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ISO Standards Readiness Evidence Prep

Structures scope, controlled documents, traceability, CAPA and supplier evidence into a reviewable draft package for ISO 13485, 14971, 17025 and 15189.

Docs & OfficeAdvanced★ 33,030⑂ 3,248AI score 8/10Last updated: Aug 9, 2026

What it does

  • Runs an 8-step workflow: declare standard/lane/owners → freeze source and edition baseline → inventory controlled documents and records → review process implementation with sampled records → run lane-specific checks → handle regulator evidence (US FDA QMSR) separately → assemble a bounded evidence manifest → controlled human handoff.
  • Ships deterministic, stdlib-only Python CLIs (validate_scope_intake.py, audit_document_records.py, check_traceability.py, check_capa.py, check_supplier_controls.py, check_qmsr_transition.py, validate_evidence_manifest.py, gap_analyzer.py) that read bounded local JSON, make no network calls, and reject symlinks, unsafe paths and unlisted standards.
  • Enforces assurance-lane hygiene: organizations are certified, laboratories are accredited; ISO certification never displaces FDA inspection or CLIA.
  • Reproduces no ISO clause text (copyright-safe) and labels every output as draft material for authorized human review.

Who it's for

  • RA/QA and quality managers at medical device manufacturers
  • Testing, calibration and medical laboratories preparing for ISO/IEC 17025 or ISO 15189 accreditation
  • Consultants and internal auditors assembling pre-assessment evidence packages

Examples

  1. ISO 13485 pre-assessment: fill the scope-intake template, run validate_scope_intake.py --standard iso-13485, and surface unresolved applicability items as explicit blockers for management review.
  2. CAPA and supplier sweep: run check_capa.py and check_supplier_controls.py to flag CAPAs lacking effectiveness evidence and critical suppliers without risk-based controls or approvals.
  3. ISO 17025 accreditation prep: build an evidence manifest, validate it with --standard iso-17025 --verify-files, then run gap_analyzer.py for a domain-level gap report that marks unlisted domains not-assessed rather than compliant.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/HEAD/skills/iso-standards-readiness/SKILL.md

What I want: (describe your task here)

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↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on Claude Skill Mart.
Copy the skills/iso-standards-readiness folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/iso-standards-readiness/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git /tmp/scientific-agent-skills && mkdir -p ~/.claude/skills && cp -r /tmp/scientific-agent-skills/skills/iso-standards-readiness ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Open a terminal in your working directory.
  2. Clone the repository: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  3. Create the skills directory: mkdir -p ~/.claude/skills
  4. Copy this skill only: cp -r scientific-agent-skills/skills/iso-standards-readiness ~/.claude/skills/
  5. Verify Python 3.11 or newer: python3 --version
  6. Restart Claude Code and ask something like "help me prepare ISO 13485 readiness evidence" to trigger the skill.
  7. Copy any template out of the skill folder into your controlled workspace before filling it in — never edit a distributed template into a purported approved record.
View source on GitHub ↗License: MIT