencies — skills are markdown files read by the agent
  • Individual skills list their own tool-specific prerequisites (e.g., pip install scanpy)

License

CC-BY-4.0 for original content. Individual skills note the license of their underlying tools.

Acknowledgments

This project builds on 50+ open-source scientific Python packages. If you find a skill useful, consider starring the underlying tool's repository and supporting its maintainers.

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