academic-aio
Use when a medical AI paper should be found and cited by AI search engines and RAG tools. Optimizes the title, abstract, summary…
Use when auditing a manuscript item by item against a reporting guideline or risk-of-bias tool. Covers 49 reporting guidelines and risk-of-bias tools (STROBE, CONSORT, STARD, TRIPOD+AI, PRISMA, QUADAS and more), marking each item PRESENT, PARTIAL or MISSING. Not a reviewer
$ npx -y skills add Aperivue/medsci-skills --skill check-reporting --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/check-reportingContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when auditing a manuscript item by item against a reporting guideline or risk-of-bias tool. Covers 49 reporting guidelines and risk-of-bias tools (STROBE, CONSORT, STARD, TRIPOD+AI, PRISMA, QUADAS and more), marking each item PRESENT, PARTIAL or MISSING. Not a reviewer
name: check-reporting description: Use when auditing a manuscript item by item against a reporting guideline or risk-of-bias tool. Covers 49 reporting guidelines and risk-of-bias tools (STROBE, CONSORT, STARD, TRIPOD+AI, PRISMA, QUADAS and more), marking each item PRESENT, PARTIAL or MISSING. Not a reviewer critique (/self-review). metadata: triggers: "checklist, QUADAS-3, abstract checklist, structured abstract, reporting guideline, STROBE, STROBE-MR, Mendelian randomization, CONSORT, CONSORT-AI, STARD, STARD-AI, TRIPOD, TRIPOD-LLM, PGS-RS, PRS-RS, polygenic risk score, polygenic score, PRISMA, PRISMA-DTA, PRISMA-P, PRISMA-ScR, scoping review, scoping, evidence map, ARRIVE, CARE, CLAIM, DECIDE-AI, MI-CLEAR-LLM, SPIRIT, SPIRIT-AI, QUADAS, QUADAS-C, RoB, ROBINS, ROBINS-E, ROBIS, ROB-ME, PROBAST, NOS, COSMIN, AMSTAR, SWiM, CHEERS, economic evaluation, cost-effectiveness, cost-utility, QALY, ICER, RECORD, RECORD-PE, routinely-collected data, registry, claims, electronic health records, EHR, real-world data, CROSS, CHERRIES, survey, questionnaire, KAP, e-survey, response rate, SRQR, COREQ, qualitative research, interviews, focus groups, thematic analysis, grounded theory, reflexivity, REMARK, tumor marker, prognostic marker, prognostic biomarker, molecular residual disease, TARGET, target trial emulation, target trial, causal inference, estimand, immortal time bias, GATHER, burden of disease, global burden, GBD, health estimates, attributable burden, comparative risk assessment, population attributable fraction, disability-adjusted life years, DALY, forecasting, decomposition, risk of bias, compliance check, LLM accuracy, large language model, clinical deployment"
Checklists are vendored under `${CLAUDE_SKILL_DIR}/references/checklists/`, one file per instrument. Each file's header gives its version, source citation and licence, and says when its item text is an own-words summary rather than the published wording.
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If a checklist already exists for this project (`qc/reporting_checklist.json` or a prior `.md` report), verify it targets the **current** manuscript before reusing it — one generated against an older version carries stale section/line references and a stale version label:
python3 "${CLAUDE_SKILL_DIR}/scripts/check_checklist_version.py" \
--checklist qc/reporting_checklist.json --manuscript manuscript_v8.mdA non-zero exit means the checklist is stale (older `target_version`, changed `source_sha256`, different `target_manuscript`) or pre-dates the version contract: regenerate it against the current manuscript (Steps 1–5) rather than reusing it. Every report you generate carries the `target_manuscript` / `target_version` / `source_sha256` fields (Part A header + Part D JSON) so this check works next round.
Use the guideline the user names; otherwise auto-detect it from the study type. If the study type is ambiguous, ask the user to confirm before selecting a guideline.
**Auto-detection mapping:**
| Study Type | Primary Guideline | AI Extension | |------------|------------------|--------------| | Observational study | STROBE | -- | | Mendelian randomization study | STROBE-MR (base STROBE + MR extension) | -- | | Health economic evaluation (cost-effectiveness / cost-utility / cost-benefit / budget-impact) | CHEERS 2022 | -- | | Observational study using routinely-collected data (claims / EHR / registry / health-checkup DB) | RECORD (base STROBE + RECORD extension; RECORD-PE for drug studies) | -- | | Survey / questionnaire study (KAP, physician/patient, cross-sectional, e-survey) | CROSS (+ CHERRIES for internet surveys) | -- | | Scoping review (maps breadth/nature of evidence, clarifies concepts, identifies gaps — not a focused effectiveness/accuracy question) | PRISMA-ScR (base PRISMA + scoping-review extension) | -- | | Qualitative study (interviews, focus groups, ethnography, grounded theory, phenomenology, document analysis) | SRQR (all qualitative approaches); COREQ (interviews/focus groups specifically) | -- | | Randomized controlled trial | CONSORT 2025 | CONSORT-AI | | Diagnostic accuracy study | STARD 2015 | STARD-AI | | Prediction
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 a set of Agent Skills for clinical research: literature
Use when a medical AI paper should be found and cited by AI search engines and RAG tools. Optimizes the title, abstract, summary…
Use when a target journal has no profile yet. Reads the journal's author guidelines and writes a detailed /write-paper profile…
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Use when analyzing a researcher's publication record from PubMed. Fetches an author's papers, classifies study types and author…
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