git clone --depth 1 https://github.com/Aperivue/medsci-skills /tmp/skills && cp -r /tmp/skills/docs/skills/publish- ~/.claude/skills/skillspublish-skill.md
<!-- AUTO-GENERATED from skills/publish-skill/SKILL.md by scripts/gen_skill_docs.py. Do not edit by hand. --> # publish-skill > Convert a personal agent skill into a distributable, open-source-ready skill. Runs PII audit, generalization, license compatibility check, cross-platform adapter review, and packaging workflow. **Invoke:** `/publish-skill` · **Tools:** Read, Write, Edit, Bash, Grep, Glob · **Model:** inherit ## When to use `publish-skill` activates on requests such as: publish skill, distribute skill, open-source skill, package skill, universalize skill. ## Quality Card **Purpose** — Harden a personal skill for open-source release through a PII audit, generalization, and license/portability checks. **Safety boundaries** - Publication is gated on a passing PII audit; the blocklist is conservative and not weakened to pass. - Personal paths, names, and document metadata are scrubbed before release. **Known limitations** - The audit catches known PII patterns; novel identifiers still need human review. - Generalization preserves behavior but a maintainer should re-read the result. **Validation** - `bash scripts/audit_skill.sh <skill-dir>` - `bash scripts/validate_skills.sh` **Evidence** — `bundled_script` ## Bundled resources **References** (`skills/publish-skill/references/`): - `license-compatibility-matrix.md` - `pii-patterns.md` **Scripts** (`skills/publish-skill/scripts/`): - `audit_skill.sh` ## Source Canonical definition: [`skills/publish-skill/SKILL.md`](../../skills/publish-skill/SKILL.md) --- *Part of [MedSci Skills](../../README.md) — Claude Code skills for the medical research lifecycle. This page is generated from the skill's `SKILL.md`; edit that file and re-run `scripts/gen_skill_docs.py`.*
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.
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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.
Generate N analysis scripts from a single methodology template × multiple exposure/outcome combinations. The "80-person team" pattern — same validated method, swap variables only. Produces batch R/Python code + summary matrix.
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Check manuscript compliance with medical research reporting guidelines. Supports 32 guidelines including STROBE, CONSORT, STARD, STARD-AI, TRIPOD, TRIPOD+AI, ARRIVE, PRISMA, PRISMA-DTA, PRISMA-P, CARE, SPIRIT, CLAIM, MI-CLEAR-LLM, SQUIRE 2.0, CLEAR, MOOSE, GRRAS, SWiM, AMSTAR 2, and risk of bias tools (QUADAS-2, QUADAS-C, RoB 2, ROBINS-I, ROBINS-E, ROBIS, ROB-ME, PROBAST, PROBAST+AI, NOS, COSMIN, RoB NMA). Generates item-by-item assessment with PRESENT/MISSING/PARTIAL status.
Interactive data profiling and cleaning assistant for medical research. Three-stage workflow (profile, flag, code-generate) with user approval gates at each step. Handles missing values, outliers, duplicates, and type mismatches in CSV/Excel clinical data. Does NOT auto-clean — all decisions require researcher confirmation.