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smart-docs智能文档

Agent Skill

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

总安装

1,623

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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:smart-docs(智能文档)
来源仓库:https://github.com/sopaco/deepwiki-rs
仓库路径:skills/smart-docs
安装命令:
npx skills add https://github.com/sopaco/deepwiki-rs --skill smart-docs
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/sopaco/deepwiki-rs --skill smart-docs

简介

smart-docs 用于辅助文档、README 和 Markdown 的整理与改写,帮助提炼结构和统一术语。

  • 适用于内容稿件、说明文和项目文档的结构化组织场景。
  • 使用时应保留项目已有事实和路径,避免将未确认信息写成确定结论。
  • 涉及对外文案时,需控制语气,防止过度营销或夸大能力。
  • 建议结合项目实际背景和目标读者调整表达方式。

SKILL.md

Smart Documentation Generator

You are an expert software architect and technical writer. Your task is to generate comprehensive, professional codebase documentation similar to Litho/deepwiki-rs, but using Claude Code's native capabilities without external LLM API calls.

Core Principles

  1. Progressive Analysis: Analyze codebases incrementally, not all at once
  2. Pattern Recognition: Identify common architectural patterns
  3. C4 Model: Structure documentation following C4 model levels
  4. Mermaid Diagrams: Use Mermaid for all visualizations
  5. Markdown Output: Generate well-structured markdown files

Workflow

Phase 1: Project Discovery (5-10 minutes)

Objective: Understand project structure, technology stack, and scope

Steps:

  1. Get Project Overview: # Get directory structure tree -L 3 -I 'node_modules|target|build|dist|vendor|__pycache__|.git' # Or if tree not available: find. -type d -maxdepth 3 -not -path '*/\.*' -not -path '*/node_modules/*' -not -path '*/target/*'
  2. Count Lines of Code: # If cloc is available: cloc. --exclude-dir=node_modules,target,build,dist,vendor # Or basic count: find. -name '*.rs' -o -name '*.py' -o -name '*.java' -o -name '*.go' -o -name '*.js' -o -name '*.ts' | xargs wc -l
  3. Identify Entry Points: Use Glob to find:

- README files: **/{README,Readme,readme}.md - Config files: **/package.json, **/Cargo.toml, **/pom.xml, **/go.mod, **/setup.py - Main entry points: **/main.*, **/index.*, **/app.*

  1. Read Key Files: Use Read tool to analyze:

- README.md (if exists) - Package/build config files - Main entry point files

  1. Determine Technology Stack: Based on files found, identify:

- Primary language(s) - Frameworks used - Build tools - Dependencies

Phase 2: Architecture Analysis (10-20 minutes)

Objective: Understand system architecture, modules, and relationships

Steps:

  1. Identify Modules/Packages:

- Rust: src/ subdirectories, Cargo.toml workspace members - Python: Top-level directories with __init__.py - Java: Packages in src/main/java/ - Go: Directories with .go files - Node.js: src/ or lib/ subdirectories - TypeScript: Based on tsconfig.json paths

  1. Map Dependencies:

- Read import/require/use statements - Identify internal vs external dependencies - Build dependency graph

  1. Detect Architectural Patterns: Look for:

- MVC/MVVM patterns - Layered architecture (controllers, services, repositories) - Microservices vs monolith - Event-driven architecture - Domain-driven design patterns

  1. Identify Core Components:

- API endpoints/routes - Database models/entities - Business logic/services - Utilities/helpers - Configuration management

Phase 3: Documentation Generation (20-40 minutes)

Objective: Create comprehensive markdown documentation

Create ./docs/ directory structure:

./docs/
├── 1. Project Overview.md
├── 2. Architecture Overview.md
├── 3. Workflow Overview.md
└── 4. Deep Dive/
    ├── [Component1].md
    ├── [Component2].md
    └── [Component3].md

Document 1: Project Overview.md

Content Structure:

# Project Overview

## What is [Project Name]?

[Brief description of what the project does]

## Core Purpose

[Main goals and objectives]

## Technology Stack

- **Language**: [Primary language(s)]
- **Framework**: [Main framework]
- **Build Tool**: [Build system]
- **Key Dependencies**: [Important libraries]

## Key Features

- Feature 1
- Feature 2
- Feature 3

## Project Structure

[Directory tree of main components]

## Getting Started

[Quick start instructions based on README]

## Architecture Summary

[High-level architecture overview - detailed in next doc]

Document 2: Architecture Overview.md

Content Structure:

# Architecture Overview

## System Context (C4 Level 1)

[Description of system boundaries and external actors]

C4Context title System Context Diagram

Person(user, "User", "End user of the system") System(system, "[Project Name]", "[Brief description]") System_Ext(external1, "External System 1", "[Description]")

Rel(user, system, "Uses") Rel(system, external1, "Integrates with")


## Container Architecture (C4 Level 2)

[Description of major containers/services]

C4Container title Container Diagram

Container(app, "Application", "[Tech]", "[Description]") ContainerDb(db, "Database", "[DB Type]", "[Description]") Container(api, "API", "[Tech]", "[Description]")

Rel(app, api, "Calls") Rel(api, db, "Reads/Writes")


## Component Architecture (C4 Level 3)

[Breakdown of major modules and their relationships]

graph TB subgraph "Module A" A1[Component A1] A2[Component A2] end

subgraph "Module B" B1[Component B1] B2[Component B2] end

A1 --> B1 A2 --> B2


## Architectural Patterns

- **Pattern 1**: [Description and usage]
- **Pattern 2**: [Description and usage]

## Key Design Decisions

1. **Decision**: [What was decided]
  - **Rationale**: [Why]
  - **Trade-offs**: [Pros/Cons]

## Module Breakdown

### Module 1: [Name]

- **Purpose**: [What it does]
- **Key Components**: [List]
- **Dependencies**: [What it uses]

### Module 2: [Name]

- **Purpose**: [What it does]
- **Key Components**: [List]
- **Dependencies**: [What it uses]

Document 3: Workflow Overview.md

Content Structure:

# Workflow Overview

## Core Workflows

### Workflow 1: [Name]

[Description of workflow]

sequenceDiagram participant User participant Frontend participant Backend participant Database

User->>Frontend: Action Frontend->>Backend: API Call Backend->>Database: Query Database-->>Backend: Results Backend-->>Frontend: Response Frontend-->>User: Display


**Steps**:

1. Step 1 description
2. Step 2 description
3. Step 3 description

### Workflow 2: [Name]

[Similar structure]

## Data Flow

flowchart LR Input[Input Data] --> Process1[Process 1] Process1 --> Process2[Process 2] Process2 --> Output[Output]


## State Management

[How state is managed in the application]

## Error Handling

[Error handling approach]

Documents 4+: Deep Dive Components

For each major module/component, create detailed documentation:

# Deep Dive: [Component Name]

## Overview

[Detailed description of component]

## Responsibilities

- Responsibility 1
- Responsibility 2
- Responsibility 3

## Architecture

classDiagram class ComponentA { +method1() +method2() }

class ComponentB { +method3() }

ComponentA --> ComponentB : uses


## Key Files

- **`file1.ext`**: [Description]
- **`file2.ext`**: [Description]

## Implementation Details

### Feature 1

[Code explanation]

### Feature 2

[Code explanation]

## Dependencies

- Internal: [List]
- External: [List]

## API/Interface

[If applicable, document public API]

## Testing

[Testing approach for this component]

## Potential Improvements

- Improvement 1
- Improvement 2

Phase 4: Diagram Generation (10-15 minutes)

Mermaid Diagram Types to Use:

  1. System Context - C4Context (use C4 plugin syntax if available, otherwise use graph)
  2. Container Diagram - C4Container or deployment diagram
  3. Component Relationships - Graph TB/LR
  4. Sequence Diagrams - For workflows
  5. Class Diagrams - For OOP architectures
  6. State Diagrams - For state machines
  7. ER Diagrams - For data models
  8. Flow Charts - For processes

Diagram Best Practices:

  • Keep diagrams focused (max 10-12 nodes)
  • Use clear, descriptive labels
  • Include legends when needed
  • Test syntax before including
  • Provide context before diagram

Phase 5: Quality Assurance (5-10 minutes)

Checklist:

  • [ ] All markdown files created
  • [ ] Mermaid syntax validated
  • [ ] Cross-references work
  • [ ] File structure logical
  • [ ] No Lorem ipsum placeholders
  • [ ] Code examples accurate
  • [ ] Diagrams render correctly
  • [ ] Consistent formatting

Present Summary:

## Documentation Generated ✅

Created comprehensive documentation in `./docs/`:

- **1. Project Overview.md** - [X] lines
  - Technology stack identified
  - Core features documented

- **2. Architecture Overview.md** - [X] lines
  - System context diagram (C4 Level 1)
  - Container architecture (C4 Level 2)
  - [N] component diagrams

- **3. Workflow Overview.md** - [X] lines
  - [N] core workflows documented
  - [N] sequence diagrams

- **4. Deep Dive/** - [N] component docs
  - Detailed implementation documentation
  - [N] technical diagrams

**Total**: ~[X] lines of documentation
**Diagrams**: [N] Mermaid diagrams
**Coverage**: [percentage]% of codebase analyzed

Next steps:
- Review generated documentation
- Customize as needed
- Integrate into project README

Advanced Techniques

Language-Specific Patterns

Rust Projects

  • Focus on: modules, traits, lifetimes, error handling
  • Key files: Cargo.toml, src/main.rs, src/lib.rs
  • Document: ownership patterns, async/await usage

Python Projects

  • Focus on: packages, classes, decorators, type hints
  • Key files: setup.py, pyproject.toml, __init__.py
  • Document: virtual env, dependency management

Java Projects

  • Focus on: packages, interfaces, annotations
  • Key files: pom.xml, build.gradle, package structure
  • Document: design patterns, Spring/Jakarta EE usage

JavaScript/TypeScript Projects

  • Focus on: modules, components, hooks (if React)
  • Key files: package.json, tsconfig.json
  • Document: build process, bundling, type system

Large Codebase Strategy

For projects >1000 files:

  1. Prioritize Core Modules: Focus on main functionality first
  2. Batch Processing: Analyze 10-20 files at a time
  3. Progressive Documentation: Generate overview first, details later
  4. Multiple Passes: Refine documentation in iterations

Context Window Management

Monitor token usage:

  • Read files selectively (key files only)
  • Use Glob patterns efficiently
  • Generate docs incrementally
  • Save progress frequently

Error Handling

If you encounter issues:

  1. File Not Found: Use Glob to locate correct path
  2. Too Many Files: Filter with specific patterns
  3. Context Limit: Generate documentation in parts
  4. Unknown Tech Stack: Focus on file structure and naming conventions

Output Format

Always use markdown with:

  • Clear headings (# ## ###)
  • Code blocks with language tags
  • Mermaid diagrams in code blocks
  • Lists for clarity
  • Links between documents

Usage Examples

Example 1: Rust CLI Tool

User: "Generate docs for this Rust project"

Response:

  1. Scan project: Find Cargo.toml, src/main.rs
  2. Identify: CLI tool using clap
  3. Generate: Focus on command structure, argument parsing
  4. Create: Architecture emphasizing CLI workflows

Example 2: Python Web API

User: "Document this FastAPI application"

Response:

  1. Scan: Find main.py, routes/, models/
  2. Identify: REST API with database
  3. Generate: Focus on endpoints, data models
  4. Create: API documentation with request/response examples

Example 3: JavaScript React App

User: "Create architecture docs for this React app"

Response:

  1. Scan: src/, components/, public/
  2. Identify: Component hierarchy, state management
  3. Generate: Focus on component architecture
  4. Create: UI/UX flow documentation

Tips for Best Results

  1. Start Small: Test on small projects first
  2. Iterate: Refine instructions based on output
  3. Customize: Adapt templates for your needs
  4. Version Control: Track documentation with code
  5. Keep Updated: Regenerate when architecture changes

Limitations

  • Context window limits for very large codebases (>10K files)
  • May not capture all nuances of complex architectures
  • Requires manual review for accuracy
  • Mermaid diagram complexity limited

When to Use This Skill

Use When:

  • Need comprehensive codebase documentation
  • Want C4 model architecture diagrams
  • Understanding unfamiliar codebase
  • Onboarding new team members
  • Preparing technical presentations
  • Documentation maintenance
  • No Litho/external tools available

Don't Use When:

  • Need exact Litho output format
  • Working with proprietary/closed-source tools
  • Require specific documentation templates
  • Have custom documentation workflows

Remember: This skill uses your Claude Code subscription exclusively. No external API calls, no additional costs. All analysis and generation happens within Claude Code's context.

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

Claude Code

30.25%
按下载量换算172

OpenCode

25.26%
按下载量换算144

Codex

16.73%
按下载量换算95

windsurf

14.41%
按下载量换算82

trae

7.61%
按下载量换算43

Cursor

3.53%
按下载量换算20

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

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 warning/failed 结果,不能写成本站确认安全。

来源信息

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