claude-scientific-skills
💡 摘要
一个包含 140 个预构建技能的集合,使 Claude AI 能够跨生物学、化学、医学和其他研究领域执行复杂的科学工作流程。
🎯 适合人群
🤖 AI 吐槽: “这是一个庞大且令人印象深刻的科学工具集合,但阅读 README 的感觉就像在每个环节都被推销升级到高级版本。”
该技能集合集成了大量外部科学数据库(OpenAlex、PubMed、ChEMBL)和 Python 包,为依赖供应链攻击创造了广泛的攻击面。执行科学模拟或数据处理的代码可能消耗大量本地资源。缓解措施:为技能执行实施沙盒环境,并使用完整性检查的依赖项锁定。
Claude Scientific Skills
A comprehensive collection of 140 ready-to-use scientific skills for Claude, created by K-Dense. Transform Claude into your AI research assistant capable of executing complex multi-step scientific workflows across biology, chemistry, medicine, and beyond.
Looking for the full AI co-scientist experience? Try K-Dense Web for 200+ skills, cloud compute, and publication-ready outputs.
K-Dense Web - The Full Experience
Want 10x the power with zero setup? K-Dense Web is the complete AI co-scientist platform—everything in this repo, plus:
| Feature | This Repo | K-Dense Web | |---------|-----------|-------------| | Scientific Skills | 140 skills | 200+ skills (exclusive access) | | Setup Required | Manual installation | Zero setup — works instantly | | Compute | Your machine | Cloud GPUs & HPC included | | Workflows | Basic prompts | End-to-end research pipelines | | Outputs | Code & analysis | Publication-ready figures, reports & papers | | Integrations | Local tools | Lab systems, ELNs, cloud storage |
Researchers at Stanford, MIT, and leading pharma companies use K-Dense Web to accelerate discoveries.
Get $50 in free credits — no credit card required.
Learn more at k-dense.ai | Read our detailed comparison →
These skills enable Claude to seamlessly work with specialized scientific libraries, databases, and tools across multiple scientific domains:
- 🧬 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
- 🧪 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 Claude Code 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.
📦 What's Included
This repository provides 140 scientific skills organized into the following categories:
- 28+ Scientific Databases - Direct API access to OpenAlex, PubMed, bioRxiv, ChEMBL, UniProt, COSMIC, ClinicalTrials.gov, and more
- 55+ Python Packages - RDKit, Scanpy, PyTorch Lightning, scikit-learn, BioPython, BioServices, PennyLane, Qiskit, and others
- 15+ Scientific Integrations - Benchling, DNAnexus, LatchBio, OMERO, Protocols.io, and more
- 30+ Analysis & Communication Tools - Literature review, scientific writing, peer review, document processing, posters, slides, schematics, and more
- 10+ Research & Clinical Tools - Hypothesis generation, grant writing, clinical decision support, treatment plans, regulatory compliance
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
- Why Use This?
- Getting Started
- Support Open Source
- Prerequisites
- Quick Examples
- Use Cases
- Available Skills
- Contributing
- Troubleshooting
- FAQ
- Support
- Join Our Community
- Citation
- 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
- 140 Skills - Extensive coverage across all major scientific domains
- 28+ Databases - Direct access to OpenAlex, PubMed, bioRxiv, ChEMBL, UniProt, COSMIC, and more
- 55+ Python Packages - RDKit, Scanpy, PyTorch Lightning, scikit-learn, BioServices, PennyLane, Qiskit, and others
🔧 Easy Integration
- One-Click Setup - Install via Claude Code or MCP server
- Automatic Discovery - Claude 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
Choose your preferred platform to get started:
🖥️ Claude Code (Recommended)
📚 New to Claude Code? Check out the Claude Code Quickstart Guide to get started. When using Claude Code please use the Skills as a plugin. Do not use the MCP server below.
Step 1: Install Claude Code
macOS:
curl -fsSL https://claude.ai/install.sh | bash
Windows:
irm https://claude.ai/install.ps1 | iex
Step 2: Register the Marketplace
In Claude Code, run the following command:
/plugin marketplace add K-Dense-AI/claude-scientific-skills
Step 3: Install the Plugin
Option A: Direct Install (Fastest)
/plugin install scientific-skills@claude-scientific-skills
Option B: Interactive Install
- Run
/pluginin Claude Code - Select Browse and install plugins
- Choose claude-scientific-skills marketplace
- Select scientific-skills
- Click Install now
That's it! Claude will automatically use the appropriate skills when you describe your scientific tasks.
Managing Your Plugin:
# Check installed plugins /plugin → Manage Plugins # Update the plugin to the latest version /plugin update scientific-skills@claude-scientific-skills # Enable/disable the plugin /plugin enable scientific-skills@claude-scientific-skills /plugin disable scientific-skills@claude-scientific-skills # Uninstall if needed /plugin uninstall scientific-skills@claude-scientific-skills
⌨️ Cursor IDE
One-click installation via our hosted MCP server:
🔌 Any MCP Client (Not for Claude Code)
Access all skills via our MCP server in any MCP-compatible client (ChatGPT, Google ADK, OpenAI Agent SDK, etc.):
**Option 1: Hosted MCP Server
优点
- 涵盖许多科学领域的 140 项技能,覆盖范围广泛
- 为 Claude Code 和其他 MCP 客户端提供了清晰的集成路径
- 文档结构良好,每个技能都有实用示例
缺点
- README 中大力推广付费的 K-Dense Web 平台
- 管理 140 个独立技能及其依赖项的复杂性
- 根据调用的技能,可能存在高资源使用率
相关技能
免责声明:本内容来源于 GitHub 开源项目,仅供展示和评分分析使用。
版权归原作者所有 K-Dense-AI.
