By youyinnn
Skills for scientific visualization, statistical analysis, and interactive plotting
Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.
Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.
Meta-skill for publication-ready figures. Use when creating journal submission figures requiring multi-panel layouts, significance annotations, error bars, colorblind-safe palettes, and specific journal formatting (Nature, Science, Cell). Orchestrates matplotlib/seaborn/plotly with publication styles. For quick exploration use seaborn or plotly directly.
Statistical visualization with pandas integration. Use for quick exploration of distributions, relationships, and categorical comparisons with attractive defaults. Best for box plots, violin plots, pair plots, heatmaps. Built on matplotlib. For interactive plots use plotly; for publication styling use scientific-visualization.
Guided statistical analysis with test selection and reporting. Use when you need help choosing appropriate tests for your data, assumption checking, power analysis, and APA-formatted results. Best for academic research reporting, test selection guidance. For implementing specific models programmatically use statsmodels.
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A curated collection of 50 Claude Code skills organized by research workflow stage, tailored for AI and Medical AI PhD researchers.
| File | Description |
|---|---|
| PLATFORM_GUIDE.en.md | Which skills work in Claude Code vs Claude.ai |
| PLATFORM_GUIDE.zh.md | 平台兼容性指南(中文) |
| recommended_skills_for_medical_ai_phd.en.md | Recommended skills by research stage (English) |
| recommended_skills_for_medical_ai_phd.zh.md | 按研究阶段推荐的 skills(中文) |
| Plugin | Skills | Description |
|---|---|---|
literature-and-topic-selection | 12 | Topic ideation, literature review, academic databases |
data-preparation-and-processing | 12 | Medical imaging, EHR, physiological signals, data processing |
model-development-and-experiments | 11 | Deep learning, GNNs, explainability, time series |
results-analysis-and-visualization | 6 | Plotting, statistical analysis, interactive visualization |
paper-writing-and-submission | 10 | Academic writing, slides, posters, peer review |
/plugin marketplace add youyinnn/skills-collection
/plugin install literature-and-topic-selection@skills-collection
/plugin install data-preparation-and-processing@skills-collection
/plugin install model-development-and-experiments@skills-collection
/plugin install results-analysis-and-visualization@skills-collection
/plugin install paper-writing-and-submission@skills-collection
You can install only the plugins relevant to your current work.
/plugin install literature-and-topic-selection@skills-collection
/plugin install data-preparation-and-processing@skills-collection
/plugin install model-development-and-experiments@skills-collection
/plugin install results-analysis-and-visualization@skills-collection
/plugin install paper-writing-and-submission@skills-collection
| Skill | Purpose |
|---|---|
scientific-brainstorming | Research ideation, finding gaps, cross-disciplinary exploration |
hypothesis-generation | Derive testable hypotheses from data or literature |
literature-review | Systematic review across PubMed / arXiv / bioRxiv |
scientific-critical-thinking | Evaluate study design, identify bias, evidence grading (GRADE) |
citation-management | Reference management workflows |
pyzotero | Programmatic Zotero library management |
arxiv-database | Search arXiv preprints (CS / AI / Statistics) |
pubmed-database | PubMed REST API with Boolean / MeSH queries |
biorxiv-database | Search bioRxiv life science preprints |
openalex-database | Query 240M+ scholarly works, citation analysis |
bgpt-paper-search | Extract structured experiment data from full-text papers |
research-grants | NSF / NIH / DARPA grant writing |
| Skill | Purpose |
|---|---|
pydicom | Read/write DICOM files (CT / MRI / X-Ray / Ultrasound) |
pathml | Computational pathology WSI analysis, 160+ formats |
histolab | Lightweight H&E tile extraction |
imaging-data-commons | Access NIH public medical imaging datasets |
pyhealth | Medical AI toolkit: MIMIC-III/IV, eICU, OMOP |
clinicaltrials-database | Query ClinicalTrials.gov |
clinvar-database | Query ClinVar genetic variants database |
neurokit2 | Physiological signal processing: ECG / EEG / EDA / PPG |
polars | Fast in-memory dataframe processing |
dask | Distributed computing for larger-than-RAM workflows |
exploratory-data-analysis | EDA reports for scientific data formats |
statistical-analysis | Statistical testing and modeling |
| Skill | Purpose |
|---|---|
pytorch-lightning | Structured PyTorch training with logging and checkpointing |
transformers | HuggingFace transformers for NLP and vision tasks |
torch-geometric | Graph neural networks for molecular / biomedical data |
scikit-learn | Classical ML: classification, regression, clustering |
pymc | Bayesian statistical modeling |
shap | Model explainability via Shapley values |
umap-learn | Dimensionality reduction and embedding visualization |
aeon | Time series classification and regression |
networkx | Graph analysis and network science |
primekg | Biomedical knowledge graph for drug discovery |
stable-baselines3 | Reinforcement learning algorithms |
npx claudepluginhub youyinnn/skills-collection --plugin results-analysis-and-visualizationSkills for deep learning, graph neural networks, explainability, time series, and dimensionality reduction
Skills for research topic selection, literature review, and academic database search
Skills for medical imaging, EHR data, physiological signals, and general data processing
Skills for academic writing, venue templates, peer review, and presentation materials
Generate publication-quality academic diagrams, statistical plots, and presentation slides using PaperBanana multi-agent framework
Self-documenting, self-improving framework for analytical repositories
Scientific writing, citations, grants, posters, and academic career (13 skills)
Publication-quality matplotlib/seaborn charts with opinionated aesthetics
Create data visualizations and plots
Research orchestration, project intake and management, research-gap and meta-analysis topic discovery, and author-strategy analysis.