project-analysis

Analyze project directories to generate tech stack, architecture, and quality reports.

Updated Jul 31, 2026
One-click install
npx skills add https://github.com/shengmingzhishu/LeeCommonVideoCut --skill project-analysis-shengmingzhishu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: project-analysis
Source: https://github.com/shengmingzhishu/LeeCommonVideoCut/tree/main/.trae/skills/shared/project-analysis
Command: npx skills add https://github.com/shengmingzhishu/LeeCommonVideoCut --skill project-analysis-shengmingzhishu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

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.

Frequently Asked Questions about project-analysis

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

FAQPage Schema
How do I analyze a project's tech stack automatically?▼

Trigger the analysis by asking to analyze the project or generate project documentation. It scans marker files like package.json, requirements.txt, pom.xml, Cargo.toml, and go.mod to detect languages, frameworks, build tools, and test frameworks.

What does the project quality score include?▼

The quality assessment scores six dimensions from 0 to 5: code organization, documentation completeness, testing, code style, security, and maintainability. Scores are averaged into an overall grade of A, A-, B, B-, C, or D with supporting evidence.

Can I analyze only a subdirectory instead of the whole project?▼

Yes, pass the focus_dir parameter to limit analysis to a specific subdirectory such as src/. Without it, the skill analyzes the entire project root while ignoring directories like node_modules, .git, dist, and build.

How does the analysis handle very large projects?▼

Projects are classified by file count: under 500 files uses deep mode, 500-2000 uses standard, and over 2000 uses quick mode. Quick mode retains core conclusions and risk items while reducing scan depth to stay within time and token limits.

Where is the analysis report saved?▼

Each run must produce one Markdown main report saved by default in the 文档 directory under the project root, named 项目分析-{timestamp}.md. You can override the location with the output_dir parameter.

What happens if the project type cannot be recognized?▼

The analysis degrades to a generic mode and still outputs the main report rather than failing. Dependency parsing failures are marked with their cause while other report sections continue normally.