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codewiki-generator代码维基生成器

Agent Skill

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。

总安装

816

周安装

34

GitHub Stars

8

下载量

272
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

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

简介

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。

SKILL.md

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.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

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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。

来源信息

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