code-analyzer

Name: code-analyzer
Availability: InStock
Author: yun520-1

Analyze codebases for architectural patterns, code quality, and DDD elements.

38|8|Updated Mar 28, 2026

Search Tags:#code quality #architecture #static analysis #code analysis #DDD

Ready to run

npx skills add https://github.com/yun520-1/mark-heartflow-skill --skill code-analyzer-yun520-1

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: code-analyzer
Source: https://github.com/yun520-1/mark-heartflow-skill/tree/main/skills/code-analyzer
Command: npx skills add https://github.com/yun520-1/mark-heartflow-skill --skill code-analyzer-yun520-1

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires ast, pdfplumber, json, argparse, collections, dataclasses, datetime, re, sys, os, pathlib, typing, and includes scripts (resource) and references (resource) components.

What problem does it solve?

The Code Analyzer Skill streamlines the process of code analysis to enhance code maintainability and uncover insights hidden in complex codebases.

Core Features & Use Cases

Deep Code Analysis: Perform comprehensive codebase analysis including architecture, data flow, and business logic.
Quality Assessment: Evaluate code quality based on maintainability, testability, and complexity.
DDD Pattern Recognition: Identify domain-driven design patterns (such as aggregates, entities, and value objects) within the codebase.
Use Case: For a new code project, the Skill can provide a comprehensive analysis report highlighting potential architectural improvements and areas for code refactoring.

Quick Start

Analyze your codebase with the code-analyzer skill and receive a detailed report.

Frequently Asked Questions about code-analyzer

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

FAQPage Schema

How do I perform static code analysis to assess code quality and architecture?▼

Static code analysis evaluates codebases to identify architectural patterns and assess quality without executing the code. It provides a detailed report highlighting potential architectural improvements and areas for refactoring to enhance maintainability.

Can I detect domain-driven design patterns like aggregates and entities in my codebase?▼

Yes, domain-driven design pattern recognition identifies aggregates, entities, and value objects within the codebase. It extracts these DDD elements during deep analysis to help you understand your business logic and data flow structure.

Does code analysis support multiple programming languages or just Python?▼

Code analysis operates on multiple programming languages to identify architectural patterns and assess quality. However, you need a Python environment to execute the analysis scripts and generate the comprehensive maintainability report.

What's the best way to evaluate code maintainability and testability for a new project?▼

Evaluating code maintainability and testability requires a comprehensive codebase analysis based on complexity metrics. It delivers a detailed report highlighting architectural improvements and refactoring areas to streamline code insights.

Do I need to run my code to identify architectural patterns and data flow issues?▼

No, architectural pattern identification and data flow analysis rely entirely on static analysis tools to detect issues without running the code. This approach safely uncovers hidden insights in complex codebases.

What dependencies are required to extract domain-driven design elements from source files?▼

Extracting domain-driven design elements requires Python dependencies including ast and pdfplumber, alongside standard libraries like json, re, and pathlib. These modules enable the static analysis scripts to parse code structures and generate reports.