deepwiki-rs

🥈Silver

Deepwiki-rs automates technical documentation generation from code. It creates accurate, structured docs for human teams and AI agents. Integrates with Claude and other LLMs to streamline knowledge sharing in operations.

887870Updated Today

Intermediate30min to implementautomation

Saves ~90 min per use

Quick InstallView Source

git clone https://github.com/sopaco/deepwiki-rs.git

Works with:

Claude

Overview

About This Skill

./README.md

How to Use

["1. **Prepare Your Codebase**: Ensure your codebase is well-organized and includes comments for better documentation generation.","2. **Identify Key Modules**: Determine which modules or components you want to document. Focus on the most critical parts of your codebase.","3. **Use the Prompt Template**: Copy the prompt template and fill in the placeholders with your specific codebase and module details.","4. **Generate Documentation**: Paste the completed prompt into Claude or another LLM and let it generate the documentation.","5. **Review and Refine**: Review the generated documentation for accuracy and completeness. Make any necessary adjustments to ensure it meets your needs."]

Use Cases

Automatically generate architecture documentation from your existing codebase.

Create professional C4 model diagrams that illustrate the structure of your application.

Integrate with CI/CD pipelines to ensure documentation is updated with every code commit.

Enhance code reviews by providing clear and concise architectural context.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/sopaco/deepwiki-rs

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Generate technical documentation for the [CODEBASE] repository. Focus on the [SPECIFIC_MODULE] module. Include architecture diagrams, API specifications, and usage examples. Ensure the documentation is structured for both human engineers and AI agents to understand. Output the documentation in Markdown format.

Example Output

```markdown
# [CODEBASE] - [SPECIFIC_MODULE] Documentation

## Overview
The [SPECIFIC_MODULE] module is responsible for handling data processing and transformation within the [CODEBASE] repository. It integrates with various data sources and provides a unified interface for data manipulation.

## Architecture
The module follows a microservices architecture with the following components:
- **Data Ingestion Service**: Handles data ingestion from multiple sources.
- **Transformation Service**: Processes and transforms the ingested data.
- **API Gateway**: Provides a unified interface for interacting with the module.

```

## API Specifications
### Data Ingestion Service
- **Endpoint**: `/api/ingest
- **Method**: POST
- **Description**: Ingests data from various sources.
- **Request Body**: JSON object containing data source details.
- **Response**: 200 OK on success, 400 Bad Request on failure.

### Transformation Service
- **Endpoint**: `/api/transform
- **Method**: POST
- **Description**: Processes and transforms the ingested data.
- **Request Body**: JSON object containing data to be transformed.
- **Response**: 200 OK on success, 400 Bad Request on failure.

## Usage Examples
### Ingesting Data
```bash
curl -X POST -H "Content-Type: application/json" -d '{"source": "database", "query": "SELECT * FROM users"}' http://localhost:8080/api/ingest
```

### Transforming Data
```bash
curl -X POST -H "Content-Type: application/json" -d '{"data": "raw_data"}' http://localhost:8080/api/transform
```

## Integration with AI Agents
The documentation is structured to be easily understood by AI agents, enabling them to assist with data processing tasks and provide insights based on the module's functionality.
```