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AI FeaturesDocument Generation

Document Generation

Automatically generate comprehensive documentation from your codebase using AI-powered analysis of modules, dependencies, and semantic information.

Overview

Document Generation analyzes your codebase and automatically creates detailed documentation for each module. The system combines code analysis with AI to produce professional, structured documentation that follows best practices.

Privacy & Security: Your code is temporarily checked out for analysis, processed, and then immediately deleted. We only store the generated documentation, never your source code.

Automatic Updates: Documentation is automatically updated when you push changes to your repository, keeping your docs in sync with your code.

How Document Generation Works

🔍 Code Analysis

Analyzes your codebase to extract modules, dependencies, and semantic information

🧠 AI Processing

Uses AI to understand code structure and generate human-readable documentation

📚 Structured Output

Generates documentation following consistent structure and formatting standards

🔄 Auto-Updates

Automatically updates documentation when you push changes to your repository

Document Generation Process

1

Repository Analysis

Analyzes your GitHub repository to understand the codebase structure
2

Module Extraction

Identifies modules, their exports, imports, and dependencies
3

Semantic Analysis

Extracts detailed information about functions, classes, interfaces, and types
4

AI Documentation Generation

Uses AI to generate comprehensive documentation based on the analyzed code structure
5

Document Storage

Saves generated documentation and makes it available in your Simplistica workspace. Your source code is deleted after analysis.

Supported Languages & Frameworks

📘TypeScript

  • Full TypeScript support with type information
  • Interface and type definitions
  • Class inheritance and implementations
  • Generic types and constraints
  • Namespace and module declarations

JavaScript

  • ES6+ module analysis
  • Function and class extraction
  • Import/export tracking
  • CommonJS and ES modules
  • Async/await and Promise handling

⚛️React & JSX

  • React component documentation
  • Props and state analysis
  • Hook usage and patterns
  • JSX element extraction
  • Component lifecycle methods

📁Project Types

  • Node.js applications and APIs
  • Frontend applications (React, Next.js)
  • Libraries and SDKs
  • CLI tools and utilities
  • Monorepos and multi-package projects

Generated Documentation Structure

📋Standard Documentation Sections

Overview

Module purpose, responsibilities, and system context

Public Exports

All exported functions, classes, types, and constants with signatures

Usage Examples

Code examples showing how to use the module

Dependencies

Internal and external module dependencies with links

Limitations

Known limitations, edge cases, and important considerations

Source Files

Links to GitHub source files and relevant code

Analysis Features

🔬Complete Analysis

  • Full repository analysis
  • All modules and dependencies
  • Comprehensive semantic extraction
  • Role analysis and categorization
  • Best for initial documentation generation

Smart Updates

  • Automatic change detection
  • Efficient processing for updates
  • Maintains existing documentation
  • Updates affected modules
  • Best for ongoing maintenance

Module Analysis Features

📊 Dependency Graph

Maps internal and external dependencies between modules

🎯 Role Analysis

Identifies module roles (utility, service, component, etc.) with confidence scores

🔍 Semantic Extraction

Extracts detailed information about functions, classes, and types

📈 Module Insights

Provides insights into module structure, dependencies, and relationships

How to Generate Documentation

🚀Start Document Generation

1

Configure GitHub Integration

Set up GitHub Personal Access Token and repository access in Auto-Docs settings
2

Start Analysis

Navigate to the Analyzer page and start a new analysis for your repository
3

Monitor Progress

Track analysis progress and wait for completion (can take several minutes for large repositories)
4

Review Generated Docs

Access generated documentation in your workspace and review the results
5

Automatic Updates

Documentation automatically updates when you push changes to your repository

Documentation Quality Standards

🏗️Structure & Organization

  • Clear hierarchical structure with consistent headings
  • Logical flow from overview to implementation details
  • Modular sections that can be easily navigated
  • Consistent formatting across all documents

Clarity & Readability

  • Simple, precise language without ambiguity
  • Clear definitions of key terms and concepts
  • Proper code formatting and syntax highlighting
  • Accessible to developers of different skill levels

🎯Context & Completeness

  • Sufficient background for new readers
  • Links to related modules and external resources
  • Practical usage examples and patterns
  • Coverage of edge cases and limitations

🤖AI Readiness

  • Structured format for automated parsing
  • Consistent section markers and formatting
  • Machine-readable cross-references
  • Optimized for LLM consumption and processing

Integration with GitHub

🔑Repository Access

  • GitHub Personal Access Token required
  • Read access to repository contents
  • Support for private repositories
  • Branch-specific analysis
  • Code is temporarily cloned and deleted after analysis

🔗Source Links

  • Direct links to GitHub source files
  • Line-specific references where relevant
  • Branch-aware URL generation
  • Commit hash references for stability

Performance & Limitations

Performance Considerations

  • Large repositories may take 10-30 minutes to analyze
  • Updates are much faster than initial analysis
  • Memory usage scales with repository size
  • Network speed affects GitHub cloning time

⚠️Current Limitations

  • Currently supports TypeScript and JavaScript only
  • Limited support for complex build systems
  • May not capture all dynamic imports
  • Requires clear module structure for best results

Best Practices

📁Repository Setup

  • Use clear module structure and naming conventions
  • Include JSDoc comments for better AI understanding
  • Organize code in logical directories and files
  • Use TypeScript for better type information

🔄Documentation Maintenance

  • Documentation updates automatically on repository pushes
  • Review and customize generated documentation
  • Keep repository structure consistent
  • Update documentation when APIs change

Troubleshooting

Common Issues

  • Analysis fails - check GitHub token permissions
  • Missing modules - verify repository structure
  • Poor documentation quality - add JSDoc comments
  • Slow analysis - consider incremental updates

Performance Tips

  • Use .gitignore to exclude unnecessary files
  • Break large repositories into smaller modules
  • Use smart updates for regular maintenance
  • Monitor analysis progress and adjust expectations

📚

Document Generation Tip

For best results, ensure your codebase has clear module structure and includes JSDoc comments. The AI uses this information to generate more accurate and comprehensive documentation. Start with a complete analysis for new repositories, then use smart updates for ongoing maintenance.

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