code-dissect

Generate structured analysis reports for AI/ML codebases.

Updated Apr 26, 2026

Search Tags:#mermaid #code-analysis #project-structure #data-flow #report-generation #training-pipeline #ai-repo

Ready to run

npx skills add https://github.com/skywalkjian/skywalkjian-skills --skill code-dissect

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: code-dissect
Source: https://github.com/skywalkjian/skywalkjian-skills/tree/main/ai-code-dissect
Command: npx skills add https://github.com/skywalkjian/skywalkjian-skills --skill code-dissect

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

本技能提供对 AI/ML 代码库的结构化、全面分析，帮助研究人员在不逐行阅读代码的情况下快速理解项目架构、数据流和训练/推理流程。

Core Features & Use Cases

完整的代码库结构分析与可视化，快速把握模块边界
自动定位入口点、数据流路径和关键依赖，清晰呈现训练和推理流程
生成可分享的分析报告，便于团队沟通与评审

Quick Start

将一个代码仓库输入给模型，即可生成完整的项目分析报告。

Frequently Asked Questions about code-dissect

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

FAQPage Schema

How do I analyze an unfamiliar AI repo structure without reading code line by line?▼

To analyze an unfamiliar AI repo structure without reading code line by line, you can generate a comprehensive analysis report that maps module boundaries, entry points, and inter-module relationships. This provides a complete overview of the project architecture.

What is the best way to trace data flow and training pipelines in an ML codebase?▼

Tracing data flow and training pipelines in an ML codebase is best achieved by automating the extraction of data-to-output flow and entry points. This approach clearly visualizes the complete training and inference pipelines without manual code tracing.

Can I automatically generate a visual report of inter-module relationships for an AI project?▼

Yes, you can automatically generate a visual report of inter-module relationships for an AI project. The analysis interprets repository metadata and module connections to outline a complete data-to-output flow, which can be shared for team communication and review.

Does this codebase analysis approach work for complex training and inference pipelines?▼

Yes, this codebase analysis approach works specifically for complex training and inference pipelines. It automatically locates key dependencies and data flow paths within AI/ML repositories to outline the complete pipeline structure.

How do I quickly grasp project structure and module boundaries in a new repository?▼

To quickly grasp project structure and module boundaries in a new repository, generate a structured analysis report. This report dissects repository metadata and inter-module relationships to provide a complete visualization of the project architecture.