n8n-workflows/CLAUDE.md
Rex Lorenzo fff6919ffb Add comprehensive Python-based n8n workflow documentation generator
Creates an automated documentation system that analyzes n8n workflow JSON files
and generates interactive HTML documentation with detailed insights.

Features:
• Static analysis of 2053+ workflow files with intelligent categorization
• Interactive HTML interface with search, filtering, and statistics dashboard
• Automatic trigger type detection (Manual, Webhook, Scheduled, Complex)
• Complexity classification and integration detection
• AI-generated workflow descriptions and metadata extraction
• Responsive design with dark/light themes and WCAG accessibility
• JSON viewer with copy/download functionality

Technical Implementation:
• WorkflowAnalyzer class processes all JSON files in workflows/ directory
• Generates self-contained HTML with embedded analysis data
• No external dependencies - uses only Python standard library
• Clean, optimized code with proper type hints and error handling
• Performance optimized for large workflow collections

Usage:
1. Run: python3 generate_documentation.py
2. Open: workflow-documentation.html in browser
3. Browse comprehensive workflow documentation with full analysis

Code Quality:
• Optimized Python with dictionary-based lookups and constants
• Clean CSS without redundant declarations
• Comprehensive README with usage instructions
• Removed superseded documentation files

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-06-12 18:09:57 -07:00

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# n8n-workflows Repository
## Overview
This repository contains a collection of n8n workflow automation files. n8n is a workflow automation tool that allows creating complex automations through a visual node-based interface. Each workflow is stored as a JSON file containing node definitions, connections, and configurations.
## Repository Structure
```
n8n-workflows/
├── workflows/ # Main directory containing all n8n workflow JSON files
│ ├── *.json # Individual workflow files
├── README.md # Repository documentation
├── claude.md # This file - AI assistant context
└── [other files] # Additional configuration or documentation files
```
## Workflow File Format
Each workflow JSON file contains:
- **name**: Workflow identifier
- **nodes**: Array of node objects defining operations
- **connections**: Object defining how nodes are connected
- **settings**: Workflow-level configuration
- **staticData**: Persistent data across executions
- **tags**: Categorization tags
- **createdAt/updatedAt**: Timestamps
## Common Node Types
- **Trigger Nodes**: webhook, cron, manual
- **Integration Nodes**: HTTP Request, database connectors, API integrations
- **Logic Nodes**: IF, Switch, Merge, Loop
- **Data Nodes**: Function, Set, Transform Data
- **Communication**: Email, Slack, Discord, etc.
## Working with This Repository
### For Analysis Tasks
When analyzing workflows in this repository:
1. Parse JSON files to understand workflow structure
2. Examine node chains to determine functionality
3. Identify external integrations and dependencies
4. Consider the business logic implemented by node connections
### For Documentation Tasks
When documenting workflows:
1. Verify existing descriptions against actual implementation
2. Identify trigger mechanisms and schedules
3. List all external services and APIs used
4. Note data transformations and business logic
5. Highlight any error handling or retry mechanisms
### For Modification Tasks
When modifying workflows:
1. Preserve the JSON structure and required fields
2. Maintain node ID uniqueness
3. Update connections when adding/removing nodes
4. Test compatibility with n8n version requirements
## Key Considerations
### Security
- Workflow files may contain sensitive information in webhook URLs or API configurations
- Credentials are typically stored separately in n8n, not in the workflow files
- Be cautious with any hardcoded values or endpoints
### Best Practices
- Workflows should have clear, descriptive names
- Complex workflows benefit from documentation nodes or comments
- Error handling nodes improve reliability
- Modular workflows (calling sub-workflows) improve maintainability
### Common Patterns
- **Data Pipeline**: Trigger → Fetch Data → Transform → Store/Send
- **Integration Sync**: Cron → API Call → Compare → Update Systems
- **Automation**: Webhook → Process → Conditional Logic → Actions
- **Monitoring**: Schedule → Check Status → Alert if Issues
## Helpful Context for AI Assistants
When assisting with this repository:
1. **Workflow Analysis**: Focus on understanding the business purpose by examining the node flow, not just individual nodes.
2. **Documentation Generation**: Create descriptions that explain what the workflow accomplishes, not just what nodes it contains.
3. **Troubleshooting**: Common issues include:
- Incorrect node connections
- Missing error handling
- Inefficient data processing in loops
- Hardcoded values that should be parameters
4. **Optimization Suggestions**:
- Identify redundant operations
- Suggest batch processing where applicable
- Recommend error handling additions
- Propose splitting complex workflows
5. **Code Generation**: When creating tools to analyze these workflows:
- Handle various n8n format versions
- Account for custom nodes
- Parse expressions in node parameters
- Consider node execution order
## Repository-Specific Information
[Add any specific information about your workflows, naming conventions, or special considerations here]
## Version Compatibility
- n8n version: [Specify the n8n version these workflows are compatible with]
- Last updated: [Date of last major update]
- Migration notes: [Any version-specific considerations]