What problem does it solve? Understanding an unfamiliar codebase requires manually inspecting configuration files, directory structures, and dependencies, which is slow and error-prone. This Skill automates that discovery process and produces a persistent Markdown report covering technology stack, architecture, dependencies, and quality scores. ## Core Features & Use Cases - Tech Stack & Architecture Detection: Identifies languages, frameworks, build tools, and architecture patterns (MVC, Monorepo, layered architecture) from marker files like package.json, pom.xml, and requirements.txt. - Quality Scoring & Best Practices: Scores documentation, testing, code style, security, and maintainability on a 0-5 scale with an A-D grade, then outputs prioritized improvement suggestions. - Use Case: When joining a new project, ask the AI to analyze the repository and receive a saved Markdown report with a dependency Mermaid diagram, quality scorecard, and high-priority refactoring recommendations. ## Quick Start Ask the AI to analyze the current project and generate a project analysis report in the 文档 directory.