Agent skill

Medical Device Mdr Auditor

by aipoch in aipoch/medical-research-skills

Audit medical device technical files against EU MDR 2017/745 regulations.

MITAuto-check passedResearch & Science

Install Medical Device Mdr Auditor

skills CLI
$ npx skills add aipoch/medical-research-skills --skill medical-device-mdr-auditor -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills medical-device-mdr-auditor --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'scientific-skills/Academic Writing/medical-device-mdr-auditor' .claude/skills/medical-device-mdr-auditor && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
medical-device-mdr-auditor
GitHub stars
1.9k
Token cost
~2.6k tokens
SKILL.md length
1,050 words
Files
5 (incl. scripts, references)
Skills in repo
578
Repo updated
First seen
Licence
MIT

At a glance

Audit medical device technical files against EU MDR 2017/745 regulations.

  • Works in 4 steps: Clinical Evaluation Report (CER) → Post-Market Surveillance Plan (PMS) → Post-Market Clinical Follow-up Plan… → …
  • Research & Science work in your project
  • SKILL.md covers When to Use, Key Features, Dependencies and Example Usage, plus 18 more sections
  • Runs Python scripts from its folder; calls python

What it does

Medical Device Mdr Auditor is an agent skill from aipoch/medical-research-skills. Audit medical device technical files against EU MDR 2017/745 regulations.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `medical-device-mdr-auditor_audit_result_v2.json`, `references/audit-reference.md` and `scripts/main.py`).

It sits in Research & Science. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

  • Research & Science work in your project

Example prompts

  • “/medical-device-mdr-auditor”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Clinical Evaluation Report (CER)
  2. Post-Market Surveillance Plan (PMS)
  3. Post-Market Clinical Follow-up Plan (PMCF Plan)
  4. Other Key Documents

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Medical Device Mdr Auditor loads about 2.6k tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 25 tokens; SKILL.md has 1,050 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~25
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 1,050 words, ~2,622 tokens.

Download SKILL.mdSave it as .claude/skills/medical-device-mdr-auditor/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
medical-device-mdr-auditor
description
Audit medical device technical files against EU MDR 2017/745 regulations.
license
MIT
author
AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Medical Device MDR Auditor

ID: 130
Version: 1.0.0
Description: Check whether medical device technical files contain required documents according to EU MDR (2017/745) regulations


When to Use

  • Use this skill when the task needs Audit medical device technical files against EU MDR 2017/745 regulations.
  • Use this skill for academic writing tasks that require explicit assumptions, bounded scope, and a reproducible output format.
  • Use this skill when you need a documented fallback path for missing inputs, execution errors, or partial evidence.

Key Features

  • Scope-focused workflow aligned to: Audit medical device technical files against EU MDR 2017/745 regulations.
  • Packaged executable path(s): scripts/main.py.
  • Reference material available in references/ for task-specific guidance.
  • Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

See ## Prerequisites above for related details.

  • Python: 3.10+. Repository baseline for current packaged skills.
  • dataclasses: unspecified. Declared in requirements.txt.
  • enum: unspecified. Declared in requirements.txt.

Example Usage

See ## Usage above for related details.

bash
cd "20260318/scientific-skills/Academic Writing/medical-device-mdr-auditor"
python -m py_compile scripts/main.py
python scripts/main.py --help

Example run plan:

  1. Confirm the user input, output path, and any required config values.
  2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
  3. Run python scripts/main.py with the validated inputs.
  4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See ## Workflow above for related details.

  • Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
  • Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
  • Primary implementation surface: scripts/main.py.
  • Reference guidance: references/ contains supporting rules, prompts, or checklists.
  • Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
  • Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.

Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

bash
python -m py_compile scripts/main.py

Audit-Ready Commands

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

bash
python -m py_compile scripts/main.py
python scripts/main.py --help
python scripts/main.py -h

Workflow

  1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
  2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
  3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
  4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
  5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Overview

This Skill is used to audit the compliance of medical device technical files, checking whether documents contain necessary Clinical Evaluation Reports and Post-Market Surveillance plans according to EU MDR 2017/745 regulatory requirements.

Usage

text

# Check single technical file directory
python3 /Users/z04030865/.openclaw/workspace/skills/medical-device-mdr-auditor/scripts/main.py --input /path/to/technical/file --class IIa

# Batch check using JSON configuration file
python3 /Users/z04030865/.openclaw/workspace/skills/medical-device-mdr-auditor/scripts/main.py --config /path/to/config.json

# Output detailed report
python3 /Users/z04030865/.openclaw/workspace/skills/medical-device-mdr-auditor/scripts/main.py --input /path/to/technical/file --class III --verbose --output report.json

Parameters

ParameterTypeRequiredDescription
--inputstringConditionalTechnical file directory path
--configstringConditionalJSON configuration file path
--classstringYesDevice classification (I, IIa, IIb, III)
--outputstringNoOutput report path
--verboseflagNoOutput detailed information

MDR 2017/745 Check Points

1. Clinical Evaluation Report (CER)

According to MDR Annex XIV Part A, must include:

  • Clinical Evaluation Plan
  • Clinical Data Assessment (Literature review / Clinical investigation data)
  • Clinical Evidence Analysis
  • Benefit-risk Conclusion
2. Post-Market Surveillance Plan (PMS)

According to MDR Article 83 & Annex III, must include:

  • PMS procedure description
  • Data collection methods
  • Risk assessment update mechanism
  • Trend reporting mechanism
3. Post-Market Clinical Follow-up Plan (PMCF Plan)

According to MDR Annex XIV Part B, for Class IIa and above devices:

  • PMCF plan document
  • Clinical data continuous collection methods
  • Safety and performance monitoring procedures
4. Other Key Documents
  • Risk Management File (ISO 14971)
  • Usability Engineering File
  • Biological Evaluation Report
  • Labeling & Instructions for Use

Output Format

Compliance Report Example
json
{
  "audit_date": "2026-02-06T06:00:00Z",
  "device_class": "IIa",
  "compliance_status": "PARTIAL",
  "findings": [
    {
      "category": "CRITICAL",
      "regulation": "MDR Annex XIV Part A",
      "item": "Clinical Evaluation Report",
      "status": "MISSING",
      "description": "Clinical evaluation report file not found"
    },
    {
      "category": "MAJOR",
      "regulation": "MDR Article 83",
      "item": "PMS Plan",
      "status": "INCOMPLETE",
      "description": "PMS plan lacks trend reporting mechanism"
    }
  ],
  "summary": {
    "total_checks": 12,
    "passed": 8,
    "warnings": 2,
    "failed": 2
  }
}

Compliance Levels

LevelDescription
COMPLIANTFully compliant with MDR requirements
PARTIALPartially compliant, with correctable deficiencies
NON_COMPLIANTSeriously non-compliant, critical documents missing
Show full SKILL.md (429 more words)Show less

Exit Codes

CodeMeaning
0Audit passed, fully compliant
1Audit passed, with warnings
2Audit failed, with deficiencies
3Execution error

References

  • Regulation (EU) 2017/745 (MDR)
  • MDCG Guidance Documents
  • EN ISO 14971:2019
  • EN ISO 13485:2016

Author

OpenClaw Skill Development Team

Risk Assessment

Risk IndicatorAssessmentLevel
Code ExecutionPython/R scripts executed locallyMedium
Network AccessNo external API callsLow
File System AccessRead input files, write output filesMedium
Instruction TamperingStandard prompt guidelinesLow
Data ExposureOutput files saved to workspaceLow

Security Checklist

  • No hardcoded credentials or API keys
  • No unauthorized file system access (../)
  • Output does not expose sensitive information
  • Prompt injection protections in place
  • Input file paths validated (no ../ traversal)
  • Output directory restricted to workspace
  • Script execution in sandboxed environment
  • Error messages sanitized (no stack traces exposed)
  • Dependencies audited

Prerequisites

text

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics
  • Successfully executes main functionality
  • Output meets quality standards
  • Handles edge cases gracefully
  • Performance is acceptable
Test Cases
  1. Basic Functionality: Standard input → Expected output
  2. Edge Case: Invalid input → Graceful error handling
  3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

  • Current Stage: Draft
  • Next Review Date: 2026-03-06
  • Known Issues: None
  • Planned Improvements:
    • Performance optimization
    • Additional feature support

Output Requirements

Every final response should make these items explicit when they are relevant:

  • Objective or requested deliverable
  • Inputs used and assumptions introduced
  • Workflow or decision path
  • Core result, recommendation, or artifact
  • Constraints, risks, caveats, or validation needs
  • Unresolved items and next-step checks

Error Handling

  • If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
  • If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
  • If scripts/main.py fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
  • Do not fabricate files, citations, data, search results, or execution outcomes.

Input Validation

This skill accepts requests that match the documented purpose of medical-device-mdr-auditor and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

medical-device-mdr-auditor only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

References

Response Template

Use the following fixed structure for non-trivial requests:

  1. Objective
  2. Inputs Received
  3. Assumptions
  4. Workflow
  5. Deliverable
  6. Risks and Limits
  7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (scripts, references) in scientific-skills/Academic Writing/medical-device-mdr-auditor of aipoch/medical-research-skills.

  • SKILL.md
  • medical-device-mdr-auditor_audit_result_v2.json
  • references/audit-reference.md
  • requirements.txt
  • scripts/main.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Medical Device Mdr Auditor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Medical Device Mdr Auditor compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Medical Device Mdr Auditor this skillaipoch/medical-research-skills1.9k—~2.6kAutomated safety check: PassMIT
Hypothesis Generationspacering-net/codeg3.9k14 repos~3.6kAutomated safety check: NotesMIT
GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
Nature Paper CardYuan1z0825/nature-skills47k2 repos~2.1kAutomated safety check: PassApache-2.0
Content Research Writerweapp-tailwindcss/weapp-tailwindcss1.9k25 repos~3.5kAutomated safety check: PassMIT
Last30daysmvanhorn/last30days-skill64k—~7.9kAutomated safety check: NotesMIT

Similar skills

  • Hypothesis Generation

    spacering-net/codeg

    Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.

    3.9k GitHub starsUsed in 14 repos~3.6k tokens
    Research & ScienceAuto-check: notes
  • GitHub Deep Research

    bytedance/deer-flow

    Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.

    84k GitHub starsUsed in 4 repos~1.3k tokens
    Research & ScienceAuto-check passed
  • Nature Paper Card

    Yuan1z0825/nature-skills

    Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source.

    47k GitHub starsUsed in 2 repos~2.1k tokens
    Research & ScienceAuto-check passed
  • Content Research Writer

    weapp-tailwindcss/weapp-tailwindcss

    Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section.

    1.9k GitHub starsUsed in 25 repos~3.5k tokens
    Research & ScienceAuto-check passed
  • Last30days

    mvanhorn/last30days-skill

    Research what people actually say about any topic in the last 30 days.

    64k GitHub stars~7.9k tokensUpdated yesterday
    Research & ScienceAuto-check: notes
  • Peer Review

    spacering-net/codeg

    Structured manuscript/grant review with checklist-based evaluation.

    3.9k GitHub starsUsed in 17 repos~5.9k tokens
    Research & ScienceAuto-check: notes

More from aipoch/medical-research-skills

All 578 skills in this repo
  • Academic Poster Generator

    aipoch/medical-research-skills

    Complete workflow for generating academic research posters from PDF literature; use when you need to extract paper content from PDFs and produce a LaTeX-based poster…

    1.9k GitHub stars~2.2k tokensUpdated 24 days ago
    Auto-check passed
  • Diagnostic Study Quality Assessment Quadas

    aipoch/medical-research-skills

    Analyzes clinical diagnostic accuracy studies for bias using the QUADAS-2 tool.

    1.9k GitHub stars~1.4k tokensUpdated 24 days ago
    Auto-check passed
  • Exploratory Data Analysis

    aipoch/medical-research-skills

    Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats.

    1.9k GitHub stars~3.7k tokensUpdated 24 days ago
    Auto-check passed
  • Iso Certification

    aipoch/medical-research-skills

    A toolkit for preparing ISO 13485:2016 certification documentation for medical device QMS.

    1.9k GitHub stars~1.8k tokensUpdated 24 days ago
    Auto-check passed
  • Journal Skills

    aipoch/medical-research-skills

    Recommends target journals for manuscript submission by analyzing the paper topic/abstract and the journal distribution of similar PubMed literature; use when users ask for journal…

    1.9k GitHub stars~1.7k tokensUpdated 24 days ago
    Auto-check passed
  • Latex Posters

    aipoch/medical-research-skills

    Creates academic-poster writing packages for LaTeX using beamerposter, tikzposter, or baposter.

    1.9k GitHub stars~1.3k tokensUpdated 24 days ago
    Auto-check passed

Questions about Medical Device Mdr Auditor

What does Medical Device Mdr Auditor do?

Audit medical device technical files against EU MDR 2017/745 regulations. Medical Device Mdr Auditor is an agent skill from aipoch/medical-research-skills. Audit medical device technical files against EU MDR 2017/745 regulations.

When should I use Medical Device Mdr Auditor?

Medical Device Mdr Auditor fits situations like: research & Science work in your project.

How do I install Medical Device Mdr Auditor in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill medical-device-mdr-auditor -a claude-code`. Or copy the skill folder (scientific-skills/Academic Writing/medical-device-mdr-auditor in aipoch/medical-research-skills) into .claude/skills/medical-device-mdr-auditor in your project. Claude Code loads it when a task matches its description.

How do I install Medical Device Mdr Auditor in Codex?

Run `npx skills add aipoch/medical-research-skills --skill medical-device-mdr-auditor -a codex`. Or copy the skill folder (scientific-skills/Academic Writing/medical-device-mdr-auditor in aipoch/medical-research-skills) into .agents/skills/medical-device-mdr-auditor in your project. Codex loads it when a task matches its description.

Can I use Medical Device Mdr Auditor in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill medical-device-mdr-auditor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/medical-device-mdr-auditor, .gemini/skills/medical-device-mdr-auditor, .github/skills/medical-device-mdr-auditor and .opencode/skills/medical-device-mdr-auditor in your project.

What does Medical Device Mdr Auditor need to run?

Going by SKILL.md and its folder, Medical Device Mdr Auditor needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Medical Device Mdr Auditor access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Medical Device Mdr Auditor safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Medical Device Mdr Auditor use?

Medical Device Mdr Auditor is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Medical Device Mdr Auditor use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 172 tokens, read only when the agent opens those files.

What are the alternatives to Medical Device Mdr Auditor?

Skills that share tags, products or a category with Medical Device Mdr Auditor: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Medical Device Mdr Auditor?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,937 GitHub stars. The repository holds 578 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.