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BC qms-audit-expert

ISO 13485 internal audit expertise for medical device QMS. Use for audit planning and execution, nonconformity classification, CAPA verification, external audit preparation, or audit program management.

borghei/Claude-Skills Agent Skills author: borghei 4 files · 1 script body ≈ 3 772 tokens Open the sourcegithub.com↗ analyzed 7 h ago

ISO 13485 internal audit expertise for medical device QMS.

As a process C 60/100 · Has gaps — References files that are not bundled: ../quality-manager-qms-iso13485/, ../capa-officer/, ../quality-documentation-manager/

AnalyzerQuality controltype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
C
60/100
Has gaps
References files that are not bundled: ../quality-manager-qms-iso13485/, ../capa-officer/, ../quality-documentation-manager/
Tools and files w 18
0
Inputs and preconditions w 11
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../quality-manager-qms-iso13485/
  • warning missing-ref reference to a missing file: ../capa-officer/
  • warning missing-ref reference to a missing file: ../quality-documentation-manager/
  • warning missing-ref reference to a missing file: ../quality-manager-qmr/
  • warning missing-ref reference to a missing file: ../risk-management-specialist/
  • note edit-residue the text marks something as outdated (lines 53, 101): check that old rules are not kept next to new ones — the full check reads the text for contradictions

Process rating: all ten parameters 60/100

Will not run. References files that are not bundled: ../quality-manager-qms-iso13485/, ../capa-officer/, ../quality-documentation-manager/
  • 0Tools and files. 5 referenced file(s) missing: ../quality-manager-qms-iso13485/, ../capa-officer/, ../quality-documentation-manager/
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 1 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 85Steps. 109 steps, 1 vague phrases
  • 100Result and completion. Output format and completion criterion are stated
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3772 tokens
  • 100Progress reporting. Reports progress
  • low 14 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +2Single-language instructions
  • +3Description length 202: enough signal without eating the budget
  • +4Structure: 31 headings
  • +3Step-by-step instructions: 109 items
  • +3Output format is stated explicitly
  • +4Has examples (5 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.