quality-nonconformance

Guide NCR investigations through containment, RCA, and CAPA closure.

1|Updated Mar 3, 2026
One-click install
npx skills add https://github.com/samymity/bridge-ventures-backend --skill quality-nonconformance-samymity
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: quality-nonconformance
Source: https://github.com/samymity/bridge-ventures-backend/tree/main/.claude/skills/quality-nonconformance
Command: npx skills add https://github.com/samymity/bridge-ventures-backend --skill quality-nonconformance-samymity

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps quality and compliance teams contain non-conforming product, determine appropriate disposition, perform rigorous root cause analysis, and close CAPAs effectively to prevent recurrence in regulated manufacturing.

Core Features & Use Cases

  • NCR lifecycle guidance: Capture traceability, define scope, manage containment, and document MRB disposition decisions (use-as-is, rework, repair, RTV/SCAR, scrap).
  • Root cause analysis playbooks: Select and apply 5-Whys, Ishikawa (fishbone), Fault Tree Analysis, and 8D with common failure modes to avoid “symptom-only” conclusions.
  • CAPA effectiveness & SPC interpretation: Define initiation triggers, corrective vs preventive actions, verification vs validation of effectiveness, and how to respond to Western Electric SPC signals.
  • Supplier quality management: Audit methodology, supplier scorecards, CAR/SCAR escalation, and approved supplier list decisions tied to performance.
  • Regulatory and industry alignment: Practical mapping to FDA 21 CFR 820, IATF 16949, AS9100, and ISO 13485 expectations for documentation and timing.

Quick Start

Use the quality-nonconformance skill to draft an NCR investigation plan, MRB disposition rationale, RCA method selection, and a CAPA with defined verification and effectiveness criteria based on the specific non-conformance details.

Frequently Asked Questions about quality-nonconformance

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I conduct a root cause analysis for a non-conformance report?

To conduct RCA for an NCR, select an appropriate method like 5-Whys, Ishikawa, fault tree, or 8D based on complexity. This structure ensures you identify true underlying causes rather than symptoms, enabling effective corrective and preventive actions.

What is the best way to manage an MRB disposition for non-conforming product?

Managing an MRB disposition requires structuring containment and evaluating the non-conforming product to determine the appropriate outcome, such as use-as-is, rework, repair, RTV/SCAR, or scrap, based on severity classification and documented traceability.

How do I write a CAPA with effectiveness verification for manufacturing quality?

Writing a CAPA with effectiveness verification requires defining corrective and preventive actions, then establishing clear verification and validation criteria to confirm the actions worked. This ensures the CAPA closure effectively prevents recurrence in regulated manufacturing.

Does this NCR investigation approach support FDA 21 CFR 820 and ISO 13485 compliance?

Yes, this NCR investigation approach supports FDA 21 CFR 820, ISO 13485, IATF 16949, and AS9100 compliance by aligning documentation, MRB dispositions, and CAPA timing expectations directly with regulated manufacturing standards.

When do I need to use 8D methodology versus 5-Whys for supplier quality issues?

You need to use 8D methodology versus 5-Whys for supplier quality issues based on complexity; 8D provides a comprehensive team-based containment and prevention framework for complex failures, while 5-Whys is suited for straightforward symptom-only conclusions.

How do I respond to Western Electric SPC signals during in-process testing?

Responding to Western Electric SPC signals during in-process testing involves initiating an NCR investigation to contain the variation, classify severity, and apply root cause analysis. This ensures statistical process control deviations are formally investigated and resolved.