A comprehensive collection of 146+ ready-to-use scientific and research skills (now including financial/SEC research, U.S. Treasury fiscal data, OFR Hedge Fund Monitor, and Alpha Vantage market data) for any AI agent that supports the open Agent Skills standard, created by K-Dense. Works with Cursor, Claude Code, Codex, and more. Transform your AI agent into a research assistant capable of executi
Add this skill
npx mdskills install K-Dense-AI/claude-scientific-skillsProvides no actionable instructions or concrete capabilities for scientific work
A comprehensive collection of 146+ ready-to-use scientific and research skills (now including financial/SEC research, U.S. Treasury fiscal data, OFR Hedge Fund Monitor, and Alpha Vantage market data) for any AI agent that supports the open Agent Skills standard, created by K-Dense. 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.
Looking for the full AI co-scientist experience? Try K-Dense Web for 200+ skills, cloud compute, and publication-ready outputs.
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 your AI agent to seamlessly work with specialized scientific libraries, databases, and tools across multiple scientific domains:
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 Claude Scientific Skills? Watch our Getting Started with Claude Scientific Skills video for a quick walkthrough.
This repository provides 146 scientific and research skills organized into the following categories:
Each skill includes:
SKILL.md)Claude Scientific Skills follows the open Agent Skills standard. Simply copy the skill folders into your skills directory and your AI agent will automatically discover and use them.
git clone https://github.com/K-Dense-AI/claude-scientific-skills.git
Copy the individual skill folders from scientific-skills/ to one of the supported skill directories below. You can install skills globally (available across all projects) or per-project (available only in that project).
Global installation (recommended — skills available everywhere):
| Tool | Directory |
|---|---|
| Cursor | ~/.cursor/skills/ |
| Claude Code | ~/.claude/skills/ |
| Codex | ~/.codex/skills/ |
Project-level installation (skills scoped to a single project):
| Tool | Directory |
|---|---|
| Cursor | .cursor/skills/ (in your project root) |
| Claude Code | .claude/skills/ (in your project root) |
| Codex | .codex/skills/ (in your project root) |
Note: Cursor also reads from
.claude/skills/and.codex/skills/directories, and vice versa, so skills are cross-compatible between tools.
Example — global install for Cursor:
cp -r claude-scientific-skills/scientific-skills/* ~/.cursor/skills/
Example — global install for Claude Code:
cp -r claude-scientific-skills/scientific-skills/* ~/.claude/skills/
Example — project-level install:
mkdir -p .cursor/skills
cp -r /path/to/claude-scientific-skills/scientific-skills/* .cursor/skills/
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.
Claude Scientific Skills is powered by 50+ incredible open source projects maintained by dedicated developers and research communities worldwide. Projects like Biopython, Scanpy, RDKit, scikit-learn, PyTorch Lightning, and many others form the foundation of these skills.
If you find value in this repository, please consider supporting the projects that make it possible:
👉 View the full list of projects to support
SKILL.md files for specific requirements)The skills use uv as the package manager for installing Python dependencies. Install it using the instructions for your operating system:
macOS and Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows:
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Alternative (via pip):
pip install uv
After installation, verify it works by running:
uv --version
For more installation options and details, visit the official uv documentation.
Once you've installed the skills, you can ask your AI agent to execute complex multi-step scientific workflows. Here are some example prompts:
Goal: Find novel EGFR inhibitors for lung cancer treatment
Prompt:
Use available skills you have access to whenever possible. Query ChEMBL for EGFR inhibitors (IC50 📖 **Want more examples?** Check out [docs/examples.md](docs/examples.md) for comprehensive workflow examples and detailed use cases across all scientific domains.
---
## 🔬 Use Cases
### 🧪 Drug Discovery & Medicinal Chemistry
- **Virtual Screening**: Screen millions of compounds from PubChem/ZINC against protein targets
- **Lead Optimization**: Analyze structure-activity relationships with RDKit, generate analogs with datamol
- **ADMET Prediction**: Predict absorption, distribution, metabolism, excretion, and toxicity with DeepChem
- **Molecular Docking**: Predict binding poses and affinities with DiffDock
- **Bioactivity Mining**: Query ChEMBL for known inhibitors and analyze SAR patterns
### 🧬 Bioinformatics & Genomics
- **Sequence Analysis**: Process DNA/RNA/protein sequences with BioPython and pysam
- **Single-Cell Analysis**: Analyze 10X Genomics data with Scanpy, identify cell types, infer GRNs with Arboreto
- **Variant Annotation**: Annotate VCF files with Ensembl VEP, query ClinVar for pathogenicity
- **Gene Discovery**: Query NCBI Gene, UniProt, and Ensembl for comprehensive gene information
- **Network Analysis**: Identify protein-protein interactions via STRING, map to pathways (KEGG, Reactome)
### 🏥 Clinical Research & Precision Medicine
- **Clinical Trials**: Search ClinicalTrials.gov for relevant studies, analyze eligibility criteria
- **Variant Interpretation**: Annotate variants with ClinVar, COSMIC, and ClinPGx for pharmacogenomics
- **Drug Safety**: Query FDA databases for adverse events, drug interactions, and recalls
- **Precision Therapeutics**: Match patient variants to targeted therapies and clinical trials
### 🔬 Multi-Omics & Systems Biology
- **Multi-Omics Integration**: Combine RNA-seq, proteomics, and metabolomics data
- **Pathway Analysis**: Enrich differentially expressed genes in KEGG/Reactome pathways
- **Network Biology**: Reconstruct gene regulatory networks, identify hub genes
- **Biomarker Discovery**: Integrate multi-omics layers to predict patient outcomes
### 📊 Data Analysis & Visualization
- **Statistical Analysis**: Perform hypothesis testing, power analysis, and experimental design
- **Publication Figures**: Create publication-quality visualizations with matplotlib and seaborn
- **Network Visualization**: Visualize biological networks with NetworkX
- **Report Generation**: Generate comprehensive PDF reports with Document Skills
### 🧪 Laboratory Automation
- **Protocol Design**: Create Opentrons protocols for automated liquid handling
- **LIMS Integration**: Integrate with Benchling and LabArchives for data management
- **Workflow Automation**: Automate multi-step laboratory workflows
---
## 📚 Available Skills
This repository contains **143 scientific and research skills** organized across multiple domains. Each skill provides comprehensive documentation, code examples, and best practices for working with scientific libraries, databases, and tools.
### Skill Categories
#### 🧬 **Bioinformatics & Genomics** (16+ skills)
- Sequence analysis: BioPython, pysam, scikit-bio, BioServices
- Single-cell analysis: Scanpy, AnnData, scvi-tools, Arboreto, Cellxgene Census
- Genomic tools: gget, geniml, gtars, deepTools, FlowIO, Zarr
- Phylogenetics: ETE Toolkit
#### 🧪 **Cheminformatics & Drug Discovery** (11+ skills)
- Molecular manipulation: RDKit, Datamol, Molfeat
- Deep learning: DeepChem, TorchDrug
- Docking & screening: DiffDock
- Cloud quantum chemistry: Rowan (pKa, docking, cofolding)
- Drug-likeness: MedChem
- Benchmarks: PyTDC
#### 🔬 **Proteomics & Mass Spectrometry** (2 skills)
- Spectral processing: matchms, pyOpenMS
#### 🏥 **Clinical Research & Precision Medicine** (12+ skills)
- Clinical databases: ClinicalTrials.gov, ClinVar, ClinPGx, COSMIC, FDA Databases
- Healthcare AI: PyHealth, NeuroKit2, Clinical Decision Support
- Clinical documentation: Clinical Reports, Treatment Plans
- Variant analysis: Ensembl, NCBI Gene
#### 🖼️ **Medical Imaging & Digital Pathology** (3 skills)
- DICOM processing: pydicom
- Whole slide imaging: histolab, PathML
#### 🧠 **Neuroscience & Electrophysiology** (1 skill)
- Neural recordings: Neuropixels-Analysis (extracellular spikes, silicon probes, spike sorting)
#### 🤖 **Machine Learning & AI** (15+ skills)
- Deep learning: PyTorch Lightning, Transformers, Stable Baselines3, PufferLib
- Classical ML: scikit-learn, scikit-survival, SHAP
- Time series: aeon
- Bayesian methods: PyMC
- Optimization: PyMOO
- Graph ML: Torch Geometric
- Dimensionality reduction: UMAP-learn
- Statistical modeling: statsmodels
#### 🔮 **Materials Science, Chemistry & Physics** (7 skills)
- Materials: Pymatgen
- Metabolic modeling: COBRApy
- Astronomy: Astropy
- Quantum computing: Cirq, PennyLane, Qiskit, QuTiP
#### ⚙️ **Engineering & Simulation** (4 skills)
- Numerical computing: MATLAB/Octave
- Computational fluid dynamics: FluidSim
- Discrete-event simulation: SimPy
- Data processing: Dask, Polars, Vaex
#### 📊 **Data Analysis & Visualization** (14+ skills)
- Visualization: Matplotlib, Seaborn, Plotly, Scientific Visualization
- Geospatial analysis: GeoPandas
- Network analysis: NetworkX
- Symbolic math: SymPy
- Document processing: Document Skills (PDF, DOCX, PPTX, XLSX)
- Data access: Data Commons
- Exploratory data analysis: EDA workflows
- Statistical analysis: Statistical Analysis workflows
#### 🧪 **Laboratory Automation** (3 skills)
- Liquid handling: PyLabRobot
- Protocol management: Protocols.io
- LIMS integration: Benchling, LabArchives
#### 🔬 **Multi-omics & Systems Biology** (5+ skills)
- Pathway analysis: KEGG, Reactome, STRING
- Multi-omics: Denario, HypoGeniC
- Data management: LaminDB
#### 🧬 **Protein Engineering & Design** (2 skills)
- Protein language models: ESM
- Cloud laboratory platform: Adaptyv (automated protein testing and validation)
#### 📚 **Scientific Communication** (20+ skills)
- Literature: OpenAlex, PubMed, bioRxiv, Literature Review
- Web search: Perplexity Search (AI-powered search with real-time information)
- Writing: Scientific Writing, Peer Review
- Document processing: XLSX, MarkItDown, Document Skills
- Publishing: Paper-2-Web, Venue Templates
- Presentations: Scientific Slides, LaTeX Posters, PPTX Posters
- Diagrams: Scientific Schematics
- Citations: Citation Management
- Illustration: Generate Image (AI image generation with FLUX.2 Pro and Gemini 3 Pro (Nano Banana Pro))
#### 🔬 **Scientific Databases** (28+ skills)
- Protein: UniProt, PDB, AlphaFold DB
- Chemical: PubChem, ChEMBL, DrugBank, ZINC, HMDB
- Genomic: Ensembl, NCBI Gene, GEO, ENA, GWAS Catalog
- Literature: bioRxiv (preprints)
- Clinical: ClinVar, COSMIC, ClinicalTrials.gov, ClinPGx, FDA Databases
- Pathways: KEGG, Reactome, STRING
- Targets: Open Targets
- Metabolomics: Metabolomics Workbench
- Enzymes: BRENDA
- Patents: USPTO
#### 🔧 **Infrastructure & Platforms** (6+ skills)
- Cloud compute: Modal
- Genomics platforms: DNAnexus, LatchBio
- Microscopy: OMERO
- Automation: Opentrons
- Resource detection: Get Available Resources
#### 🎓 **Research Methodology & Planning** (8+ skills)
- Ideation: Scientific Brainstorming, Hypothesis Generation
- Critical analysis: Scientific Critical Thinking, Scholar Evaluation
- Funding: Research Grants
- Discovery: Research Lookup
- Market analysis: Market Research Reports
#### ⚖️ **Regulatory & Standards** (1 skill)
- Medical device standards: ISO 13485 Certification
#### 💹 **Financial & SEC Research** (4 skills)
- SEC filings & financial data: edgartools (10-K, 10-Q, 8-K, 13F, Form 4, XBRL, insider trading, institutional holdings)
- U.S. federal fiscal data: usfiscaldata (national debt, Daily/Monthly Treasury Statements, Treasury auctions, interest rates, exchange rates, savings bonds)
- Hedge fund systemic risk: hedgefundmonitor (OFR Hedge Fund Monitor API — Form PF aggregated stats, CFTC futures positioning, FICC sponsored repo, SCOOS dealer financing)
- Global market data: alpha-vantage (real-time & historical stocks, options, forex, crypto, commodities, economic indicators, 50+ technical indicators via Alpha Vantage API)
> 📖 **For complete details on all skills**, see [docs/scientific-skills.md](docs/scientific-skills.md)
> 💡 **Looking for practical examples?** Check out [docs/examples.md](docs/examples.md) for comprehensive workflow examples across all scientific domains.
---
## 🤝 Contributing
We welcome contributions to expand and improve this scientific skills repository!
### Ways to Contribute
✨ **Add New Skills**
- Create skills for additional scientific packages or databases
- Add integrations for scientific platforms and tools
📚 **Improve Existing Skills**
- Enhance documentation with more examples and use cases
- Add new workflows and reference materials
- Improve code examples and scripts
- Fix bugs or update outdated information
🐛 **Report Issues**
- Submit bug reports with detailed reproduction steps
- Suggest improvements or new features
### How to Contribute
1. **Fork** the repository
2. **Create** a feature branch (`git checkout -b feature/amazing-skill`)
3. **Follow** the existing directory structure and documentation patterns
4. **Ensure** all new skills include comprehensive `SKILL.md` files
5. **Test** your examples and workflows thoroughly
6. **Commit** your changes (`git commit -m 'Add amazing skill'`)
7. **Push** to your branch (`git push origin feature/amazing-skill`)
8. **Submit** a pull request with a clear description of your changes
### Contribution Guidelines
✅ **Adhere to the [Agent Skills Specification](https://agentskills.io/specification)** — Every skill must follow the official spec (valid `SKILL.md` frontmatter, naming conventions, directory structure)
✅ Maintain consistency with existing skill documentation format
✅ Ensure all code examples are tested and functional
✅ Follow scientific best practices in examples and workflows
✅ Update relevant documentation when adding new capabilities
✅ Provide clear comments and docstrings in code
✅ Include references to official documentation
### Recognition
Contributors are recognized in our community and may be featured in:
- Repository contributors list
- Special mentions in release notes
- K-Dense community highlights
Your contributions help make scientific computing more accessible and enable researchers to leverage AI tools more effectively!
### Support Open Source
This project builds on 50+ amazing open source projects. If you find value in these skills, please consider [supporting the projects we depend on](docs/open-source-sponsors.md).
---
## 🔧 Troubleshooting
### Common Issues
**Problem: Skills not loading**
- Verify skill folders are in the correct directory (see [Getting Started](#getting-started))
- Each skill folder must contain a `SKILL.md` file
- Restart your agent/IDE after copying skills
- In Cursor, check Settings → Rules to confirm skills are discovered
**Problem: Missing Python dependencies**
- Solution: Check the specific `SKILL.md` file for required packages
- Install dependencies: `uv pip install package-name`
**Problem: API rate limits**
- Solution: Many databases have rate limits. Review the specific database documentation
- Consider implementing caching or batch requests
**Problem: Authentication errors**
- Solution: Some services require API keys. Check the `SKILL.md` for authentication setup
- Verify your credentials and permissions
**Problem: Outdated examples**
- Solution: Report the issue via GitHub Issues
- Check the official package documentation for updated syntax
---
## ❓ FAQ
### General Questions
**Q: Is this free to use?**
A: Yes! This repository is MIT licensed. However, each individual skill has its own license specified in the `license` metadata field within its `SKILL.md` file—be sure to review and comply with those terms.
**Q: Why are all skills grouped together instead of separate packages?**
A: We believe good science in the age of AI is inherently interdisciplinary. Bundling all skills together makes it trivial for you (and your agent) to bridge across fields—e.g., combining genomics, cheminformatics, clinical data, and machine learning in one workflow—without worrying about which individual skills to install or wire together.
**Q: Can I use this for commercial projects?**
A: The repository itself is MIT licensed, which allows commercial use. However, individual skills may have different licenses—check the `license` field in each skill's `SKILL.md` file to ensure compliance with your intended use.
**Q: Do all skills have the same license?**
A: No. Each skill has its own license specified in the `license` metadata field within its `SKILL.md` file. These licenses may differ from the repository's MIT License. Users are responsible for reviewing and adhering to the license terms of each individual skill they use.
**Q: How often is this updated?**
A: We regularly update skills to reflect the latest versions of packages and APIs. Major updates are announced in release notes.
**Q: Can I use this with other AI models?**
A: The skills follow the open [Agent Skills](https://agentskills.io/) standard and work with any compatible agent, including Cursor, Claude Code, and Codex.
### Installation & Setup
**Q: Do I need all the Python packages installed?**
A: No! Only install the packages you need. Each skill specifies its requirements in its `SKILL.md` file.
**Q: What if a skill doesn't work?**
A: First check the [Troubleshooting](#troubleshooting) section. If the issue persists, file an issue on GitHub with detailed reproduction steps.
**Q: Do the skills work offline?**
A: Database skills require internet access to query APIs. Package skills work offline once Python dependencies are installed.
### Contributing
**Q: Can I contribute my own skills?**
A: Absolutely! We welcome contributions. See the [Contributing](#contributing) section for guidelines and best practices.
**Q: How do I report bugs or suggest features?**
A: Open an issue on GitHub with a clear description. For bugs, include reproduction steps and expected vs actual behavior.
---
## 💬 Support
Need help? Here's how to get support:
- 📖 **Documentation**: Check the relevant `SKILL.md` and `references/` folders
- 🐛 **Bug Reports**: [Open an issue](https://github.com/K-Dense-AI/claude-scientific-skills/issues)
- 💡 **Feature Requests**: [Submit a feature request](https://github.com/K-Dense-AI/claude-scientific-skills/issues/new)
- 💼 **Enterprise Support**: Contact [K-Dense](https://k-dense.ai/) for commercial support
- 🌐 **Community**: [Join our Slack](https://join.slack.com/t/k-densecommunity/shared_invite/zt-3iajtyls1-EwmkwIZk0g_o74311Tkf5g)
---
## 🎉 Join Our Community!
**We'd love to have you join us!** 🚀
Connect with other scientists, researchers, and AI enthusiasts using AI agents for scientific computing. Share your discoveries, ask questions, get help with your projects, and collaborate with the community!
🌟 **[Join our Slack Community](https://join.slack.com/t/k-densecommunity/shared_invite/zt-3iajtyls1-EwmkwIZk0g_o74311Tkf5g)** 🌟
Whether you're just getting started or you're a power user, our community is here to support you. We share tips, troubleshoot issues together, showcase cool projects, and discuss the latest developments in AI-powered scientific research.
**See you there!** 💬
---
## 📖 Citation
If you use Claude Scientific Skills in your research or project, please cite it as:
### BibTeX
```bibtex
@software{claude_scientific_skills_2026,
author = {{K-Dense Inc.}},
title = {Claude Scientific Skills: A Comprehensive Collection of Scientific Tools for Claude AI},
year = {2026},
url = {https://github.com/K-Dense-AI/claude-scientific-skills},
note = {skills covering databases, packages, integrations, and analysis tools}
}
K-Dense Inc. (2026). Claude Scientific Skills: A comprehensive collection of scientific tools for Claude AI [Computer software]. https://github.com/K-Dense-AI/claude-scientific-skills
K-Dense Inc. Claude Scientific Skills: A Comprehensive Collection of Scientific Tools for Claude AI. 2026, github.com/K-Dense-AI/claude-scientific-skills.
Claude Scientific Skills by K-Dense Inc. (2026)
Available at: https://github.com/K-Dense-AI/claude-scientific-skills
We appreciate acknowledgment in publications, presentations, or projects that benefit from these skills!
This project is licensed under the MIT License.
Copyright © 2026 K-Dense Inc. (k-dense.ai)
See LICENSE.md for full terms.
⚠️ Important: Each skill has its own license specified in the
licensemetadata field within itsSKILL.mdfile. These licenses may differ from the repository's MIT License and may include additional terms or restrictions. Users are responsible for reviewing and adhering to the license terms of each individual skill they use.
Install via CLI
npx mdskills install K-Dense-AI/claude-scientific-skillsClaude Scientific Skills is a free, open-source AI agent skill. A comprehensive collection of 146+ ready-to-use scientific and research skills (now including financial/SEC research, U.S. Treasury fiscal data, OFR Hedge Fund Monitor, and Alpha Vantage market data) for any AI agent that supports the open Agent Skills standard, created by K-Dense. Works with Cursor, Claude Code, Codex, and more. Transform your AI agent into a research assistant capable of executi
Install Claude Scientific Skills with a single command:
npx mdskills install K-Dense-AI/claude-scientific-skillsThis downloads the skill files into your project and your AI agent picks them up automatically.
Claude Scientific Skills works with Claude Code, Claude Desktop, Cursor, Vscode Copilot, Windsurf, Continue Dev, Codex, Gemini Cli, Amp, Roo Code, Goose, Opencode, Trae, Qodo, Command Code. Skills use the open SKILL.md format which is compatible with any AI coding agent that reads markdown instructions.