scientific-agent-skills

# Scientific Agent Skills

> **🔔 Claude Scientific Skills is now Scientific Agent Skills.** Same skills, broader compatibility — now works with any AI agent that supports the open [Agent Skills](https://agentskills.io/) standard, not just Claude.

> **New: [K-Dense BYOK](https://github.com/K-Dense-AI/k-dense-byok)** — A free, open-source AI co-scientist that runs on your desktop, powered by Scientific Agent Skills. Bring your own API keys, pick from 40+ models, and get a full research workspace with web search, file handling, 100+ scientific databases, and access to all 133 skills in this repo. Your data stays on your computer, and you can optionally scale to cloud compute via [Modal](https://modal.com/) for heavy workloads. [Get started here.](https://github.com/K-Dense-AI/k-dense-byok)

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE.md)
[![Skills](https://img.shields.io/badge/Skills-133-brightgreen.svg)](#whats-included)
[![Databases](https://img.shields.io/badge/Databases-100%2B-orange.svg)](#whats-included)
[![Agent Skills](https://img.shields.io/badge/Standard-Agent_Skills-blueviolet.svg)](https://agentskills.io/)
[![Works with](https://img.shields.io/badge/Works_with-Cursor_|_Claude_Code_|_Codex-blue.svg)](#getting-started)
[![X](https://img.shields.io/badge/Follow_on_X-%40k__dense__ai-000000?logo=x)](https://x.com/k_dense_ai)
[![LinkedIn](https://img.shields.io/badge/LinkedIn-K--Dense_Inc.-0A66C2?logo=linkedin)](https://www.linkedin.com/company/k-dense-inc)
[![YouTube](https://img.shields.io/badge/YouTube-K--Dense_Inc.-FF0000?logo=youtube)](https://www.youtube.com/@K-Dense-Inc)

A comprehensive collection of **133 ready-to-use scientific and research skills** (covering cancer genomics, drug-target binding, molecular dynamics, RNA velocity, geospatial science, time series forecasting, 78+ scientific databases, and more) for any AI agent that supports the open [Agent Skills](https://agentskills.io/) standard, created by [K-Dense](https://k-dense.ai). Works with **Cursor, Claude Code, Codex, and more**. Transform your AI agent into a research assistant capable of executing complex multi-step scientific workflows across biology, chemistry, medicine, and beyond.

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These skills enable your AI agent to seamlessly work with specialized scientific libraries, databases, and tools across multiple scientific domains. While the agent can use any Python package or API on its own, these explicitly defined skills provide curated documentation and examples that make it significantly stronger and more reliable for the workflows below:
- 🧬 Bioinformatics & Genomics - Sequence analysis, single-cell RNA-seq, gene regulatory networks, variant annotation, phylogenetic analysis
- 🧪 Cheminformatics & Drug Discovery - Molecular property prediction, virtual screening, ADMET analysis, molecular docking, lead optimization
- 🔬 Proteomics & Mass Spectrometry - LC-MS/MS processing, peptide identification, spectral matching, protein quantification
- 🏥 Clinical Research & Precision Medicine - Clinical trials, pharmacogenomics, variant interpretation, drug safety, clinical decision support, treatment planning
- 🧠 Healthcare AI & Clinical ML - EHR analysis, physiological signal processing, medical imaging, clinical prediction models
- 🖼️ Medical Imaging & Digital Pathology - DICOM processing, whole slide image analysis, computational pathology, radiology workflows
- 🤖 Machine Learning & AI - Deep learning, reinforcement learning, time series analysis, model interpretability, Bayesian methods
- 🔮 Materials Science & Chemistry - Crystal structure analysis, phase diagrams, metabolic modeling, computational chemistry
- 🌌 Physics & Astronomy - Astronomical data analysis, coordinate transformations, cosmological calculations, symbolic mathematics, physics computations
- ⚙️ Engineering & Simulation - Discrete-event simulation, multi-objective optimization, metabolic engineering, systems modeling, process optimization
- 📊 Data Analysis & Visualization - Statistical analysis, network analysis, time series, publication-quality figures, large-scale data processing, EDA
- 🌍 Geospatial Science & Remote Sensing - Satellite imagery processing, GIS analysis, spatial statistics, terrain analysis, machine learning for Earth observation
- 🧪 Laboratory Automation - Liquid handling protocols, lab equipment control, workflow automation, LIMS integration
- 📚 Scientific Communication - Literature review, peer review, scientific writing, document processing, posters, slides, schematics, citation management
- 🔬 Multi-omics & Systems Biology - Multi-modal data integration, pathway analysis, network biology, systems-level insights
- 🧬 Protein Engineering & Design - Protein language models, structure prediction, sequence design, function annotation
- 🎓 Research Methodology - Hypothesis generation, scientific brainstorming, critical thinking, grant writing, scholar evaluation

**Transform your AI coding agent into an 'AI Scientist' on your desktop!**

> ⭐ **If you find this repository useful**, please consider giving it a star! It helps others discover these tools and encourages us to continue maintaining and expanding this collection.

> 🎬 **New to Scientific Agent Skills?** Watch our [Getting Started with Scientific Agent Skills](https://youtu.be/ZxbnDaD_FVg) video for a quick walkthrough.

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## 📦 What's Included

This repository provides **133 scientific and research skills** organized into the following categories:

- **100+ Scientific & Financial Databases** - A unified database-lookup skill provides direct access to 78 public databases (PubChem, ChEMBL, UniProt, COSMIC, ClinicalTrials.gov, FRED, USPTO, and more), plus dedicated skills for DepMap, Imaging Data Commons, PrimeKG, and U.S. Treasury Fiscal Data. Multi-database packages like BioServices (~40 bioinformatics services), BioPython (38 NCBI sub-databases via Entrez), and gget (20+ genomics databases) add further coverage
- **70+ Optimized Python Package Skills** - Explicitly defined skills for RDKit, Scanpy, PyTorch Lightning, scikit-learn, BioPython, pyzotero, BioServices, PennyLane, Qiskit, OpenMM, MDAnalysis, scVelo, TimesFM, and others — with curated documentation, examples, and best practices. Note: the agent can write code using *any* Python package, not just these; these skills simply provide stronger, more reliable performance for the packages listed
- **9 Scientific Integration Skills** - Explicitly defined skills for Benchling, DNAnexus, LatchBio, OMERO, Protocols.io, Open Notebook, and more. Again, the agent is not limited to these — any API or platform reachable from Python is fair game; these skills are the optimized, pre-documented paths
- **30+ Analysis & Communication Tools** - Literature review, scientific writing, peer review, document processing, posters, slides, schematics, infographics, Mermaid diagrams, and more
- **10+ Research & Clinical Tools** - Hypothesis generation, grant writing, clinical decision support, treatment plans, regulatory compliance, scenario analysis

Each skill includes:
- ✅ Comprehensive documentation (`SKILL.md`)
- ✅ Practical code examples
- ✅ Use cases and best practices
- ✅ Integration guides
- ✅ Reference materials

---

## 📋 Table of Contents

- [What's Included](#whats-included)
- [Why Use This?](#why-use-this)
- [Getting Started](#getting-started)
- [Security Disclaimer](#-security-disclaimer)
- [Support Open Source](#-support-the-open-source-community)
- [Prerequisites](#prerequisites)
- [Quick Examples](#quick-examples)
- [Use Cases](#use-cases)
- [Available Skills](#available-skills)
- [Contributing](#contributing)
- [Troubleshooting](#troubleshooting)
- [FAQ](#faq)
- [Support](#support)
- [Join Our Community](#join-our-community)
- [Citation](#citation)
- [License](#license)

---

## 🚀 Why Use This?

### ⚡ **Accelerate Your Research**
- **Save Days of Work** - Skip API documentation research and integration setup
- **Production-Ready Code** - Tested, validated examples following scientific best practices
- **Multi-Step Workflows** - Execute complex pipelines with a single prompt

### 🎯 **Comprehensive Coverage**
- **133 Skills** - Extensive coverage across all major scientific domains
- **100+ Databases** - Unified access to 78+ databases via database-lookup, plus dedicated data access skills and multi-database packages like BioServices, BioPython, and gget
- **70+ Optimized Python Package Skills** - RDKit, Scanpy, PyTorch Lightning, scikit-learn, BioServices, PennyLane, Qiskit, OpenMM, scVelo, TimesFM, and others (the agent can use any Python package; these are the pre-documented, higher-performing paths)

### 🔧 **Easy Integration**
- **Simple Setup** - Copy skills to your skills directory and start working
- **Automatic Discovery** - Your agent automatically finds and uses relevant skills
- **Well Documented** - Each skill includes examples, use cases, and best practices

### 🌟 **Maintained & Supported**
- **Regular Updates** - Continuously maintained and expanded by K-Dense team
- **Community Driven** - Open source with active community contributions
- **Enterprise Ready** - Commercial support available for advanced needs

---

## 🎯 Getting Started

Install Scientific Agent Skills with a single command:

```bash
npx skills add K-Dense-AI/scientific-agent-skills
```

This is the official standard approach for installing Agent Skills across **all platforms**, including **Claude Code**, **Claude Cowork**, **Codex**, **Gemini CLI**, **Cursor**, and any other agent that supports the open [Agent Skills](https://agentskills.io/) standard.

**That's it!** Your AI agent will automatically discover the skills and use them when relevant to your scientific tasks. You can also invoke any skill manually by mentioning the skill name in your prompt.

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## ⚠️ Security Disclaimer

> **Skills can execute code and influence your coding agent's behavior. Review what you install.**

Agent Skills are pow