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Agent Skill · AI 工具

codewiki-generator(代码维基生成器)

codewiki-generator 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

codewiki-generator 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证为 MIT,第三方扫描已通过,按安装量在AI 工具类的 2,536 个 Skill 里排第 1,347。

总安装 816周安装 34GitHub Stars 8下载 272核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:codewiki-generator(代码维基生成器)
来源仓库:https://github.com/samzong/samzong
仓库路径:skills/codewiki-generator
安装命令:
npx skills add https://github.com/samzong/samzong --skill codewiki-generator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/samzong/samzong --skill codewiki-generator

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

Codewiki Generator 生成 DeepWiki 风格的代码优先型文档站点架构。输出包含 VitePress 配置和自动生成侧边栏的完整文档工程目录。必须反映项目当前状态,重点阐述系统设计理念而非仅描述功能特性。首次运行需确认目标语言偏好,后续流程将据此调整所有输出内容语种。

codewiki-generator 属于AI 工具类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/codewiki-generator

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/samzong/samzong --skill codewiki-generator;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

codewiki-generator 怎么安装?

在终端执行 npx skills add https://github.com/samzong/samzong --skill codewiki-generator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

codewiki-generator 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

codewiki-generator 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

codewiki-generator 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

codewiki-generator 用的人多吗?

公开数据是累计安装 816 次,近一周安装 34 次,下载 272 次,GitHub 8 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

codewiki-generator 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理AI 工具类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
codewiki-generator

代码维基生成器 · 本页

8168只读MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Codewiki Generator

Overview

Generate a DeepWiki-style, code-first documentation site for a given repository. The output will reside in the codewiki/ directory, including a VitePress configuration and an auto-generated sidebar. The documentation must reflect the project's current state and prioritize explaining the system's design rationale over merely describing its functionality.

Workflow

0) Confirm Language Preference

Ask the user: "What language should the documentation be written in? (e.g., English, 中文, 日本語, etc.)" IF the user specifies a language THEN store the provided language and apply it to all generated prose content. ELSE IF the user does not specify a language THEN default to English.

1) Inspect the Codebase First (Code > Docs)

  • Scan source files, configuration files, build/test pipelines, entry points, and architectural directories.
  • Treat existing documentation (e.g., README, docs/) as secondary hints.
  • Prioritize code evidence as the ultimate source of truth.
  • Identify and report any discrepancies between documentation and code.

2) Analyze Codebase → Structured Metadata

Execute the analyzer script to scan the codebase and generate structured metadata. <skill-root> refers to the directory containing this SKILL.md.

python3 <skill-root>/scripts/codewiki_analyze.py \
  --repo-root <repo-root> \
  --out-dir codewiki \
  --force

This command generates the following outputs:

  • codewiki/.meta/ directory containing deps.json, entrypoints.json, evidence.json, doc_plan.json, and symbols.json (if ctags is available).
  • codewiki/quality-report.md detailing coverage and pages with low confidence.
  • VitePress configuration scaffolding, without placeholder .md files.

Note: This step does not generate placeholder .md files. The LLM is responsible for writing documentation content directly in Step 4. Note: Images referenced in existing Markdown files are copied into codewiki/assets/.

3) Dynamically Determine the Documentation Set

  • Include all minimally required pages.
  • Add conditional modules only when corresponding code evidence exists.
  • Split or merge pages based on project size and complexity.
  • Adhere to the guidelines specified in references/structure-and-heuristics.md.
  • Use lowercase directory and file names for all generated documentation.

4) Write the Documentation (Code-first, Visual-first)

Read codewiki/.meta/doc_plan.json and process each planned page:

  • IF a page has no supporting evidence OR low relevance to the codebase THEN skip that page.
  • ELSE create an .md file only for pages containing actual content.

Writing guidelines:

  • Use the language determined in Step 0 for all prose content.
  • Retain original formatting for code snippets, file paths, and technical terms.
  • Start every page with a low-contrast # Related Code block (fenced text block), not a heading.
  • Utilize Mermaid for diagrams (context, class, sequence, component, dataflow).
  • Adhere to Mermaid-safe syntax: use simple node IDs, avoid /, (), and : in labels, and prefer node[plain label].
  • Explain the rationale behind design choices, trade-offs, and constraints.
  • Provide informed opinions: highlight strengths, technical debt, or "code smells."
  • Link concepts to specific file paths, classes, or entry points.
  • Reuse existing images/diagrams IF they are accurate.
  • Maintain Markdown lint-friendly practices: consistent headings, no trailing spaces, and proper list formatting.

Refer to references/doc-templates.md for detailed, evidence-linked page templates.

5) Refresh Sidebar and Run the Site

After documentation generation, update the sidebar to reflect the actual files:

python3 <skill-root>/scripts/codewiki_bootstrap.py \
  --repo-root <repo-root> \
  --out-dir codewiki \
  --refresh-sidebar

Install documentation dependencies (Mermaid support is enabled by default):

npm --prefix codewiki install

Launch the documentation site:

npm --prefix codewiki run docs:dev

Alternative launch command (without prior npm install):

npx -p vitepress -p vitepress-plugin-mermaid -p mermaid vitepress dev codewiki

6) Offer Optional Workflows

After the site is operational, inform the user about available options:

"Documentation site is ready! You can now:

  • Option A: Deploy to Cloudflare Pages — publish the site to a live URL
  • Option B: Add multi-language support (i18n) — translate docs to another language

Let me know if you'd like to proceed with any of these."

Optional Workflows

These workflows are available for execution after the core documentation generation process is complete.

Option A) Deploy to Cloudflare Pages

Deploy the documentation site to Cloudflare Pages using the wrangler CLI.

Trigger: The user requests to deploy, publish, or host the documentation.

See: references/deploy-cloudflare.md for comprehensive instructions (including wrangler installation, login verification, build process, deployment, and updating index.md with the live URL).

Option B) Add Multi-language Support (i18n)

Translate existing documentation into a second language and configure the VitePress language switcher.

Trigger: The user requests translation, multi-language, or internationalization (i18n) support.

See: references/i18n-setup.md for comprehensive instructions (including directory structure, VitePress locales configuration, and translation guidelines).

Quality Bar (Non-negotiable)

  • Visual First: Prioritize diagrams over extensive text blocks.
  • Insightful: Explain design intent beyond mere mechanics.
  • Opinionated: Highlight architectural strengths and identified risks.
  • Linked: Reference concrete files/classes for all key concepts.
  • Code-first: The codebase is the authoritative source; documentation serves as a complementary explanation.

Resources

scripts/

  • codewiki_analyze.py: Scans the codebase and generates .meta/*.json metadata files.
  • codewiki_bootstrap.py: Scaffolds the codewiki/ directory, copies referenced images, and generates the sidebar.

references/

  • structure-and-heuristics.md: Contains rules for module selection and signal identification.
  • doc-templates.md: Provides comprehensive, evidence-linked templates for all page types.
  • deploy-cloudflare.md: Details the workflow for deploying to Cloudflare Pages.
  • i18n-setup.md: Outlines the configuration process for multi-language support.

assets/

  • vitepress/: Contains minimal VitePress configuration and a landing page template.

平台分布

windsurf

31.74%
按下载量换算86

Claude Code

22.35%
按下载量换算61

Antigravity

17.65%
按下载量换算48

OpenCode

12.34%
按下载量换算34

Gemini CLI

7.89%
按下载量换算21

trae

3.16%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

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