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product-reverse

product-reverse is an agent skill for reverse-engineering web products from a URL.

product-reverse 是一个面向 AI agent 的技能,用于从 URL 逆向分析 Web 产品。

Project Positioning | 项目定位

This repository publishes a single production-ready skill: product-reverse. It is designed for Claude/Codex-style agents to analyze product UX, infer API/data patterns, and output actionable build docs.

本仓库发布一个可直接使用的单技能:product-reverse。 它用于帮助 Claude/Codex 类 agent 分析产品体验、推断 API/数据模型,并生成可落地的实现文档。

Quick Install | 快速安装

Install from the current repository:

npx skills add rxdaozhang/product-reverse

Install only this skill explicitly:

npx skills add rxdaozhang/product-reverse --skill product-reverse

Usage Examples | 使用示例

  • "Analyze this product and tell me how it works."
  • "Reverse engineer this site."
  • "Help me clone this product."

可用中文示例:

  • “分析这个产品的交互和技术栈”
  • “帮我逆向这个网站并输出设计文档”

Repository Structure | 仓库结构

.
├── AGENTS.md
├── .well-known/skills/index.json
├── skills/
│   └── product-reverse/
│       ├── SKILL.md
│       ├── references/
│       │   ├── chrome-patterns.md
│       │   ├── design-doc-template.md
│       │   └── report-template.md
│       └── scripts/
│           └── summarize_state.py
└── scripts/
    ├── validate-skill.sh
    └── smoke-install.sh

Directory Compatibility | 收录兼容说明

This repo is aligned with common ecosystem expectations:

  • skills.sh / npx skills discovery (SKILL.md with name + description)
  • repository-level agent guidance (AGENTS.md)
  • machine-readable discovery endpoint (.well-known/skills/index.json)

该仓库已对齐主流收录需求:

  • 兼容 skills.sh / npx skills 的技能发现机制
  • 提供仓库级 agent 说明入口(AGENTS.md
  • 提供可机器读取的索引(.well-known/skills/index.json

Quality Checks | 质量校验

bash scripts/validate-skill.sh
bash scripts/smoke-install.sh

Contribution & Release | 贡献与发布

  • Keep skill name and path stable unless there is a breaking-change plan.
  • If changing discovery metadata, update README.md, AGENTS.md, and .well-known/skills/index.json together.
  • Run quality checks before commit and push.

License

MIT

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