What it does

This skill transforms your AI agent into an elite Software Quality Director. It performs a deep, evidence-based scan of your repository to generate a professional, repository-aware Software Quality Test Strategy. Unlike generic templates, it maps twenty Carnegie human-centered principles to your specific codebase, ensuring the strategy addresses both technical debt and engineering culture.

How it works

The skill follows a rigorous four-step workflow: repository inspection, maturity assessment, Carnegie principle mapping, and final strategy generation. It analyzes your dependency manifests, CI/CD pipelines, test suites, and high-risk code areas (like auth or payments) to build a grounded "Product Understanding Report."

Why use this skill

Standard AI prompts often yield generic "you should write more tests" advice. This skill is better because it:

• Grounds recommendations in reality: Every suggestion references specific file paths, frameworks, and gaps found in your repo.
• Assesses maturity: It categorizes your project from Level 0 to 5, ensuring the plan is realistic for your current stage.
• Balances Tech and People: It uses Carnegie principles to provide actionable advice on stakeholder engagement and quality culture.

Output

The result is a comprehensive quality-strategy.md file suitable for presentation to CTOs or Engineering Managers, covering test engineering, defect management, and a 30-60-90 day execution plan.