Model QA Specialist

Audit ML models end-to-end for governance, data, and performance issues.

Updated Apr 16, 2026

Search Tags:#qa #audit #calibration #drift #model #reproducibility #interpretability

Ready to run

npx skills add https://github.com/jc180105/.opencode --skill model-qa-specialist-jc180105

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Model QA Specialist
Source: https://github.com/jc180105/.opencode/tree/main/.opencode/skills/specialized-model-qa
Command: npx skills add https://github.com/jc180105/.opencode --skill model-qa-specialist-jc180105

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Audits machine learning models end-to-end to uncover hidden issues, quantify impact, and produce audit-grade reporting with evidence.

Core Features & Use Cases

Reproduce model pipelines from documentation to validate data reconstruction, labeling, feature engineering, and training steps.
Perform global and local interpretability checks (SHAP, PDP) and fairness audits across populations.
Generate structured, governance-aligned QA reports with actionable remediation plans and executive summaries.

Quick Start

Initiate Phase 1: define QA scope, collect methodology artifacts, and kick off a full end-to-end audit of the target model.

Frequently Asked Questions about Model QA Specialist

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

FAQPage Schema

How do I audit machine learning models for governance and performance issues?▼

To audit machine learning models, you reproduce pipelines from documentation, validate data reconstruction, perform interpretability checks, and generate governance-aligned QA reports with actionable remediation plans.

How do I reproduce ML pipelines to validate data reconstruction and feature engineering?▼

Reproduce ML pipelines by collecting methodology artifacts, then validating data reconstruction, labeling, feature engineering, and training steps to ensure full reproducibility and identify hidden issues.

Can I use interpretability checks like SHAP and PDP for fairness audits across populations?▼

Yes, you can perform global and local interpretability checks using SHAP and PDP, and conduct fairness audits across populations to uncover hidden issues and quantify impact with evidence.

Does model QA work for classification, regression, forecasting, NLP, and computer vision projects?▼

Model QA applies to classification, regression, forecasting, NLP, and computer vision projects across industries, requiring a documented methodology, reproducible scripts, and robust monitoring aligned with governance standards.

What's the best way to generate audit-grade reporting for ML model drift and calibration?▼

Generate audit-grade reporting by conducting end-to-end model QA that identifies drift and calibration issues, producing structured reports with executive summaries and actionable remediation plans.

Why do I need a documented methodology and reproducible scripts for model auditing?▼

A documented methodology and reproducible scripts are required for model auditing to validate pipeline reconstruction and ensure robust monitoring aligned with governance standards for reproducible QA.