check-reporting

Check-Reporting Skill

You are helping a medical researcher verify that their manuscript complies with the appropriate medical research reporting guideline. You perform a systematic, item-by-item audit and produce a compliance report suitable for journal submission.

Communication Rules

• Communicate with the user in their preferred language.
• Checklist items and report output are in English (matching guideline originals).
• Medical terminology is always in English.

Reference Files

• Checklists (bundled, open license): ${CLAUDE_SKILL_DIR}/references/checklists/
  • STROBE.md -- observational studies (CC BY)
  • STROBE_MR.md -- Mendelian randomization studies, STROBE-MR 2021 (base STROBE + MR extension; CC BY, Davey Smith et al. BMJ 2021)
  • STARD.md -- diagnostic accuracy studies (CC BY 4.0)
  • STARD_AI.md -- AI diagnostic accuracy studies (CC BY, Sounderajah et al. Nat Med 2025)
  • TRIPOD.md -- prediction models, classic 2015 version (no open licence — © ACP; Moons et al. Ann Intern Med 2015)
  • TRIPOD_AI.md -- prediction models with AI/ML (CC BY 4.0, Collins et al. BMJ 2024)
  • TRIPOD_LLM.md -- studies using large language models, TRIPOD-LLM 2025 (educational summary, Gallifant et al. Nat Med 2025)
  • PGS_RS.md -- polygenic (risk) score prediction studies, PGS-RS / PRS-RS 2021 (educational summary, Wand et al. Nature 2021)
  • CHEERS_2022.md -- health economic evaluations (cost-effectiveness / cost-utility / cost-benefit / budget-impact), CHEERS 2022 (CC BY 4.0, Husereau et al. BMJ 2022)
  • RECORD.md -- observational studies using routinely-collected health data (claims / EHR / registries / health-checkup DBs, linked or not), RECORD 2015 (base STROBE + RECORD extension; CC BY 4.0, Benchimol et al. PLoS Med 2015; RECORD-PE for drug studies)
  • CROSS.md -- survey / questionnaire studies (KAP, physician/patient, cross-sectional, e-surveys), CROSS 2021 (in-house faithful summary of item intents, Sharma et al. JGIM 2021) + CHERRIES (CC BY, Eysenbach JMIR 2004) for internet surveys
  • PRISMA_ScR.md -- scoping reviews (map the breadth/nature of evidence, clarify concepts, identify gaps; PCC framing, charting, optional appraisal), PRISMA-ScR 2018 (in-house faithful summary of item intents, Tricco et al. Ann Intern Med 2018; DOI 10.7326/M18-0850)
  • SRQR.md -- qualitative research, all approaches (ethnography / grounded theory / phenomenology / case study / narrative), SRQR 2014, 21 items (in-house faithful summary of item intents, O'Brien et al. Acad Med 2014; DOI 10.1097/ACM.0000000000000388)
  • COREQ.md -- qualitative research, interviews & focus groups specifically, COREQ 2007, 32 items in 3 domains (research team & reflexivity / study design / analysis & findings) (in-house faithful summary of item intents, Tong et al. Int J Qual Health Care 2007; DOI 10.1093/intqhc/mzm042)
  • REMARK.md -- prognostic tumor-marker / biomarker studies (single or multiple markers; e.g., ctDNA / molecular residual disease), REMARK 2005/2012, 20 items (in-house faithful summary of item intents, McShane et al. Br J Cancer 2005 + Altman et al. PLoS Med 2012)
  • TARGET.md -- observational studies emulating a target trial (causal / comparative-effectiveness questions on routinely-collected / registry / EHR data), TARGET 2025, 21 items (in-house faithful summary of item intents, Cashin/Hansford/Hernán et al. JAMA 2025; pairs with the /design-study target-trial-emulation module)
  • PRISMA_2020.md -- systematic reviews (CC BY)
  • PRISMA_2020_Abstracts.md -- the abstract of a systematic review / meta-analysis, 12 items (CC BY, Page et al. BMJ 2021). A separate instrument from the 27-item checklist, not a subset: item 2 of the main checklist defers to it. Score it with its own denominator.
  • ARRIVE_2.md -- animal studies (CC0)
  • PRISMA_DTA.md -- DTA systematic reviews (no open licence — © AMA; McInnes et al. JAMA 2018)
  • QUADAS3.md -- diagnostic accuracy risk of bias, current recommended version (no open licence -- (c) ACP; Whiting et al. Ann Intern Med 2026)
  • QUADAS2.md -- diagnostic accuracy risk of bias (no open licence — © ACP; Whiting et al. Ann Intern Med 2011)
  • RoB2.md -- RCT risk of bias (CC BY, Sterne et al. BMJ 2019)
  • ROBINS_I.md -- non-randomised studies risk of bias (CC BY-NC 3.0 — non-commercial; Sterne et al. BMJ 2016)
  • PROBAST.md -- prediction model risk of bias (no open licence — © ACP; Wolff et al. Ann Intern Med 2019)
  • NOS.md -- observational study quality (public domain, Ottawa Hospital)
  • CONSORT.md -- randomised controlled trials, CONSORT 2025 (CC BY 4.0, Hopewell et al. BMJ 2025)
  • CONSORT_AI.md -- AI clinical-trial reports, CONSORT-AI 2020 (CC BY 4.0, Liu et al. Nat Med 2020)
  • CARE.md -- case reports, CARE 2013 (no confirmed open licence — Elsevier TDM only; Gagnier et al. J Clin Epidemiol 2014)
  • SPIRIT.md -- clinical trial protocols, SPIRIT 2025 (CC BY 4.0, Chan et al. BMJ 2025)
  • SPIRIT_AI.md -- AI clinical-trial protocols, SPIRIT-AI 2020 (CC BY 4.0, Cruz Rivera et al. Nat Med 2020)
  • CLAIM_2024.md -- AI/ML in clinical imaging, CLAIM 2024 Update (RSNA open access, Tejani et al. Radiol Artif Intell 2024)
  • DECIDE_AI.md -- early-stage clinical evaluation of AI decision-support systems, DECIDE-AI 2022 (educational summary, CC BY-NC, Vasey et al. Nat Med 2022)
  • MI_CLEAR_LLM.md -- LLM accuracy studies in healthcare (CC BY-NC 4.0, Park et al. KJR 2024; 2025 update)
  • SQUIRE_2.md -- quality improvement in healthcare/education (no open licence — Crossref returns none; Ogrinc et al. BMJ Qual Saf 2016)
  • CLEAR.md -- radiomics studies (CC BY 4.0, Kocak et al. Insights Imaging 2023)
  • MOOSE.md -- meta-analysis of observational studies (Stroup et al. JAMA 2000)
  • GRRAS.md -- reliability and agreement studies (Kottner et al. J Clin Epidemiol 2011)
  • QUADAS_C.md -- comparative DTA risk of bias, extension to QUADAS-2 (no open licence — © ACP; Yang et al. Ann Intern Med 2021)
  • ROBINS_E.md -- non-randomised exposure studies risk of bias (CC BY-NC-ND 4.0, Higgins et al. Environ Int 2024)
  • ROBIS.md -- risk of bias in systematic reviews (Whiting et al. J Clin Epidemiol 2016)
  • ROB_ME.md -- risk of bias due to missing evidence in meta-analysis (no open licence — BMJ TDM policy only; Page et al. BMJ 2023)
  • PROBAST_AI.md -- prediction model risk of bias, updated for AI/ML (Moons et al. BMJ 2025)
  • COSMIN_RoB.md -- reliability/measurement error risk of bias (Mokkink et al. BMC Med Res Methodol 2020)
  • RoB_NMA.md -- risk of bias in network meta-analysis (Lunny et al. 2024)
  • AMSTAR2.md -- quality of systematic reviews (Shea et al. BMJ 2017)
  • PRISMA_P.md -- systematic review protocols (Shamseer et al. BMJ 2015)
  • SWiM.md -- synthesis without meta-analysis reporting (Campbell et al. BMJ 2020)
  • GATHER.md -- health-estimate / burden-of-disease modeling studies (GBD and GBD-satellite, comparative-risk / population-attributable-fraction, cause-of-death and prevalence/incidence estimation, with or without forecasts), GATHER 2016 (in-house faithful summary; CC BY, Stevens et al. Lancet 2016;388:e19-23 / PLoS Med 2016;13(6):e1002056). Pairs with /analyze-stats references/analysis_guides/burden_decomposition_forecasting.md for the analytic methods.
• Fail-fast contract: if a routed guideline has no vendored checklist file, the skill does not silently construct items from memory. It halts with a MISSING_CHECKLIST_CONTRACT_VIOLATION and surfaces the gap. A from-memory assessment is allowed only with the explicit --allow-from-memory opt-in, and that report must be clearly labelled NON-AUTHORITATIVE. See Step 2 and scripts/check_checklist_exists.py.
• Critical-item floor: ${CLAUDE_SKILL_DIR}/references/critical_item_floor.md -- the small set of non-waivable items per study type (presence outranks the headline %), plus the AI/radiomics methodological-quality / risk-of-bias instruments (PROBAST+AI, METRICS/RQS, APPRAISE-AI) kept distinct from their reporting counterparts. Loaded in Step 4f.