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
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npx mdskills install K-Dense-AI/claude-scientific-skillsProvides no actionable instructions or concrete capabilities for scientific work
1# Claude Scientific Skills23[](LICENSE.md)4[](#whats-included)5[](https://agentskills.io/)6[](#getting-started)78A 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](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.910**Looking for the full AI co-scientist experience?** Try [K-Dense Web](https://k-dense.ai) for 200+ skills, cloud compute, and publication-ready outputs.1112<p align="center">13 <a href="https://k-dense.ai">14 <img src="docs/k-dense-web.gif" alt="K-Dense Web Demo" width="800"/>15 </a>16</p>1718---1920## K-Dense Web - The Full Experience2122Want 10x the power with zero setup? **[K-Dense Web](https://k-dense.ai)** is the complete AI co-scientist platform—everything in this repo, plus:2324| Feature | This Repo | K-Dense Web |25|---------|-----------|-------------|26| Scientific Skills | 140 skills | **200+ skills** (exclusive access) |27| Setup Required | Manual installation | **Zero setup** — works instantly |28| Compute | Your machine | **Cloud GPUs & HPC** included |29| Workflows | Basic prompts | **End-to-end research pipelines** |30| Outputs | Code & analysis | **Publication-ready** figures, reports & papers |31| Integrations | Local tools | **Lab systems, ELNs, cloud storage** |3233**Researchers at Stanford, MIT, and leading pharma companies use K-Dense Web to accelerate discoveries.**3435**Get $50 in free credits** — no credit card required.3637<a href="https://k-dense.ai"><img src="https://img.shields.io/badge/Try_K--Dense_Web-Start_Free-blue?style=for-the-badge&logo=data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHdpZHRoPSIyNCIgaGVpZ2h0PSIyNCIgdmlld0JveD0iMCAwIDI0IDI0IiBmaWxsPSJub25lIiBzdHJva2U9IndoaXRlIiBzdHJva2Utd2lkdGg9IjIiIHN0cm9rZS1saW5lY2FwPSJyb3VuZCIgc3Ryb2tlLWxpbmVqb2luPSJyb3VuZCI+PHBhdGggZD0iTTUgMTJoMTQiLz48cGF0aCBkPSJtMTIgNSA3IDctNyA3Ii8+PC9zdmc+" alt="Try K-Dense Web"></a>3839*Learn more at [k-dense.ai](https://k-dense.ai)* | *[Read our detailed comparison →](https://k-dense.ai/blog/k-dense-web-vs-claude-scientific-skills)*4041---4243These skills enable your AI agent to seamlessly work with specialized scientific libraries, databases, and tools across multiple scientific domains:44- 🧬 Bioinformatics & Genomics - Sequence analysis, single-cell RNA-seq, gene regulatory networks, variant annotation, phylogenetic analysis45- 🧪 Cheminformatics & Drug Discovery - Molecular property prediction, virtual screening, ADMET analysis, molecular docking, lead optimization46- 🔬 Proteomics & Mass Spectrometry - LC-MS/MS processing, peptide identification, spectral matching, protein quantification47- 🏥 Clinical Research & Precision Medicine - Clinical trials, pharmacogenomics, variant interpretation, drug safety, clinical decision support, treatment planning48- 🧠 Healthcare AI & Clinical ML - EHR analysis, physiological signal processing, medical imaging, clinical prediction models49- 🖼️ Medical Imaging & Digital Pathology - DICOM processing, whole slide image analysis, computational pathology, radiology workflows50- 🤖 Machine Learning & AI - Deep learning, reinforcement learning, time series analysis, model interpretability, Bayesian methods51- 🔮 Materials Science & Chemistry - Crystal structure analysis, phase diagrams, metabolic modeling, computational chemistry52- 🌌 Physics & Astronomy - Astronomical data analysis, coordinate transformations, cosmological calculations, symbolic mathematics, physics computations53- ⚙️ Engineering & Simulation - Discrete-event simulation, multi-objective optimization, metabolic engineering, systems modeling, process optimization54- 📊 Data Analysis & Visualization - Statistical analysis, network analysis, time series, publication-quality figures, large-scale data processing, EDA55- 🧪 Laboratory Automation - Liquid handling protocols, lab equipment control, workflow automation, LIMS integration56- 📚 Scientific Communication - Literature review, peer review, scientific writing, document processing, posters, slides, schematics, citation management57- 🔬 Multi-omics & Systems Biology - Multi-modal data integration, pathway analysis, network biology, systems-level insights58- 🧬 Protein Engineering & Design - Protein language models, structure prediction, sequence design, function annotation59- 🎓 Research Methodology - Hypothesis generation, scientific brainstorming, critical thinking, grant writing, scholar evaluation6061**Transform your AI coding agent into an 'AI Scientist' on your desktop!**6263> ⭐ **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.6465> 🎬 **New to Claude Scientific Skills?** Watch our [Getting Started with Claude Scientific Skills](https://youtu.be/ZxbnDaD_FVg) video for a quick walkthrough.6667---6869## 📦 What's Included7071This repository provides **146 scientific and research skills** organized into the following categories:7273- **30+ Scientific & Financial Databases** - Direct API access to OpenAlex, PubMed, bioRxiv, ChEMBL, UniProt, COSMIC, ClinicalTrials.gov, SEC EDGAR, U.S. Treasury Fiscal Data, Alpha Vantage, and more74- **55+ Python Packages** - RDKit, Scanpy, PyTorch Lightning, scikit-learn, BioPython, BioServices, PennyLane, Qiskit, and others75- **15+ Scientific Integrations** - Benchling, DNAnexus, LatchBio, OMERO, Protocols.io, and more76- **30+ Analysis & Communication Tools** - Literature review, scientific writing, peer review, document processing, posters, slides, schematics, and more77- **10+ Research & Clinical Tools** - Hypothesis generation, grant writing, clinical decision support, treatment plans, regulatory compliance7879Each skill includes:80- ✅ Comprehensive documentation (`SKILL.md`)81- ✅ Practical code examples82- ✅ Use cases and best practices83- ✅ Integration guides84- ✅ Reference materials8586---8788## 📋 Table of Contents8990- [What's Included](#whats-included)91- [Why Use This?](#why-use-this)92- [Getting Started](#getting-started)93- [Support Open Source](#-support-the-open-source-community)94- [Prerequisites](#prerequisites)95- [Quick Examples](#quick-examples)96- [Use Cases](#use-cases)97- [Available Skills](#available-skills)98- [Contributing](#contributing)99- [Troubleshooting](#troubleshooting)100- [FAQ](#faq)101- [Support](#support)102- [Join Our Community](#join-our-community)103- [Citation](#citation)104- [License](#license)105106---107108## 🚀 Why Use This?109110### ⚡ **Accelerate Your Research**111- **Save Days of Work** - Skip API documentation research and integration setup112- **Production-Ready Code** - Tested, validated examples following scientific best practices113- **Multi-Step Workflows** - Execute complex pipelines with a single prompt114115### 🎯 **Comprehensive Coverage**116- **140 Skills** - Extensive coverage across all major scientific domains117- **28+ Databases** - Direct access to OpenAlex, PubMed, bioRxiv, ChEMBL, UniProt, COSMIC, and more118- **55+ Python Packages** - RDKit, Scanpy, PyTorch Lightning, scikit-learn, BioServices, PennyLane, Qiskit, and others119120### 🔧 **Easy Integration**121- **Simple Setup** - Copy skills to your skills directory and start working122- **Automatic Discovery** - Your agent automatically finds and uses relevant skills123- **Well Documented** - Each skill includes examples, use cases, and best practices124125### 🌟 **Maintained & Supported**126- **Regular Updates** - Continuously maintained and expanded by K-Dense team127- **Community Driven** - Open source with active community contributions128- **Enterprise Ready** - Commercial support available for advanced needs129130---131132## 🎯 Getting Started133134Claude Scientific Skills follows the open [Agent Skills](https://agentskills.io/) standard. Simply copy the skill folders into your skills directory and your AI agent will automatically discover and use them.135136### Step 1: Clone the Repository137138```bash139git clone https://github.com/K-Dense-AI/claude-scientific-skills.git140```141142### Step 2: Copy Skills to Your Skills Directory143144Copy 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).145146**Global installation** (recommended — skills available everywhere):147148| Tool | Directory |149|------|-----------|150| Cursor | `~/.cursor/skills/` |151| Claude Code | `~/.claude/skills/` |152| Codex | `~/.codex/skills/` |153154**Project-level installation** (skills scoped to a single project):155156| Tool | Directory |157|------|-----------|158| Cursor | `.cursor/skills/` (in your project root) |159| Claude Code | `.claude/skills/` (in your project root) |160| Codex | `.codex/skills/` (in your project root) |161162> **Note:** Cursor also reads from `.claude/skills/` and `.codex/skills/` directories, and vice versa, so skills are cross-compatible between tools.163164**Example — global install for Cursor:**165```bash166cp -r claude-scientific-skills/scientific-skills/* ~/.cursor/skills/167```168169**Example — global install for Claude Code:**170```bash171cp -r claude-scientific-skills/scientific-skills/* ~/.claude/skills/172```173174**Example — project-level install:**175```bash176mkdir -p .cursor/skills177cp -r /path/to/claude-scientific-skills/scientific-skills/* .cursor/skills/178```179180**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.181182---183184## ❤️ Support the Open Source Community185186Claude 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.187188**If you find value in this repository, please consider supporting the projects that make it possible:**189190- ⭐ **Star their repositories** on GitHub191- 💰 **Sponsor maintainers** via GitHub Sponsors or NumFOCUS192- 📝 **Cite projects** in your publications193- 💻 **Contribute** code, docs, or bug reports194195👉 **[View the full list of projects to support](docs/open-source-sponsors.md)**196197---198199## ⚙️ Prerequisites200201- **Python**: 3.9+ (3.12+ recommended for best compatibility)202- **uv**: Python package manager (required for installing skill dependencies)203- **Client**: Any agent that supports the [Agent Skills](https://agentskills.io/) standard (Cursor, Claude Code, Codex, etc.)204- **System**: macOS, Linux, or Windows with WSL2205- **Dependencies**: Automatically handled by individual skills (check `SKILL.md` files for specific requirements)206207### Installing uv208209The skills use `uv` as the package manager for installing Python dependencies. Install it using the instructions for your operating system:210211**macOS and Linux:**212```bash213curl -LsSf https://astral.sh/uv/install.sh | sh214```215216**Windows:**217```powershell218powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"219```220221**Alternative (via pip):**222```bash223pip install uv224```225226After installation, verify it works by running:227```bash228uv --version229```230231For more installation options and details, visit the [official uv documentation](https://docs.astral.sh/uv/).232233---234235## 💡 Quick Examples236237Once you've installed the skills, you can ask your AI agent to execute complex multi-step scientific workflows. Here are some example prompts:238239### 🧪 Drug Discovery Pipeline240**Goal**: Find novel EGFR inhibitors for lung cancer treatment241242**Prompt**:243```244Use available skills you have access to whenever possible. Query ChEMBL for EGFR inhibitors (IC50 < 50nM), analyze structure-activity relationships245with RDKit, generate improved analogs with datamol, perform virtual screening with DiffDock246against AlphaFold EGFR structure, search PubMed for resistance mechanisms, check COSMIC for247mutations, and create visualizations and a comprehensive report.248```249250**Skills Used**: ChEMBL, RDKit, datamol, DiffDock, AlphaFold DB, PubMed, COSMIC, scientific visualization251252---253254### 🔬 Single-Cell RNA-seq Analysis255**Goal**: Comprehensive analysis of 10X Genomics data with public data integration256257**Prompt**:258```259Use available skills you have access to whenever possible. Load 10X dataset with Scanpy, perform QC and doublet removal, integrate with Cellxgene260Census data, identify cell types using NCBI Gene markers, run differential expression with261PyDESeq2, infer gene regulatory networks with Arboreto, enrich pathways via Reactome/KEGG,262and identify therapeutic targets with Open Targets.263```264265**Skills Used**: Scanpy, Cellxgene Census, NCBI Gene, PyDESeq2, Arboreto, Reactome, KEGG, Open Targets266267---268269### 🧬 Multi-Omics Biomarker Discovery270**Goal**: Integrate RNA-seq, proteomics, and metabolomics to predict patient outcomes271272**Prompt**:273```274Use available skills you have access to whenever possible. Analyze RNA-seq with PyDESeq2, process mass spec with pyOpenMS, integrate metabolites from275HMDB/Metabolomics Workbench, map proteins to pathways (UniProt/KEGG), find interactions via276STRING, correlate omics layers with statsmodels, build predictive model with scikit-learn,277and search ClinicalTrials.gov for relevant trials.278```279280**Skills Used**: PyDESeq2, pyOpenMS, HMDB, Metabolomics Workbench, UniProt, KEGG, STRING, statsmodels, scikit-learn, ClinicalTrials.gov281282---283284### 🎯 Virtual Screening Campaign285**Goal**: Discover allosteric modulators for protein-protein interactions286287**Prompt**:288```289Use available skills you have access to whenever possible. Retrieve AlphaFold structures, identify interaction interface with BioPython, search ZINC290for allosteric candidates (MW 300-500, logP 2-4), filter with RDKit, dock with DiffDock,291rank with DeepChem, check PubChem suppliers, search USPTO patents, and optimize leads with292MedChem/molfeat.293```294295**Skills Used**: AlphaFold DB, BioPython, ZINC, RDKit, DiffDock, DeepChem, PubChem, USPTO, MedChem, molfeat296297---298299### 🏥 Clinical Variant Interpretation300**Goal**: Analyze VCF file for hereditary cancer risk assessment301302**Prompt**:303```304Use available skills you have access to whenever possible. Parse VCF with pysam, annotate variants with Ensembl VEP, query ClinVar for pathogenicity,305check COSMIC for cancer mutations, retrieve gene info from NCBI Gene, analyze protein impact306with UniProt, search PubMed for case reports, check ClinPGx for pharmacogenomics, generate307clinical report with document processing tools, and find matching trials on ClinicalTrials.gov.308```309310**Skills Used**: pysam, Ensembl, ClinVar, COSMIC, NCBI Gene, UniProt, PubMed, ClinPGx, Document Skills, ClinicalTrials.gov311312---313314### 🌐 Systems Biology Network Analysis315**Goal**: Analyze gene regulatory networks from RNA-seq data316317**Prompt**:318```319Use available skills you have access to whenever possible. Query NCBI Gene for annotations, retrieve sequences from UniProt, identify interactions via320STRING, map to Reactome/KEGG pathways, analyze topology with Torch Geometric, reconstruct321GRNs with Arboreto, assess druggability with Open Targets, model with PyMC, visualize322networks, and search GEO for similar patterns.323```324325**Skills Used**: NCBI Gene, UniProt, STRING, Reactome, KEGG, Torch Geometric, Arboreto, Open Targets, PyMC, GEO326327> 📖 **Want more examples?** Check out [docs/examples.md](docs/examples.md) for comprehensive workflow examples and detailed use cases across all scientific domains.328329---330331## 🔬 Use Cases332333### 🧪 Drug Discovery & Medicinal Chemistry334- **Virtual Screening**: Screen millions of compounds from PubChem/ZINC against protein targets335- **Lead Optimization**: Analyze structure-activity relationships with RDKit, generate analogs with datamol336- **ADMET Prediction**: Predict absorption, distribution, metabolism, excretion, and toxicity with DeepChem337- **Molecular Docking**: Predict binding poses and affinities with DiffDock338- **Bioactivity Mining**: Query ChEMBL for known inhibitors and analyze SAR patterns339340### 🧬 Bioinformatics & Genomics341- **Sequence Analysis**: Process DNA/RNA/protein sequences with BioPython and pysam342- **Single-Cell Analysis**: Analyze 10X Genomics data with Scanpy, identify cell types, infer GRNs with Arboreto343- **Variant Annotation**: Annotate VCF files with Ensembl VEP, query ClinVar for pathogenicity344- **Gene Discovery**: Query NCBI Gene, UniProt, and Ensembl for comprehensive gene information345- **Network Analysis**: Identify protein-protein interactions via STRING, map to pathways (KEGG, Reactome)346347### 🏥 Clinical Research & Precision Medicine348- **Clinical Trials**: Search ClinicalTrials.gov for relevant studies, analyze eligibility criteria349- **Variant Interpretation**: Annotate variants with ClinVar, COSMIC, and ClinPGx for pharmacogenomics350- **Drug Safety**: Query FDA databases for adverse events, drug interactions, and recalls351- **Precision Therapeutics**: Match patient variants to targeted therapies and clinical trials352353### 🔬 Multi-Omics & Systems Biology354- **Multi-Omics Integration**: Combine RNA-seq, proteomics, and metabolomics data355- **Pathway Analysis**: Enrich differentially expressed genes in KEGG/Reactome pathways356- **Network Biology**: Reconstruct gene regulatory networks, identify hub genes357- **Biomarker Discovery**: Integrate multi-omics layers to predict patient outcomes358359### 📊 Data Analysis & Visualization360- **Statistical Analysis**: Perform hypothesis testing, power analysis, and experimental design361- **Publication Figures**: Create publication-quality visualizations with matplotlib and seaborn362- **Network Visualization**: Visualize biological networks with NetworkX363- **Report Generation**: Generate comprehensive PDF reports with Document Skills364365### 🧪 Laboratory Automation366- **Protocol Design**: Create Opentrons protocols for automated liquid handling367- **LIMS Integration**: Integrate with Benchling and LabArchives for data management368- **Workflow Automation**: Automate multi-step laboratory workflows369370---371372## 📚 Available Skills373374This 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.375376### Skill Categories377378#### 🧬 **Bioinformatics & Genomics** (16+ skills)379- Sequence analysis: BioPython, pysam, scikit-bio, BioServices380- Single-cell analysis: Scanpy, AnnData, scvi-tools, Arboreto, Cellxgene Census381- Genomic tools: gget, geniml, gtars, deepTools, FlowIO, Zarr382- Phylogenetics: ETE Toolkit383384#### 🧪 **Cheminformatics & Drug Discovery** (11+ skills)385- Molecular manipulation: RDKit, Datamol, Molfeat386- Deep learning: DeepChem, TorchDrug387- Docking & screening: DiffDock388- Cloud quantum chemistry: Rowan (pKa, docking, cofolding)389- Drug-likeness: MedChem390- Benchmarks: PyTDC391392#### 🔬 **Proteomics & Mass Spectrometry** (2 skills)393- Spectral processing: matchms, pyOpenMS394395#### 🏥 **Clinical Research & Precision Medicine** (12+ skills)396- Clinical databases: ClinicalTrials.gov, ClinVar, ClinPGx, COSMIC, FDA Databases397- Healthcare AI: PyHealth, NeuroKit2, Clinical Decision Support398- Clinical documentation: Clinical Reports, Treatment Plans399- Variant analysis: Ensembl, NCBI Gene400401#### 🖼️ **Medical Imaging & Digital Pathology** (3 skills)402- DICOM processing: pydicom403- Whole slide imaging: histolab, PathML404405#### 🧠 **Neuroscience & Electrophysiology** (1 skill)406- Neural recordings: Neuropixels-Analysis (extracellular spikes, silicon probes, spike sorting)407408#### 🤖 **Machine Learning & AI** (15+ skills)409- Deep learning: PyTorch Lightning, Transformers, Stable Baselines3, PufferLib410- Classical ML: scikit-learn, scikit-survival, SHAP411- Time series: aeon412- Bayesian methods: PyMC413- Optimization: PyMOO414- Graph ML: Torch Geometric415- Dimensionality reduction: UMAP-learn416- Statistical modeling: statsmodels417418#### 🔮 **Materials Science, Chemistry & Physics** (7 skills)419- Materials: Pymatgen420- Metabolic modeling: COBRApy421- Astronomy: Astropy422- Quantum computing: Cirq, PennyLane, Qiskit, QuTiP423424#### ⚙️ **Engineering & Simulation** (4 skills)425- Numerical computing: MATLAB/Octave426- Computational fluid dynamics: FluidSim427- Discrete-event simulation: SimPy428- Data processing: Dask, Polars, Vaex429430#### 📊 **Data Analysis & Visualization** (14+ skills)431- Visualization: Matplotlib, Seaborn, Plotly, Scientific Visualization432- Geospatial analysis: GeoPandas433- Network analysis: NetworkX434- Symbolic math: SymPy435- Document processing: Document Skills (PDF, DOCX, PPTX, XLSX)436- Data access: Data Commons437- Exploratory data analysis: EDA workflows438- Statistical analysis: Statistical Analysis workflows439440#### 🧪 **Laboratory Automation** (3 skills)441- Liquid handling: PyLabRobot442- Protocol management: Protocols.io443- LIMS integration: Benchling, LabArchives444445#### 🔬 **Multi-omics & Systems Biology** (5+ skills)446- Pathway analysis: KEGG, Reactome, STRING447- Multi-omics: Denario, HypoGeniC448- Data management: LaminDB449450#### 🧬 **Protein Engineering & Design** (2 skills)451- Protein language models: ESM452- Cloud laboratory platform: Adaptyv (automated protein testing and validation)453454#### 📚 **Scientific Communication** (20+ skills)455- Literature: OpenAlex, PubMed, bioRxiv, Literature Review456- Web search: Perplexity Search (AI-powered search with real-time information)457- Writing: Scientific Writing, Peer Review458- Document processing: XLSX, MarkItDown, Document Skills459- Publishing: Paper-2-Web, Venue Templates460- Presentations: Scientific Slides, LaTeX Posters, PPTX Posters461- Diagrams: Scientific Schematics462- Citations: Citation Management463- Illustration: Generate Image (AI image generation with FLUX.2 Pro and Gemini 3 Pro (Nano Banana Pro))464465#### 🔬 **Scientific Databases** (28+ skills)466- Protein: UniProt, PDB, AlphaFold DB467- Chemical: PubChem, ChEMBL, DrugBank, ZINC, HMDB468- Genomic: Ensembl, NCBI Gene, GEO, ENA, GWAS Catalog469- Literature: bioRxiv (preprints)470- Clinical: ClinVar, COSMIC, ClinicalTrials.gov, ClinPGx, FDA Databases471- Pathways: KEGG, Reactome, STRING472- Targets: Open Targets473- Metabolomics: Metabolomics Workbench474- Enzymes: BRENDA475- Patents: USPTO476477#### 🔧 **Infrastructure & Platforms** (6+ skills)478- Cloud compute: Modal479- Genomics platforms: DNAnexus, LatchBio480- Microscopy: OMERO481- Automation: Opentrons482- Resource detection: Get Available Resources483484#### 🎓 **Research Methodology & Planning** (8+ skills)485- Ideation: Scientific Brainstorming, Hypothesis Generation486- Critical analysis: Scientific Critical Thinking, Scholar Evaluation487- Funding: Research Grants488- Discovery: Research Lookup489- Market analysis: Market Research Reports490491#### ⚖️ **Regulatory & Standards** (1 skill)492- Medical device standards: ISO 13485 Certification493494#### 💹 **Financial & SEC Research** (4 skills)495- SEC filings & financial data: edgartools (10-K, 10-Q, 8-K, 13F, Form 4, XBRL, insider trading, institutional holdings)496- U.S. federal fiscal data: usfiscaldata (national debt, Daily/Monthly Treasury Statements, Treasury auctions, interest rates, exchange rates, savings bonds)497- Hedge fund systemic risk: hedgefundmonitor (OFR Hedge Fund Monitor API — Form PF aggregated stats, CFTC futures positioning, FICC sponsored repo, SCOOS dealer financing)498- Global market data: alpha-vantage (real-time & historical stocks, options, forex, crypto, commodities, economic indicators, 50+ technical indicators via Alpha Vantage API)499500> 📖 **For complete details on all skills**, see [docs/scientific-skills.md](docs/scientific-skills.md)501502> 💡 **Looking for practical examples?** Check out [docs/examples.md](docs/examples.md) for comprehensive workflow examples across all scientific domains.503504---505506## 🤝 Contributing507508We welcome contributions to expand and improve this scientific skills repository!509510### Ways to Contribute511512✨ **Add New Skills**513- Create skills for additional scientific packages or databases514- Add integrations for scientific platforms and tools515516📚 **Improve Existing Skills**517- Enhance documentation with more examples and use cases518- Add new workflows and reference materials519- Improve code examples and scripts520- Fix bugs or update outdated information521522🐛 **Report Issues**523- Submit bug reports with detailed reproduction steps524- Suggest improvements or new features525526### How to Contribute5275281. **Fork** the repository5292. **Create** a feature branch (`git checkout -b feature/amazing-skill`)5303. **Follow** the existing directory structure and documentation patterns5314. **Ensure** all new skills include comprehensive `SKILL.md` files5325. **Test** your examples and workflows thoroughly5336. **Commit** your changes (`git commit -m 'Add amazing skill'`)5347. **Push** to your branch (`git push origin feature/amazing-skill`)5358. **Submit** a pull request with a clear description of your changes536537### Contribution Guidelines538539✅ **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)540✅ Maintain consistency with existing skill documentation format541✅ Ensure all code examples are tested and functional542✅ Follow scientific best practices in examples and workflows543✅ Update relevant documentation when adding new capabilities544✅ Provide clear comments and docstrings in code545✅ Include references to official documentation546547### Recognition548549Contributors are recognized in our community and may be featured in:550- Repository contributors list551- Special mentions in release notes552- K-Dense community highlights553554Your contributions help make scientific computing more accessible and enable researchers to leverage AI tools more effectively!555556### Support Open Source557558This 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).559560---561562## 🔧 Troubleshooting563564### Common Issues565566**Problem: Skills not loading**567- Verify skill folders are in the correct directory (see [Getting Started](#getting-started))568- Each skill folder must contain a `SKILL.md` file569- Restart your agent/IDE after copying skills570- In Cursor, check Settings → Rules to confirm skills are discovered571572**Problem: Missing Python dependencies**573- Solution: Check the specific `SKILL.md` file for required packages574- Install dependencies: `uv pip install package-name`575576**Problem: API rate limits**577- Solution: Many databases have rate limits. Review the specific database documentation578- Consider implementing caching or batch requests579580**Problem: Authentication errors**581- Solution: Some services require API keys. Check the `SKILL.md` for authentication setup582- Verify your credentials and permissions583584**Problem: Outdated examples**585- Solution: Report the issue via GitHub Issues586- Check the official package documentation for updated syntax587588---589590## ❓ FAQ591592### General Questions593594**Q: Is this free to use?**595A: 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.596597**Q: Why are all skills grouped together instead of separate packages?**598A: 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.599600**Q: Can I use this for commercial projects?**601A: 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.602603**Q: Do all skills have the same license?**604A: 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.605606**Q: How often is this updated?**607A: We regularly update skills to reflect the latest versions of packages and APIs. Major updates are announced in release notes.608609**Q: Can I use this with other AI models?**610A: The skills follow the open [Agent Skills](https://agentskills.io/) standard and work with any compatible agent, including Cursor, Claude Code, and Codex.611612### Installation & Setup613614**Q: Do I need all the Python packages installed?**615A: No! Only install the packages you need. Each skill specifies its requirements in its `SKILL.md` file.616617**Q: What if a skill doesn't work?**618A: First check the [Troubleshooting](#troubleshooting) section. If the issue persists, file an issue on GitHub with detailed reproduction steps.619620**Q: Do the skills work offline?**621A: Database skills require internet access to query APIs. Package skills work offline once Python dependencies are installed.622623### Contributing624625**Q: Can I contribute my own skills?**626A: Absolutely! We welcome contributions. See the [Contributing](#contributing) section for guidelines and best practices.627628**Q: How do I report bugs or suggest features?**629A: Open an issue on GitHub with a clear description. For bugs, include reproduction steps and expected vs actual behavior.630631---632633## 💬 Support634635Need help? Here's how to get support:636637- 📖 **Documentation**: Check the relevant `SKILL.md` and `references/` folders638- 🐛 **Bug Reports**: [Open an issue](https://github.com/K-Dense-AI/claude-scientific-skills/issues)639- 💡 **Feature Requests**: [Submit a feature request](https://github.com/K-Dense-AI/claude-scientific-skills/issues/new)640- 💼 **Enterprise Support**: Contact [K-Dense](https://k-dense.ai/) for commercial support641- 🌐 **Community**: [Join our Slack](https://join.slack.com/t/k-densecommunity/shared_invite/zt-3iajtyls1-EwmkwIZk0g_o74311Tkf5g)642643---644645## 🎉 Join Our Community!646647**We'd love to have you join us!** 🚀648649Connect 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!650651🌟 **[Join our Slack Community](https://join.slack.com/t/k-densecommunity/shared_invite/zt-3iajtyls1-EwmkwIZk0g_o74311Tkf5g)** 🌟652653Whether 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.654655**See you there!** 💬656657---658659## 📖 Citation660661If you use Claude Scientific Skills in your research or project, please cite it as:662663### BibTeX664```bibtex665@software{claude_scientific_skills_2026,666 author = {{K-Dense Inc.}},667 title = {Claude Scientific Skills: A Comprehensive Collection of Scientific Tools for Claude AI},668 year = {2026},669 url = {https://github.com/K-Dense-AI/claude-scientific-skills},670 note = {skills covering databases, packages, integrations, and analysis tools}671}672```673674### APA675```676K-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-skills677```678679### MLA680```681K-Dense Inc. Claude Scientific Skills: A Comprehensive Collection of Scientific Tools for Claude AI. 2026, github.com/K-Dense-AI/claude-scientific-skills.682```683684### Plain Text685```686Claude Scientific Skills by K-Dense Inc. (2026)687Available at: https://github.com/K-Dense-AI/claude-scientific-skills688```689690We appreciate acknowledgment in publications, presentations, or projects that benefit from these skills!691692---693694## 📄 License695696This project is licensed under the **MIT License**.697698**Copyright © 2026 K-Dense Inc.** ([k-dense.ai](https://k-dense.ai/))699700### Key Points:701- ✅ **Free for any use** (commercial and noncommercial)702- ✅ **Open source** - modify, distribute, and use freely703- ✅ **Permissive** - minimal restrictions on reuse704- ⚠️ **No warranty** - provided "as is" without warranty of any kind705706See [LICENSE.md](LICENSE.md) for full terms.707708### Individual Skill Licenses709710> ⚠️ **Important**: 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 and may include additional terms or restrictions. **Users are responsible for reviewing and adhering to the license terms of each individual skill they use.**711712## Star History713714[](https://www.star-history.com/#K-Dense-AI/claude-scientific-skills&type=date&legend=top-left)715
Full transparency — inspect the skill content before installing.