Co-Pilot / 辅助式
更新于 a month ago

claude-scientific-skills

KK-Dense-AI
6.9k
k-dense-ai/claude-scientific-skills
78
Agent 评分

💡 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

生命科学领域的学术研究人员和研究生生物技术/制药领域的数据科学家和生物信息学家临床研究人员和医疗专业人员材料科学和物理领域的工程师和科学家

🤖 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。

安全分析中风险

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

License: MIT 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


🚀 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

  1. Run /plugin in Claude Code
  2. Select Browse and install plugins
  3. Choose claude-scientific-skills marketplace
  4. Select scientific-skills
  5. 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

五维分析
清晰度8/10
创新性6/10
实用性9/10
完整性9/10
可维护性7/10
优缺点分析

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

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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.