About claude-scientific-skills
Claude Scientific Skills Collection is a set of ready-to-use skills for scientific research workflows. It covers domains from bioinformatics and clinical research to physics and engineering, with documentation, code examples, and integration guides for each skill.
Key features
- 01Skills across scientific domains
- 02Scientific database coverage
- 03Python package integrations
- 04Research and writing tools
- 05Examples and reference guides
Use cases
- 01Run bioinformatics analyses
- 02Explore drug discovery workflows
- 03Analyze clinical research data
- 04Conduct literature reviews and scientific writing
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ microck/ ordinary-claude-skills --skill claude-scientific-skillsAfter installing, type/claude-scientific-skillsin Claude Code to confirm it loaded.
Bundled files
References and scripts installed along with SKILL.md.
.gitignoreLICENSE.mdREADME.md.claude-plugin/marketplace.json.github/workflows/release.ymldocs/examples.mdscientific-skills.mdscientific-skills/adaptyv/reference/api_reference.mdexamples.mdexperiments.mdprotein_optimization.mdscientific-skills/aeon/references/anomaly_detection.mdclassification.mdclustering.mddatasets_benchmarking.mddistances.mdforecasting.mdnetworks.mdregression.mdsegmentation.mdsimilarity_search.mdtransformations.mdscientific-skills/alphafold-database/references/api_reference.mdscientific-skills/anndata/references/best_practices.mdconcatenation.mddata_structure.mdio_operations.mdmanipulation.mdscientific-skills/arboreto/references/algorithms.mdbasic_inference.mdDetails
From the project READMEClaude 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.