scientific-skills/Others/iso-13485-certification/SKILL.md
A toolkit for preparing ISO 13485:2016 certification documentation for medical device QMS. Use when you need to perform a documentation gap analysis, draft or update a Quality Manual, create required procedures/work instructions, build Medical Device Files (MDF), interpret ISO 13485 clauses, or identify missing documents for certification (often triggered by ISO 13485, QMS certification, FDA QMSR, EU MDR, or quality system documentation requests).
npx skillsauth add aipoch/medical-research-skills iso-13485-certificationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Use this skill in any of the following situations:
scripts/gap_analyzer.py to detect missing/covered QMS documents.references/iso-13485-requirements.md.references/mandatory-documents.md.references/gap-analysis-checklist.md.assets/templates/.Note: This repository references a script (
scripts/gap_analyzer.py). If it introduces additional third-party packages, install them per the repository’srequirements.txt(if present). If norequirements.txtexists, the script is expected to run on the Python standard library.
# 1) (Optional) Create and activate a virtual environment
python -m venv .venv
source .venv/bin/activate # macOS/Linux
# .venv\Scripts\activate # Windows PowerShell
# 2) Run the gap analyzer against your existing QMS document folder
python scripts/gap_analyzer.py \
--docs-dir ./my-qms-docs \
--output ./gap-report.json
# 3) Review the output
cat ./gap-report.json
A typical workflow after generating gap-report.json:
references/iso-13485-requirements.mdreferences/mandatory-documents.mdassets/templates/quality-manual-template.mdreferences/quality-manual-guide.mdassets/templates/procedures/document-control-procedure-template.mdassets/templates/procedures/CAPA-procedure-template.mdreferences/gap-analysis-checklist.mdThe gap analysis workflow is designed to answer:
Typical inputs
.md, .txt, .docx, .pdf), including manuals, SOPs, work instructions, and forms.Typical outputs
gap-report.json) that can be summarized into:
This skill emphasizes writing procedures that define what must be done and who is responsible, while keeping detailed step-by-step instructions in work instructions.
When drafting with assets/templates/quality-manual-template.md and references/quality-manual-guide.md, ensure:
For each device type/family, the MDF should consolidate or reference:
This structure supports ISO 13485 expectations and aligns with FDA QMSR’s direction toward consolidated device documentation.
When generating SOPs from templates (e.g., CAPA, document control), the organization must define:
Use references/mandatory-documents.md as the source of truth for:
For detailed clause interpretation, use references/iso-13485-requirements.md.
tools
Generates complete conventional oncology bulk-transcriptome biomarker and hub-gene research designs from a user-provided cancer type and study direction. Always use this skill whenever a user wants to design, plan, or build a tumor bioinformatics study centered on differential expression, prognostic filtering or risk modeling, PPI-based hub-gene prioritization, diagnostic/prognostic evaluation, clinical association, immune infiltration context, methylation context, and optional tissue or cell validation. Covers five study patterns (signature-first prognostic workflow, hub-gene-first biomarker workflow, hybrid signature-to-hub workflow, immune-context biomarker workflow, translational validation workflow) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path...
development
Generates complete conventional non-oncology bioinformatics research designs from a user-provided disease context, process-related gene family or biological theme, and validation direction. Use when a study centers on multi-dataset bulk transcriptome integration, DEG analysis, process-gene intersection, enrichment analysis, GSEA, PPI hub-gene prioritization, TF/miRNA regulatory networks, ROC-based biomarker evaluation, and immune infiltration analysis. Covers five study patterns (process-DEG discovery, enrichment/GSEA interpretation, hub-gene prioritization, regulatory-network and immune interpretation, multi-layer public validation) and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.
tools
Plans confounder control, variable adjustment logic, and bias mitigation strategies at the protocol stage for clinical, epidemiologic, translational, observational, and biomarker studies. Always use this skill when a user needs to identify major confounders, decide which variables should or should not be adjusted for, compare matching/stratification/weighting approaches, anticipate selection or measurement bias, or pressure-test a study design before execution. Focus on bias sensing, causal structure awareness, variable-role classification, and critical design review rather than generic statistical advice.
testing
Generates complete comparative network-toxicology research designs from a user-provided exposure pair, shared toxic phenotype, and validation direction. Use when a study centers on two related exposures under one outcome and needs target collection, shared-vs-specific target decomposition, enrichment, PPI hub prioritization, docking, optional transcriptomic cross-checks, and conservative mechanistic synthesis. Covers five study patterns and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.