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docs/blockchain-development-tutorials/use-AI-to-build-on-flow/cursor/flow-data-sources.md

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@@ -35,11 +35,11 @@ Flow Data Sources is a comprehensive repository that automatically aggregates an
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The repository contains Python scripts that:
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- Crawl Flow-related documentation sites, GitHub repositories, and discussions
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- Convert HTML content to Markdown format
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- Extract code examples from GitHub repositories
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- Capture community discussions and Q&A content
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- Merge all content into consolidated files for easy consumption
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- Crawl Flow-related documentation sites, GitHub repositories, and discussions.
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- Convert HTML content to Markdown format.
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- Extract code examples from GitHub repositories.
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- Capture community discussions and Q&A content.
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- Merge all content into consolidated files for easy consumption.
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Flow Data Sources automatically pulls content from:
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## Key Features
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- **Daily Updates**: Content is automatically refreshed to ensure the latest information
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- **Structured Format**: All content is converted to Markdown for consistent processing
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- **Comprehensive Coverage**: Includes official documentation, code examples, and community discussions
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- **Optimized for AI**: Designed specifically for AI tools, chatbots, and RAG pipelines
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- **Daily Updates**: Content is automatically refreshed to ensure the latest information.
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- **Structured Format**: All content is converted to Markdown for consistent processing.
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- **Comprehensive Coverage**: Includes official documentation, code examples, and community discussions.
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- **Optimized for AI**: Designed specifically for AI tools, chatbots, and RAG pipelines.
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## Available Files
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### All Merged Documentation
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- **File**: [all_merged.md](https://github.com/onflow/Flow-Data-Sources/blob/main/merged_docs/all_merged.md)
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- **Content**: Complete comprehensive documentation covering all aspects of Flow development
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- **Use Case**: Most comprehensive knowledge base for AI tools and complex development questions
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- **Size**: Very large file - may require powerful systems for processing
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- **File**: [all_merged.md](https://github.com/onflow/Flow-Data-Sources/blob/main/merged_docs/all_merged.md).
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- **Content**: Complete comprehensive documentation covering all aspects of Flow development.
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- **Use Case**: Most comprehensive knowledge base for AI tools and complex development questions.
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- **Size**: Very large file - may require powerful systems for processing.
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### Essentials Merged Documentation
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- **File**: [essentials_merged.md](https://github.com/onflow/Flow-Data-Sources/blob/main/merged_docs/essentials_merged.md)
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- **Content**: Core Flow and Cadence development essentials
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- **Use Case**: Lighter alternative for systems with resource constraints
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- **Size**: Smaller, more focused content for essential development needs
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- **Content**: Core Flow and Cadence development essentials.
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- **Use Case**: Lighter alternative for systems with resource constraints.
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- **Size**: Smaller, more focused content for essential development needs.
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### Cadence Only Documentation
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- **File**: [cadence_docs_merged.md](https://github.com/onflow/Flow-Data-Sources/blob/main/merged_docs/cadence_docs_merged.md)
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- **Content**: Streamlined version only including Cadence related documentation and sample codes
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- **Use Case**: Focused on Cadence language development and smart contracts
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- **Size**: Cadence-specific content for specialized development needs
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- **Content**: Streamlined version only including Cadence related documentation and sample codes.
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- **Use Case**: Focused on Cadence language development and smart contracts.
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- **Size**: Cadence-specific content for specialized development needs.
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## How to Use
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Flow Data Sources can be integrated with:
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You can integrate Flow Data Sources with:
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- **ChatGPT Plugins**: Enhance Q&A capabilities with Flow-specific knowledge
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- **Custom Chatbots**: Power Discord/Telegram bots with accurate Flow information
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- **RAG Systems**: Index content in vector databases for semantic search
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- **Development Tools**: Provide context-aware assistance in IDEs like Cursor
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- **ChatGPT Plugins**: Enhance Q&A capabilities with Flow-specific knowledge.
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- **Custom Chatbots**: Power Discord/Telegram bots with accurate Flow information.
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- **RAG Systems**: Index content in vector databases for semantic search.
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- **Development Tools**: Provide context-aware assistance in IDEs like Cursor.
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## Integration with AI Tools
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1. **Identify Your Use Case**: Determine whether you need comprehensive or essential documentation coverage
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2. **Choose Your AI Tool**: Select the AI platform you want to integrate with Flow Data Sources
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3. **Follow Integration Guides**: Use the specific tutorial for your chosen AI tool (ChatGPT, Gemini, Cursor, Claude Code, etc.)
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4. **Test and Validate**: Verify the integration works by asking Flow-specific development questions
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3. **Follow Integration Guides**: Use the specific tutorial for your chosen AI tool (ChatGPT, Gemini, Cursor, Claude Code, and so on.)
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4. **Test and Validate**: Ask Flow-specific development questions to verify that the integration works.
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The Flow Data Sources repository represents a powerful resource for enhancing AI-assisted Flow development, providing comprehensive and current knowledge that adapts to the rapidly evolving Flow ecosystem.
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The Flow Data Sources repository represents a powerful resource to enhance AI-assisted Flow development, and provides comprehensive and current knowledge that adapts to the rapidly evolving Flow ecosystem.
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docs/blockchain-development-tutorials/use-AI-to-build-on-flow/cursor/index.md

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# Use Flow Knowledge Base in Cursor
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[Cursor] is an AI code editor that makes it easy to write code while building Flow apps. This section provides comprehensive guidance on setting up and using Cursor with Flow's extensive documentation ecosystem to enhance your development experience.
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[Cursor] is an AI code editor that makes it easy to write code while building Flow apps. This section provides comprehensive guidance on how to set up and use Cursor with Flow's extensive documentation ecosystem to enhance your development experience.
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## Overview
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To get the most out of Cursor for Flow development, you'll need to understand three key components:
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1. **Flow Data Sources** - The comprehensive knowledge base that powers AI assistance
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2. **Documentation Indexing** - The process of making Flow documentation available within Cursor
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3. **Cadence Rules** - Persistent AI context that provides specialized Flow development guidance
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1. **Flow Data Sources** - The comprehensive knowledge base that powers AI assistance.
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2. **Documentation Indexing** - The process of making Flow documentation available within Cursor.
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3. **Cadence Rules** - Persistent AI context that provides specialized Flow development guidance.
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## [Flow Data Sources]
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Learn about Flow's comprehensive, auto-generated documentation repository that serves as the foundation for AI-assisted development. This resource contains the most current information about Flow, Cadence, and the broader ecosystem, specifically formatted for optimal AI integration.
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The Flow Data Sources guide covers:
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- What Flow Data Sources contains and how it's organized
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- Different file formats available for various use cases
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- Integration strategies with AI tools
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- Best practices for leveraging this knowledge base
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- What Flow Data Sources contains and how it's organized.
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- Different file formats available for various use cases.
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- Integration strategies with AI tools.
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- Best practices for leveraging this knowledge base.
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## [Indexing Flow Documentation in Cursor]
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Follow the step-by-step process for setting up Flow documentation within Cursor's AI system. This detailed guide walks you through indexing multiple documentation sources to create a comprehensive Flow development environment.
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Follow the step-by-step process for how to set up Flow documentation within Cursor's AI system. This detailed guide walks you through indexing multiple documentation sources to create a comprehensive Flow development environment.
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The indexing documentation covers:
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- Adding Flow developer documentation to Cursor
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- Integrating Cadence language documentation
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- Including Flow Data Sources for comprehensive coverage
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- Troubleshooting common indexing issues
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- Best practices for using indexed documentation
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- Adding Flow developer documentation to Cursor.
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- Integrating Cadence language documentation.
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- Including Flow Data Sources for comprehensive coverage.
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- Troubleshooting common indexing issues.
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- Best practices for using indexed documentation.
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## [Cadence Rules]
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Learn how to use Cursor Rules to enhance AI assistance for Cadence and Flow development with persistent context and automated workflows. This comprehensive guide demonstrates how to create specialized rules that transform your AI assistant into a Flow development expert with continuous knowledge of syntax patterns, NFT standards, and project workflows.
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The Cadence Rules guide covers:
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- Understanding Cursor Rules and how they provide persistent AI context
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- Five specialized rules for Flow development: NFT standards, syntax patterns, development workflows, project configuration, and user preferences
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- Creating custom rules for your specific Flow development needs
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- Best practices for rule organization and team collaboration
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- Integration with existing Flow development tools and documentation
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- Understanding Cursor Rules and how they provide persistent AI context.
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- Five specialized rules for Flow development: NFT standards, syntax patterns, development workflows, project configuration, and user preferences.
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- Creating custom rules for your specific Flow development needs.
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- Best practices for rule organization and team collaboration.
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- Integration with current Flow development tools and documentation
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## Getting Started
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1. **Start with Flow Data Sources**: Understand what documentation is available and how it can enhance your development workflow
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2. **Follow the Indexing Guide**: Set up your Cursor environment with comprehensive Flow documentation
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3. **Configure Cadence Rules**: Implement persistent AI context for consistent Flow development assistance
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4. **Practice with Examples**: Use the indexed documentation and rules to build Flow applications with enhanced AI assistance
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1. **Start with Flow Data Sources**: Understand what documentation is available and how it can enhance your development workflow.
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2. **Follow the Indexing Guide**: Set up your Cursor environment with comprehensive Flow documentation.
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3. **Configure Cadence Rules**: Implement persistent AI context for consistent Flow development assistance.
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4. **Practice with Examples**: Use the indexed documentation and rules to build Flow applications with enhanced AI assistance.
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## Best Practices for Cursor + Flow
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- **Use Specific References**: Target `@Flow`, `@Cadence`, or `@Flow Data Sources` based on your needs
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- **Leverage Cursor Rules**: Apply `@cadence-nft-standards`, `@cadence-syntax-patterns`, or other specialized rules for consistent guidance
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- **Combine Sources**: Leverage multiple documentation sources and rules for comprehensive assistance
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- **Verify AI Output**: Cross-reference generated code with official documentation
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- **Use Specific References**: Target `@Flow`, `@Cadence`, or `@Flow Data Sources` based on your needs.
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- **Leverage Cursor Rules**: Apply `@cadence-nft-standards`, `@cadence-syntax-patterns`, or other specialized rules for consistent guidance.
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- **Combine Sources**: Leverage multiple documentation sources and rules for comprehensive assistance.
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- **Verify AI Output**: Cross-reference generated code with official documentation.
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- **Stay Updated**: Refresh your documentation indexes and rules periodically for current information
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This integrated approach combining comprehensive documentation indexing with persistent AI context through Cursor Rules provides you with consistent, accurate, and specialized assistance throughout your Flow development process.

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