DeepWiki-rs (Litho)

What this skill does

• •Automatic extraction of architectural relationships from source code
• •Generation of standardized C4 model documentation
• •Support for multi-language repository analysis
• •Dual-model processing for balancing speed and analytical depth
• •Customizable output formatting for project wikis

When to use it

• ✓Generating architectural documentation for onboarding new engineers
• ✓Creating C4 diagrams for complex microservice systems
• ✓Updating legacy codebases that lack maintained technical specs
• ✓Preparing internal project wikis during CI/CD pipelines

When not to use it

• ✕Small projects where the documentation overhead exceeds the codebase size
• ✕Highly ephemeral scripts that undergo daily, radical structure changes
• ✕Projects requiring manual, highly personalized technical storytelling

How to invoke it

Example prompts that trigger this skill:

• “Analyze the current directory and generate documentation to the default output folder.”
• “Run a deep analysis on the /src folder using both an efficient and a powerful AI model.”
• “Perform a quick scan of the codebase without full architectural research.”
• “Generate full project documentation, skipping the initial preprocessing phase for speed.”
• “Create a C4-compliant architectural summary of the entire repository.”

Example workflow

1. Install the binary using 'cargo install deepwiki-rs'.
2. Navigate to the root directory of the project target.
3. Execute 'deepwiki-rs -p .' to initiate the initial scan.
4. Refine results by specifying models with '--model-efficient' and '--model-powerful'.
5. Review the generated 'litho.docs' folder for C4 diagrams and markdown reports.

Prerequisites

• –Rust toolchain (cargo)
• –API keys for supported LLM providers
• –Internet access for AI research and analysis

Pitfalls & limitations

• !Large codebases may encounter API rate limits if not properly batch-configured.
• !Preprocessing phase can be memory-intensive on limited hardware.
• !Requires careful configuration to ensure generated diagrams align with specific company standards.

FAQ

How it compares

Unlike writing documentation manually, Litho ensures technical specs stay synchronized with the actual codebase implementation by generating them directly from source analysis.

Source & trust

From the source: “# Litho (deepwiki-rs) - AI-Powered Documentation Generation ## Quick Start Guide **Use Litho when you need to:** - Analyze entire codebases and generate architecture documentation - Create C4 model diagrams (Context, Container, Component, Code) - Understand complex software systems and module relati…”

# Litho (deepwiki-rs) - AI-Powered Documentation Generation

## Quick Start Guide

**Use Litho when you need to:**
- Analyze entire codebases and generate architecture documentation
- Create C4 model diagrams (Context, Container, Component, Code)
- Understand complex software systems and module relationships
- Generate comprehensive technical specifications
- Document architecture evolution and design decisions

**Core Workflow:**
```bash
# Basic codebase analysis
deepwiki-rs -p ./src

# Complete C4 documentation with dual models
deepwiki-rs -p ./project --model-efficient gpt5-mini --model-powerful gpt5
```

## Decision Tree

### 📋 **Comprehensive Documentation** → Use "Full Litho Workflow"
Generate complete C4 model documentation with architecture diagrams and technical specs.

### ⚡ **Quick Code Analysis** → Use "Basic Analysis Mode"  
Fast code insights without full documentation pipeline.

### 🏗️ **Architecture Understanding** → Use "Advanced C4 Generation"
Deep architectural analysis with detailed component relationships.

### 🔄 **CI/CD Integration** → Use "Automated Pipeline"
Continuous documentation generation for development workflows.

## Key Capabilities

### Multi-Language Support
- Rust, Python, Java, Go, C#, JavaScript/TypeScript
- Any language with recognizable code structure

### Documentation Structure
```
project-docs/
├── 1. Project Overview
├── 2. Architecture Overview  
├── 3. Workflow Overview
└── 4. Deep Dive/
    ├── Topic1.md
    └── Topic2.md
```

### Essential Parameters
- `-p, --path`: Source directory
- `-o, --output`: Output location (default: ./litho.docs)
- `--model-efficient`: Fast model for quick analysis
- `--model-powerful`: Capable model for deep analysis
- `--skip-preprocessing`: Skip initial scanning phase
- `--skip-research`: Skip AI research phase

## Advanced Resources

For detailed configuration, troubleshooting, and advanced patterns:
- See [configuration.md](./configuration.md) for comprehensive setup guides
- See [examples.md](./examples.md) for real-world usage patterns  
- See [integration.md](./integration.md) for CI/CD and automation
- See [troubleshooting.md](./troubleshooting.md) for common issues

## Security & Performance Notes

- Install only from trusted sources
- Use `--model-efficient` for large codebases
- Batch processing helps avoid API rate limits
- Memory-constrained environments: use `--skip-preprocessing`

## Installation
```bash
# Install from crates.io (recommended)
cargo install deepwiki-rs

# Build from source
git clone https://github.com/sopaco/deepwiki-rs.git && cd deepwiki-rs && cargo build --release
```

Quoted from sopaco/deepwiki-rs for reference — see the original for the authoritative, latest version.

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