By Centaurioun
Academic presentation and PPTX building, PDF/document rendering, environment setup, and skill publishing.
Intake and normalize a new radiology research project. Classifies project type, summarizes current state, identifies missing inputs, recommends next steps, and scaffolds lightweight project memory files.
Medical AI paper optimization for AI search engines (Perplexity, ChatGPT web, Elicit, Consensus, SciSpace) and RAG-based literature tools. Applies when drafting or reviewing titles, abstracts, structured summary boxes (Key Points / Research in Context / Plain-Language Summary), manuscripts for high-impact medical AI journals (Lancet Digital Health, Radiology, Radiology-AI, npj Digital Medicine, Nature Medicine), preprints (medRxiv/arXiv), GitHub README + CITATION.cff + Zenodo archives, and Hugging Face model/dataset cards. Integrates TRIPOD+AI, CLAIM 2024, STARD-AI, TRIPOD-LLM, DECIDE-AI reporting requirements with generative engine optimization (GEO) principles. Produces a visible pass/fail checklist.
Add a new journal to the MedSci Skills profile database. Extracts metadata from author guidelines, generates write-paper (detailed) and find-journal (compact) profiles in canonical format with quality gates.
Statistical analysis for medical research papers. Generates reproducible Python/R code with publication-ready tables and figures. Supports diagnostic accuracy, inter-rater agreement, meta-analysis, survival analysis, survey data, group comparisons, regression, propensity score, and repeated measures.
PubMed author profile analysis. Author name → PubMed fetch → study-type classification → visualization → strategy report → optional trajectory-archetype classification.
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Executables (bin/) — files in this plugin's bin/directory are added to the Bash tool's PATH while the plugin is enabled.
45 skills that actually work. Built by a physician-researcher, tested on real publications.
MedSci Skills is a submission-grade clinical manuscript workflow, not a generic biomedical skill catalog. Its moat is the compliance layer — 36 reporting guidelines and risk-of-bias tools, reference/citation verification, and deterministic integrity gates, before peer review sees the manuscript. It competes on clinical submission reliability, not skill count.

Topic Discovery → Literature Search → Full-Text Retrieval → Study Design → Sample Size → Protocol → De-identification → Data Cleaning → Statistics → Figures → Writing → Humanize → Compliance → Journal Selection → Peer Review → Revision → Presentation
Created & maintained by Yoojin Nam, MD
Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea

MedSci Skills is an open-source Claude Code skill collection for clinical manuscript preparation. It helps physician-researchers and biomedical investigators move from literature search, study design, statistics, and figures to reporting-guideline compliance, citation/reference auditing, numerical-consistency checks, and response-to-reviewer workflows — combining agentic writing with deterministic integrity gates for submission-grade biomedical research. It is not a diagnostic tool, an autonomous author, or a general AI-scientist platform; every output requires human-expert verification. New here? See the 3 workflows below, the FAQ, and the scope boundary.
No terminal? Use the classroom installer ZIP — download, unzip, double-click the installer, then restart your agent app (see Installation).
Have a terminal? Fastest path — one command, nothing to clone:
npx medsci-skills install # copies every skill into your agent's folder
Have git? Install every skill in three commands:
git clone https://github.com/Aperivue/medsci-skills.git
mkdir -p ~/.claude/skills
cp -r medsci-skills/skills/* ~/.claude/skills/
Restart Claude Code, then start with /orchestrate — it classifies your request and routes you to the right skill. Full install options (Codex, Cursor, individual skills) are in Installation.
npx claudepluginhub centaurioun/medsci-skills --plugin medsci-literatureC/C++ language server (clangd) for code intelligence
Agent that simplifies and refines code for clarity, consistency, and maintainability while preserving functionality
Tools to maintain and improve CLAUDE.md files - audit quality, capture session learnings, and keep project memory current.
Upstash Context7 MCP server for up-to-date documentation lookup. Pull version-specific documentation and code examples directly from source repositories into your LLM context.
Battle-tested Claude Code plugin for engineering teams — 38 agents, 156 skills, 72 legacy command shims, production-ready hooks, and selective install workflows evolved through continuous real-world use
Ultra-compressed communication mode. Cuts 65% of output tokens (measured) while keeping full technical accuracy by speaking like a caveman.
Frontend design skill for UI/UX implementation
Memory compression system for Claude Code - persist context across sessions
Marketing skills for AI agents — conversion optimization, copywriting, SEO, paid ads, ad creative, and growth
Comprehensive UI/UX design plugin for mobile (iOS, Android, React Native) and web applications with design systems, accessibility, and modern patterns
Standalone image generation plugin using Nano Banana MCP server. Generates and edits images, icons, diagrams, patterns, and visual assets via Gemini image models. No Gemini CLI dependency required.