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/smart-docs

AI-powered comprehensive codebase documentation generator. Analyzes project structure, identifies architecture patterns, creates C4 model diagrams, and generates professional technical documentation. Use when users need to document codebases, understand software architecture,

From plugin
deepwiki-rs
3.2k5 skills

Claude Code

$ npx -y skills add sopaco/deepwiki-rs --skill smart-docs --agent claude-code

SKILL.md

smart-docs.SKILL.md
name: smart-docs
description: "AI-powered comprehensive codebase documentation generator. Analyzes project structure, identifies architecture patterns, creates C4 model diagrams, and generates professional technical documentation. Use when users need to document codebases, understand software architecture, create technical specs, or generate developer guides. Supports all programming languages. Alternative to Litho/deepwiki-rs that uses Claude Code subscription without external API costs."
allowed-tools:
  - "Read"
  - "Glob"
  - "Write"
  - "Bash(tree:*)"
  - "Bash(find:*)"
  - "Bash(wc:*)"
  - "Bash(cloc:*)"

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.*`

4. **Read Key Files**: Use Read tool to analyze:

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

5. **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

2. **Map Dependencies**:

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

3. **Detect Architectural Patterns**: Look for:

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

4. **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]

```mermaid
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 Comp
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@sopaco
Ships withdeepwiki-rs

Litho is an AI-powered documentation generation engine that automatically analyzes your source code and generates comprehensive, professional architecture documentation in the C4 model format.

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Questions about smart-docs.

Which coding agents can use smart-docs?
smart-docs installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.