Aperivue.
51 skills across 1 repo
- 100/100
academic-aio
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.
- 100/100
add-journal
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- 80/100
analyze-stats
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.
- 100/100
architecture-zoo
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- 100/100
author-strategy
PubMed author profile analysis. Author name → PubMed fetch → study-type classification → visualization → strategy report → optional trajectory-archetype classification.
- 100/100
batch-cohort
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.
- 100/100
calc-sample-size
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- 100/100
check-reporting
Check manuscript compliance with medical research reporting guidelines. Supports 47 guidelines including STROBE, STROBE-MR, RECORD, REMARK (prognostic tumor-marker studies), TARGET (target trial emulation), GATHER (burden-of-disease / health-estimate modeling), CONSORT, CONSORT-AI, STARD, STARD-AI, TRIPOD, TRIPOD+AI, TRIPOD-LLM, PGS-RS, ARRIVE, PRISMA, PRISMA-DTA, PRISMA-P, PRISMA-ScR (scoping reviews), CARE, SPIRIT, SPIRIT-AI, CLAIM, DECIDE-AI, MI-CLEAR-LLM, SQUIRE 2.0, CLEAR, MOOSE, GRRAS, SWiM, AMSTAR 2, CHEERS 2022, CROSS (survey studies), SRQR and COREQ (qualitative research), 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.
- 100/100
clean-data
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.
- 100/100
contribute
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- 100/100
cross-national
End-to-end cross-national comparison study using KNHANES + NHANES + CHNS (or other parallel surveys). Variable harmonization, parallel weighted analysis, and comparison tables. Supports 2-country (KR+US) and 3-country (KR+US+CN) designs.
- 100/100
define-variables
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- 100/100
deidentify
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- 100/100
design-ai-benchmarking
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- 100/100
design-study
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- 100/100
explainability
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- 100/100
fill-icmje-coi
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- 100/100
fill-protocol
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- 100/100
find-cohort-gap
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- 100/100
find-journal
Journal recommendation engine for medical manuscripts. 2-pass matching against a curated public profile library plus any user-local private profiles, enriched with detailed write-paper profiles for top-5 output. Returns ranked recommendations with scope fit rationale, AI disclosure policy, and homepage links. Impact-factor and APC figures in a profile are point-in-time and may be stale — verify current metrics at the journal site. A pre-ranking acceptance-readiness pre-flight scans the manuscript for design-ceiling, unfixable-defect, and importance-risk signals to add an acceptance-feasibility axis alongside scope fit, and the output includes a reject-fallback cascade plan.
- 90/100
fulltext-retrieval
Batch download open-access PDFs by DOI using legitimate OA APIs (Unpaywall, PMC, OpenAlex, Crossref). Optional PDF→Markdown conversion for token-efficient LLM analysis.
- 100/100
generate-codebook
Generate a citable data dictionary / codebook from a tabular dataset (CSV/TSV/Excel/Parquet/Stata/SAS). Profiles every variable — role, type, units placeholder, level frequencies, range/quantiles, missingness — and emits codebook.md + codebook.json. Flags coded variables whose level meanings are unknown as [NEEDS DICTIONARY] rather than guessing them, feeding /define-variables and the dictionary-first workflow.
- 100/100
grant-builder
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- 100/100
intake-project
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- 95/100
lit-sync
Sync research references from .bib files to Zotero library + Obsidian literature notes. Extract cross-cutting concept notes when enough literature accumulates. Works after /search-lit or standalone.
- 100/100
ma-scout
Meta-analysis topic discovery and feasibility assessment. Professor-first (profile → gap) or Topic-first (question → gap → co-author). Pre-protocol phase from idea to ranked topic list.
- 100/100
make-figures
Generate publication-ready figures and visual abstracts for medical research papers. Supports ROC curves, forest plots, CONSORT/STARD/PRISMA flow diagrams, calibration plots, Kaplan-Meier curves, Bland-Altman plots, confusion matrices, pipeline diagrams, and journal-specific visual/graphical abstracts (python-pptx template-based).
- 100/100
manage-project
Research project management for medical manuscripts. Scaffold project structure, track writing progress across phases, maintain project memory files, generate submission checklists and backwards timelines. Commands: init, status, sync-memory, checklist, timeline.
- 100/100
manage-refs
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- 100/100
mllm-eval
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- 100/100
model-card
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- 100/100
model-scaffold
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- 100/100
model-validation
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- 100/100
polish-language
Academic English consistency linting and non-native (ESL) language polish for medical manuscripts. Deterministically flags abbreviation define-once violations, US/UK spelling drift, hyphen-vs-en-dash numeric ranges, P/p case, hyphenation variants, small-number style, and value/unit spacing, then guides a style-only clarity pass that never alters numbers, citations, or scientific meaning. Distinct from humanize (AI-tell removal) and check-reporting (guideline items).
- 100/100
preprocess-imaging
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- 100/100
present-paper
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- 100/100
profile-imaging
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- 100/100
publish-skill
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- 100/100
radiomics-ml
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- 100/100
render-pdf-doc
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- 100/100
replicate-study
Replicate an existing cohort study's methodology on a different database. Extracts study design from a source paper, maps variables to the target DB via harmonization table, generates analysis code, and produces a replication difference report.
- 100/100
review-paper
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- 100/100
revise
Parse peer reviewer comments and generate a structured Response to Reviewers document with tracked manuscript changes. Classifies comments as MAJOR/MINOR/REBUTTAL, coordinates new analyses with /analyze-stats and /make-figures, and produces cover letter for editor.
- 100/100
search-lit
Literature search and citation management for medical research. Searches PubMed, Semantic Scholar, and bioRxiv/medRxiv with verified citations. Anti-hallucination — every reference verified via API before inclusion. Generates BibTeX entries.
- 100/100
setup-medsci
Diagnostic checklist for the MedSci Skills runtime. Verifies Python, R, Node, Claude Code, Git, Zotero, and configured MCP servers, and prints a pass/fail table with links to the right setup doc for any missing component. Read-only — does not install anything.
- 100/100
sync-submission
Audit SSOT-to-submission drift and create journal submission manifests from canonical manuscript artifacts.
- 100/100
uncertainty-imaging
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- 100/100
verify-refs
Audit-only verification of manuscript references against PubMed and CrossRef. Detects fabricated or mismatched citations and writes qc/reference_audit.json. Does not modify references/ or refs.bib.
- 100/100
version-dataset
Dataset version control for research reproducibility. Builds a deterministic content-hash manifest of a dataset (file SHA-256 + tabular schema + per-column value hashes), verifies a later copy against it to detect drift (schema change, row-count change, value changes), and diffs two manifests. Use to prove an analysis ran on the intended data, lock a dataset version, or reproducibility-lock bundled demos.
- 100/100
write-paper
Full-pipeline medical/scientific paper writing. 8-phase IMRAD workflow from outline to submission-ready manuscript. Supports original articles, case reports, case series, meta-analyses, AI validation studies, animal studies, and technical notes. Do NOT trigger for self-checking (use self-review instead).
- 100/100
write-protocol
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