claude-scientific-skills
npx skills add https://github.com/microck/ordinary-claude-skills --skill claude-scientific-skills
Agent 安装分布
Skill 文档
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
𧬠Bioinformatics & Genomics
Sequence analysis, single-cell RNA-seq, gene regulatory networks, variant annotation, phylogenetic analysis
𧪠Cheminformatics & Drug Discovery
Molecular property prediction, virtual screening, ADMET analysis, molecular docking, lead optimization
ð¬ Proteomics & Mass Spectrometry
LC-MS/MS processing, peptide identification, spectral matching, protein quantification
ð¥ Clinical Research & Precision Medicine
Clinical trials, pharmacogenomics, variant interpretation, drug safety, precision therapeutics
ð§ Healthcare AI & Clinical ML
EHR analysis, physiological signal processing, medical imaging, clinical prediction models
ð¼ï¸ Medical Imaging & Digital Pathology
DICOM processing, whole slide image analysis, computational pathology, radiology workflows
ð¤ Machine Learning & AI
Deep learning, reinforcement learning, time series analysis, model interpretability, Bayesian methods
ð® Materials Science & Chemistry
Crystal structure analysis, phase diagrams, metabolic modeling, computational chemistry
ð Physics & Astronomy
Astronomical data analysis, cosmological calculations, symbolic mathematics, physics computations
âï¸ 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.