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Agent Skill · 前端设计

repowiki(repowiki 命令行)

repowiki 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。

repowiki 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有未通过项,按安装量在前端设计类的 10,216 个 Skill 里排第 5,502。

总安装 659周安装 28GitHub Stars 4下载 231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
unknown

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:repowiki(repowiki 命令行)
来源仓库:https://github.com/zzzhizhia/repowiki
仓库路径:skills/repowiki
安装命令:
npx skills add https://github.com/zzzhizhia/repowiki --skill repowiki
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。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/zzzhizhia/repowiki --skill repowiki

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

repowiki 用于处理 GitHub 仓库、Issue、Pull Request 等协作信息。它适合围绕代码变更和项目状态进行整理。可辅助检查仓库状态或生成协作事项摘要。

安装命令为 npx skills add https://github.com/zzzhizhia/repowiki --skill repowiki。注意权限范围及是否访问私有仓库。

来源仓库内路径:skills/repowiki

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/zzzhizhia/repowiki --skill repowiki;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

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

repowiki 怎么安装?

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

repowiki 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。

repowiki 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

repowiki 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

repowiki 用的人多吗?

公开数据是累计安装 659 次,近一周安装 28 次,下载 231 次,GitHub 4 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。

repowiki 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
repowiki

repowiki 命令行 · 本页

6594需要联网未明确未通过

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

RepoWiki - Repository Report Generator

Generate a DeepWiki-style in-depth analysis report based on the current repository's code structure, configuration files, and dependency relationships.

Report Structure Specification

The generated report must strictly follow the layered structure below, output as a single Markdown file.

Layer 1: Project Overview

# {Project Name}

> {One-line project positioning description}

## Purpose & Scope

{2-3 paragraphs describing what problem the project solves, core value, target users}

## Tech Stack

| Category | Technology | Purpose |
|----------|-----------|---------|
| Language | ... | ... |
| Framework | ... | ... |
| Build Tool | ... | ... |
| Testing | ... | ... |
| Database | ... | ... |

## Repository Structure

{Mermaid graph showing top-level directory structure and module relationships}

## Core Systems Overview

{Mermaid graph showing interactions between major subsystems}

Layer 1.5: Concept & Design Philosophy

Between the project overview and module analysis, add a section that explains the core ideas and technical rationale behind the project — not what it does, but why it was built this way.

## Design Philosophy & Key Decisions

### Core Concept
{1-2 paragraphs explaining the fundamental insight or approach that drives the project's design.
 What problem does the conventional approach have? What alternative mental model does this project adopt?}

### Key Technical Decisions

| Decision | Chose | Over | Rationale |
|----------|-------|------|-----------|
| {e.g., State management} | {Zustand} | {Redux, Context API} | {Why — specific trade-off reasoning} |
| ... | ... | ... | ... |

### Architecture Principles
{2-4 bullet points capturing the non-obvious design principles extracted from the code.
 Each should explain a constraint or convention the codebase follows, and WHY.}

This layer is critical for DeepWiki-quality reports: readers need to understand the "why" before diving into the "what".

Layer 2: Module & Package Analysis

## Module Inventory

| Module | Path | Responsibility | Key Dependencies |
|--------|------|---------------|-----------------|
| ... | ... | ... | ... |

## Module Dependency Architecture

{Mermaid graph: inter-module dependency diagram}

## {Module Name} Detailed Analysis

<details>
<summary>Related Source Files</summary>

- `path/to/file1.ts`
- `path/to/file2.ts`
</details>

### Responsibilities & Boundaries
{What this module is and isn't responsible for}

### Internal Architecture
{Mermaid graph: class/function relationships within the module}

### Key Interfaces
{Code block: main exported APIs, type definitions, interfaces}

### Data Flow
{Mermaid sequence/flowchart: how data flows within the module}

Layer 3: Core System Deep Analysis

Generate an independent section for each core system:

## {System Name}

<details>
<summary>Related Source Files</summary>

- `path/to/relevant/file.ts`
</details>

### Problem & Approach
{Start each core system section with a narrative arc:
 1. What problem does this system solve?
 2. What is the conventional/naive approach, and why doesn't it work here?
 3. What insight or approach does this project use instead?
 This "problem → conventional failure → project's solution" arc is critical for DeepWiki-quality analysis.}

### System Architecture
{Mermaid graph: overall architecture diagram of the system}

### Core Workflows
{Mermaid sequence diagram: main business processes}

### Key Components

| Component | File | Responsibility |
|-----------|------|---------------|
| ... | ... | ... |

### Design Decisions & Trade-offs

| Decision | Chose | Over | Rationale |
|----------|-------|------|-----------|
| ... | ... | ... | ... |

{For each major design decision within this system, explain what was chosen over what alternatives, and why. This comparison table is required for every core system section.}

### Configuration & Extension Points
{Code block: key configuration file snippets}

Layer 4: Infrastructure & Toolchain

## Build System

### Build Pipeline
{Mermaid flowchart: complete process from source to artifacts}

### Build Configuration
{Table: key build configuration items}

## Testing Infrastructure

### Testing Strategy
| Test Type | Tool | Coverage |
|-----------|------|----------|
| Unit Tests | ... | ... |
| Integration Tests | ... | ... |
| E2E Tests | ... | ... |

### Test Configuration
{Code block: key test configuration file snippets}

## CI/CD Pipeline
{Mermaid flowchart: CI/CD process}

## Dependency Management
### Key Dependencies
| Dependency | Version | Purpose |
|-----------|---------|---------|
| ... | ... | ... |

### Dependency Strategy
{Version locking, update strategy, security auditing}

Mermaid Diagram Specifications

IMPORTANT: Mermaid syntax pitfalls to avoid:

  • Do NOT use parentheses () inside node labels or edge labels — they break the parser. Use () (fullwidth) or rephrase instead.
  • Do NOT use special characters {}[]() unescaped inside label strings. Wrap labels in ["..."] if they contain special characters.
  • Always test that your diagram type declaration (graph, flowchart, sequenceDiagram, stateDiagram-v2) matches the syntax used in the body.

Each report must include the following types of diagrams:

1. Repository Structure Diagram (Required)

graph TD
    Root[Project Root]
    Root --> Src[src/]
    Root --> Config[Configuration]
    Root --> Tests[tests/]
    Src --> Core[core/]
    Src --> Utils[utils/]
    Src --> Types[types/]

2. Module Dependency Diagram (Required)

graph LR
    A[Module A] --> B[Module B]
    A --> C[Module C]
    B --> D[Module D]
    C --> D

3. Core Workflow Diagram (Required)

sequenceDiagram
    participant User
    participant API
    participant Service
    participant DB
    User->>API: Request
    API->>Service: Process
    Service->>DB: Query
    DB-->>Service: Result
    Service-->>API: Response
    API-->>User: Return

4. Data Flow Diagram (As Needed)

flowchart LR
    Input[Input] --> Validate[Validate]
    Validate --> Transform[Transform]
    Transform --> Process[Process]
    Process --> Output[Output]

5. State/Lifecycle Diagram (As Needed)

stateDiagram-v2
    [*] --> Created
    Created --> Active
    Active --> Paused
    Paused --> Active
    Active --> Completed
    Completed --> [*]

Analysis Execution Flow

Step 1: Collect Repository Metadata

Use the following tools to gather information (execute in parallel):

  1. Directory Structure - Use Glob to scan **/* for the complete file tree
  2. Package Management - Read package.json, go.mod, Cargo.toml, pyproject.toml, pom.xml, etc.
  3. Configuration Files - Read tsconfig.json, .eslintrc.*, vite.config.*, webpack.config.*, etc.
  4. CI/CD - Read .github/workflows/*, .gitlab-ci.yml, Dockerfile, etc.
  5. Git History - Get file change frequency from the last 100 commits

Step 2: Identify Core Systems

Determine core systems based on the following signals:

SignalWeightMethod
File change frequencyHighgit log statistics
Directory sizeMediumFile count
Entry file referencesHighgrep import/require
README mentionsMediumRead documentation
Export countMediumgrep export

Step 3: Deep Analysis of Each System

For each core system, perform:

  1. Read all files in that directory
  2. Identify main class, function, and type definitions — include file:line references (e.g., src/engine.ts:42) for key definitions so readers can navigate directly to the source
  3. Trace import/export dependency chains
  4. Identify design patterns (Repository, Factory, Observer, etc.)
  5. Extract key configurations and constants
  6. For critical algorithms or workflows, provide step-by-step code logic analysis — trace through the actual implementation, not just describe what it does at interface level

Step 4: Generate Mermaid Diagrams

Based on the analysis results, generate:

  • At least 1 architecture overview diagram
  • At least 1 module dependency diagram
  • At least 1 core workflow sequence diagram
  • Add state diagrams and data flow diagrams as needed

Step 5: Assemble Report

Assemble the complete report according to the structure specification above, output to REPOWIKI.md.

Source File Reference Specification

Each section must include collapsible source file references:

<details>
<summary>Related Source Files</summary>

- `src/core/engine.ts` - Core engine implementation
- `src/core/types.ts` - Type definitions
- `src/config/default.ts` - Default configuration
</details>

Reference rules:

  • Only reference files directly related to the current section
  • Each reference includes a brief description
  • Sort by importance, most critical files first
  • 3-10 referenced files per section

Table Usage Specification

Tables must be used in the following scenarios:

  1. Tech Stack - Inventory of languages, frameworks, and tools
  2. Module Inventory - Paths, responsibilities, and dependencies of all modules
  3. Configuration Comparison - Configuration differences across environments/modes
  4. API Inventory - Methods, parameters, and return values of public APIs
  5. Dependency Inventory - Versions and purposes of key dependencies

Output Requirements

  1. Filename: REPOWIKI.md, placed in the repository root
  2. Language: Match the user's conversation language (Chinese conversation = Chinese report)
  3. Length:

- Small projects (<50 files): 800-1500 lines - Medium projects (50-200 files): 1500-3000 lines - Large projects (>200 files): 3000-6000 lines

  1. Diagram count: At least 3 Mermaid diagrams, 6-10 for large projects
  2. Table count: At least 3 tables
  3. Code blocks: Key configurations and interface definitions, no more than 30 lines each

Quality Checklist

After generating the report, verify the following items:

  • Contains project overview and one-line positioning
  • Tech stack table is complete and accurate
  • Repository structure Mermaid diagram matches reality
  • Each core system has an independent section
  • Each section has collapsible source file references
  • Module dependency diagram correctly reflects actual dependencies
  • At least one sequence diagram shows core workflows
  • All tables are correctly formatted with accurate content
  • Code block syntax highlighting is correct
  • No fabricated files or modules
  • Mermaid diagram syntax is correct and renderable

Example Snippet

Below is a report snippet example for a TypeScript web project:

# MyApp

> A full-stack e-commerce platform built on Next.js, supporting multi-tenancy and real-time inventory management.

## Purpose & Scope

MyApp is an e-commerce SaaS platform for small and medium-sized merchants. It provides
product management, order processing, payment integration, and real-time inventory
synchronization as core features. The project uses Next.js App Router architecture,
Prisma as the ORM, and PostgreSQL as the primary database.

## Tech Stack

| Category | Technology | Purpose |
|----------|-----------|---------|
| Language | TypeScript 5.3 | Full-stack development language |
| Framework | Next.js 14 | Full-stack React framework |
| ORM | Prisma 5.8 | Database access layer |
| Database | PostgreSQL 16 | Primary data storage |
| Cache | Redis 7 | Session and hot data caching |
| Testing | Vitest + Playwright | Unit and E2E testing |

## Repository Structure

graph TD Root["myapp/"] Root --> App["app/ - Next.js App Router"] Root --> Lib["lib/ - Shared Business Logic"] Root --> Components["components/ - UI Components"] Root --> Prisma["prisma/ - Database Schema"] Root --> Tests["tests/ - Test Files"]

App --> API["api/ - API Routes"] App --> Pages["(routes)/ - Pages"] Lib --> Services["services/ - Business Services"] Lib --> Utils["utils/ - Utility Functions"]


## Core Systems Overview

graph LR Client["Client"] --> AppRouter["App Router"] AppRouter --> Auth["Auth System"] AppRouter --> API["API Layer"] API --> OrderService["Order Service"] API --> ProductService["Product Service"] API --> PaymentService["Payment Service"] OrderService --> DB["PostgreSQL"] ProductService --> DB ProductService --> Cache["Redis"] PaymentService --> Stripe["Stripe API"]


## Order System

- `lib/services/order.ts` - Order service core logic
- `app/api/orders/route.ts` - Order API routes
- `prisma/schema.prisma` - Order data model
- `lib/validators/order.ts` - Order data validation
- `components/order/OrderForm.tsx` - Order form component

### Purpose & Scope

The order system manages the complete order lifecycle from shopping cart to payment completion. This includes order creation, inventory locking, payment processing, status transitions, and notification delivery.

### Order Lifecycle

stateDiagram-v2 [*] --> Created: User places order Created --> Paying: Initiate payment Paying --> Paid: Payment successful Paying --> Cancelled: Payment timeout/failure Paid --> Shipping: Merchant ships Shipping --> Completed: Delivery confirmed Completed --> [*] Cancelled --> [*]

Language/Framework Adaptation

Adjust analysis focus based on project type:

Project TypeAnalysis Focus
Node.js/TypeScriptpackage.json, tsconfig, module exports
Gogo.mod, package structure, interface definitions
Pythonpyproject.toml, package structure, class hierarchy
RustCargo.toml, crate structure, trait definitions
Java/Kotlinpom.xml/build.gradle, package structure, class hierarchy
Monorepoworkspace config, inter-package dependencies, build order
Frontend SPArouting structure, state management, component tree
Backend APIroute definitions, middleware chain, data models
CLI Toolcommand structure, argument parsing, subcommands

平台分布

Codex

35.51%
按下载量换算82

Claude

32.81%
按下载量换算76

Cursor

17.02%
按下载量换算39

Gemini CLI

10.45%
按下载量换算24

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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