scientific-skills

仓库: oimiragieo/agent-studio
安装量: 58
排名: #12814

安装

npx skills add https://github.com/oimiragieo/agent-studio --skill scientific-skills

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:

Working on scientific research tasks Need access to specialized databases (PubMed, ChEMBL, UniProt, etc.) Performing bioinformatics or cheminformatics analysis Creating literature reviews or scientific documents Analyzing single-cell RNA-seq, proteomics, or multi-omics data Drug discovery and molecular analysis workflows 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 Python 3.9+ (3.12+ recommended) uv package manager (recommended) Platform: macOS, Linux, or Windows with WSL2 Best Practices Start with the right skill: Use the category tables above to find appropriate skills Chain skills for complex workflows: Literature review → Hypothesis → Experiment design Use database skills for data access: Query databases before analysis Visualize results: Use matplotlib/seaborn/plotly skills for publication-quality figures 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

  1. Skill({ skill: "scientific-skills/rdkit" })
  2. Skill({ skill: "scientific-skills/datamol" })

Workflow

  1. Load molecular data
  2. Calculate descriptors
  3. Apply Lipinski filters
  4. Generate visualization
  5. Report findings `, });

Resources Bundled Documentation skills//SKILL.md - Individual skill documentation skills//references/ - API references and patterns skills/*/scripts/ - Example scripts and templates External Resources K-Dense AI GitHub RDKit Documentation Scanpy Documentation BioPython Tutorial Version History v2.17.0 - Current version with 139 skills Integrated from K-Dense-AI/claude-scientific-skills repository License

MIT License - Open source and freely available for research and commercial use.

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