claude-scientific-skills
Comprehensive collection of 128+ ready-to-use scientific skills for Claude enabling research across biology, chemistry, medicine, genomics, and advanced analysis domains.
Best use case
claude-scientific-skills is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Comprehensive collection of 128+ ready-to-use scientific skills for Claude enabling research across biology, chemistry, medicine, genomics, and advanced analysis domains.
Teams using claude-scientific-skills should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/claude-scientific-skills/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How claude-scientific-skills Compares
| Feature / Agent | claude-scientific-skills | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Comprehensive collection of 128+ ready-to-use scientific skills for Claude enabling research across biology, chemistry, medicine, genomics, and advanced analysis domains.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Claude Scientific Skills Collection A comprehensive collection of **128+ ready-to-use scientific skills** that transforms Claude into an AI research assistant capable of executing complex multi-step scientific workflows. ## 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, precision therapeutics ### 🧠 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, cosmological calculations, symbolic mathematics, physics computations ### ⚙️ Engineering & Simulation Discrete-event simulation, optimization, metabolic engineering, systems modeling ## Included Skill Categories - **26+ Scientific Databases** - OpenAlex, PubMed, ChEMBL, UniProt, COSMIC, ClinicalTrials.gov - **54+ Python Packages** - RDKit, Scanpy, PyTorch, scikit-learn, BioPython, PennyLane, Qiskit - **15+ Scientific Integrations** - Benchling, DNAnexus, LatchBio, OMERO, Protocols.io - **20+ Analysis & Communication Tools** - Literature review, scientific writing, peer review ## Getting Started Each skill within this collection includes: - Comprehensive documentation (SKILL.md) - Practical code examples - Use cases and best practices - Integration guides - Reference materials Explore the `scientific-skills/` subdirectory for individual skill implementations and detailed documentation.
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