singsalot/docs

📄 Documentation & Reference Models

This /docs folder contains Product Requirements Documents (PRD), data model definitions, and Firebase schema references for the Karaoke App project.

These files are intended for:

• 📃 Developers reviewing the business logic and architecture.
• 🤖 AI tools like Cursor or Copilot that reference documentation for context-aware coding.
• 📝 Project planning, architecture decisions, and future enhancements.
• 🚀 Building the app from scratch with any framework/platform combination.

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Contents

File	Purpose
PRD.md	Complete Product Requirements Document — platform-agnostic business logic, technical specifications, data flows, service APIs, component architecture, error handling, and performance optimizations. Self-guiding for AI implementation.
types.ts	Reference TypeScript interfaces used for modeling app objects. Not imported into app runtime code.
firebase_schema.json	Example Firebase Realtime Database structure for understanding data relationships and CRUD operations.

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🚀 How to Use This Documentation

For AI-Assisted Development:

Simply say "Read this PRD" in any new chat. The PRD contains:

• Self-guiding instructions for AI implementation
• Complete technical specifications for 100% accuracy
• Implementation questions to determine platform/framework choices
• Step-by-step build process with checklists

For Human Developers:

• Reference during implementation for business logic and data flows
• Guide for architecture decisions and technology choices
• Source of truth for all functional requirements
• Migration guide when switching frameworks/platforms

For New Implementations:

1. Read the PRD completely - it contains comprehensive specifications
2. Answer implementation questions from Section 29
3. Follow the implementation checklist for complete build process
4. Preserve business logic while adapting UI to chosen framework

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📋 Key Features of the Updated PRD

Platform-Agnostic Design:

• Core requirements separated from implementation details
• Framework-specific sections clearly marked
• Migration guidance for different platforms
• Toolset rationale for informed technology choices

Complete Technical Specifications:

• Data flow diagrams for all operations
• State management architecture with exact structure
• Service layer APIs with function signatures
• Component architecture with interfaces and behavior
• Error handling matrix for all scenarios
• Performance specifications with optimization patterns

Implementation Guide:

• 7 key questions to determine platform/framework
• 5-phase implementation checklist
• Must preserve vs. can replace guidelines
• Critical success factors for accurate builds

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🔄 Workflow for New Versions

When Creating New Implementations:

1. Use the PRD as-is - it's designed for any framework/platform
2. Follow the implementation guide in Section 29
3. Preserve all business logic while adapting UI layer
4. Test against specifications for 100% accuracy

When Updating the PRD:

1. Keep platform-agnostic requirements intact
2. Add new implementation details to appropriate sections
3. Update toolset sections with new technology choices
4. Maintain self-guiding nature for AI implementation

When Migrating Platforms:

1. Keep all business logic from core requirements
2. Replace only implementation details in platform-specific sections
3. Add new platform sections following the established pattern
4. Update toolset rationale for new technology choices

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Important Notes

• ✅ These files are not intended for direct import or use in application runtime.
• ✅ Validation logic and data models here serve as development references only.
• ✅ Any updates to business logic, data flow, or app architecture should be reflected here for documentation purposes.
• ✅ AI tools may use this information to assist with code generation but will not access /src directly.
• ✅ The PRD is self-guiding - it contains all instructions needed for AI implementation.
• ✅ 100% accuracy achievable when following the complete specifications.

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🎯 Success Metrics

• Zero ambiguity in technical requirements
• Framework independence for easy migration
• Complete implementation path from start to finish
• Consistent results across different technology stacks
• Self-documenting for future developers and AI tools

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This documentation is designed to be your ultimate development tool - enabling accurate builds with any framework/platform combination.