Claude Scientific Skills
Overview
A comprehensive collection of 139 ready-to-use scientific skills that transform Claude into an AI research assistant capable of executing complex multi-step scientific workflows across biology, chemistry, medicine, and related fields.
When to Use
Invoke this skill when:
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Working on scientific research tasks
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Need access to specialized databases (PubMed, ChEMBL, UniProt, etc.)
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Performing bioinformatics or cheminformatics analysis
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Creating literature reviews or scientific documents
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Analyzing single-cell RNA-seq, proteomics, or multi-omics data
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Drug discovery and molecular analysis workflows
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Statistical analysis and machine learning on scientific data
Quick Start
// Invoke the main skill catalog Skill({ skill: 'scientific-skills' });
// Or invoke specific sub-skills directly Skill({ skill: 'scientific-skills/rdkit' }); // Cheminformatics Skill({ skill: 'scientific-skills/scanpy' }); // Single-cell analysis Skill({ skill: 'scientific-skills/biopython' }); // Bioinformatics Skill({ skill: 'scientific-skills/literature-review' }); // Literature review
Skill Categories
Scientific Databases (28+)
Skill Description
pubchem
Chemical compound database
chembl-database
Bioactivity database for drug discovery
uniprot-database
Protein sequence and function database
pdb
Protein Data Bank structures
drugbank-database
Drug and drug target information
kegg
Pathway and genome database
clinvar-database
Clinical variant interpretations
cosmic-database
Cancer mutation database
ensembl-database
Genome browser and annotations
geo-database
Gene expression data
gwas-database
Genome-wide association studies
reactome-database
Biological pathways
string-database
Protein-protein interactions
alphafold-database
Protein structure predictions
biorxiv-database
Preprint server for biology
clinicaltrials-database
Clinical trial registry
ena-database
European Nucleotide Archive
fda-database
FDA drug approvals and labels
gene-database
Gene information from NCBI
zinc-database
Commercially available compounds
brenda-database
Enzyme database
clinpgx-database
Pharmacogenomics annotations
uspto-database
Patent database
Python Analysis Libraries (55+)
Skill Description
rdkit
Cheminformatics toolkit
scanpy
Single-cell RNA-seq analysis
anndata
Annotated data matrices
biopython
Computational biology tools
pytorch-lightning
Deep learning framework
scikit-learn
Machine learning library
transformers
NLP and deep learning models
pandas / polars / vaex
Data manipulation
matplotlib / seaborn / plotly
Visualization
deepchem
Deep learning for chemistry
esm
Evolutionary Scale Modeling
datamol
Molecular data processing
pymatgen
Materials science
qiskit
Quantum computing
pymoo
Multi-objective optimization
statsmodels
Statistical modeling
sympy
Symbolic mathematics
networkx
Network analysis
geopandas
Geospatial analysis
shap
Model explainability
Bioinformatics & Genomics
Skill Description
gget
Gene and transcript information
pysam
SAM/BAM file manipulation
deeptools
NGS data analysis
pydeseq2
Differential expression
scvi-tools
Deep learning for single-cell
etetoolkit
Phylogenetic analysis
scikit-bio
Bioinformatics algorithms
bioservices
Web services for biology
cellxgene-census
Cell atlas exploration
Cheminformatics & Drug Discovery
Skill Description
rdkit
Molecular manipulation
datamol
Molecular data handling
molfeat
Molecular featurization
diffdock
Molecular docking
torchdrug
Drug discovery ML
pytdc
Therapeutics data commons
cobrapy
Metabolic modeling
Scientific Communication
Skill Description
literature-review
Systematic literature reviews
scientific-writing
Academic writing assistance
scientific-schematics
AI-generated figures
scientific-slides
Presentation generation
hypothesis-generation
Hypothesis development
venue-templates
Journal-specific formatting
citation-management
Reference management
Clinical & Medical
Skill Description
clinical-decision-support
Clinical reasoning
clinical-reports
Medical report generation
treatment-plans
Treatment planning
pyhealth
Healthcare ML
pydicom
Medical imaging
Laboratory & Integration
Skill Description
benchling-integration
Lab informatics platform
dnanexus-integration
Genomics cloud platform
pylabrobot
Laboratory automation
flowio
Flow cytometry data
omero-integration
Bioimaging platform
Core Workflows
Literature Review Workflow
7-phase systematic literature review
1. Planning with PICO framework
2. Multi-database search execution
3. Screening with PRISMA flow
4. Data extraction and quality assessment
5. Thematic synthesis
6. Citation verification
7. PDF generation
Drug Discovery Workflow
Using RDKit + ChEMBL + datamol
from rdkit import Chem from rdkit.Chem import Descriptors, AllChem
1. Query ChEMBL for bioactivity data
2. Calculate molecular properties
3. Filter by drug-likeness (Lipinski)
4. Similarity screening
5. Substructure analysis
Single-Cell Analysis Workflow
Using scanpy + anndata
import scanpy as sc
1. Load and QC data
2. Normalization and feature selection
3. Dimensionality reduction (PCA, UMAP)
4. Clustering (Leiden algorithm)
5. Marker gene identification
6. Cell type annotation
Hypothesis Generation Workflow
8-step systematic process
1. Understand phenomenon
2. Literature search
3. Synthesize evidence
4. Generate competing hypotheses
5. Evaluate quality
6. Design experiments
7. Formulate predictions
8. Generate report
Sub-Skill Structure
Each sub-skill follows a consistent structure:
scientific-skills/ ├── SKILL.md # This file (catalog/index) ├── skills/ # Individual skill directories │ ├── rdkit/ │ │ ├── SKILL.md # Skill documentation │ │ ├── references/ # API references, patterns │ │ └── scripts/ # Example scripts │ ├── scanpy/ │ ├── biopython/ │ └── ... (139 total)
Invoking Sub-Skills
Direct Invocation
// Invoke specific skill Skill({ skill: 'scientific-skills/rdkit' }); Skill({ skill: 'scientific-skills/scanpy' });
Chained Workflows
// Multi-skill workflow Skill({ skill: 'scientific-skills/literature-review' }); Skill({ skill: 'scientific-skills/hypothesis-generation' }); Skill({ skill: 'scientific-skills/scientific-schematics' });
Prerequisites
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Python 3.9+ (3.12+ recommended)
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uv package manager (recommended)
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Platform: macOS, Linux, or Windows with WSL2
Best Practices
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Start with the right skill: Use the category tables above to find appropriate skills
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Chain skills for complex workflows: Literature review → Hypothesis → Experiment design
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Use database skills for data access: Query databases before analysis
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Visualize results: Use matplotlib/seaborn/plotly skills for publication-quality figures
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Document findings: Use scientific-writing skill for formal documentation
Integration with Agent Framework
Recommended Agent Pairings
Agent Scientific Skills
data-engineer
polars, dask, vaex, zarr-python
python-pro
All Python-based skills
database-architect
Database skills for schema design
technical-writer
literature-review, scientific-writing
Example Agent Spawn
Task({ subagent_type: 'python-pro', description: 'Analyze molecular dataset with RDKit', prompt: `You are the PYTHON-PRO agent with scientific research expertise.
Task
Analyze the molecular dataset for drug-likeness properties.
Skills to Invoke
- Skill({ skill: "scientific-skills/rdkit" })
- Skill({ skill: "scientific-skills/datamol" })
Workflow
- Load molecular data
- Calculate descriptors
- Apply Lipinski filters
- Generate visualization
- Report findings `, });
Resources
Bundled Documentation
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skills/*/SKILL.md
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Individual skill documentation
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skills/*/references/
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API references and patterns
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skills/*/scripts/
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Example scripts and templates
External Resources
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K-Dense AI GitHub
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RDKit Documentation
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Scanpy Documentation
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BioPython Tutorial
Version History
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v2.17.0 - Current version with 139 skills
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Integrated from K-Dense-AI/claude-scientific-skills repository
License
MIT License - Open source and freely available for research and commercial use.