New Features:
- 📊 Detailed Market Analysis Panel (similar to pro trading interface)
* Market sentiment, recommendation, resistance/support levels
* Detailed trading setup with entry/exit points
* Risk management with R:R ratios and confirmation triggers
* Technical indicators (RSI, OBV, VWAP) analysis
- 🧠 AI Learning Insights Panel
* Real-time learning status and success rates
* Winner/Loser trade outcome tracking
* AI reflection messages explaining what was learned
* Current thresholds and pattern recognition data
- 🔮 AI Database Integration
* Shows what AI learned from previous trades
* Current confidence thresholds and risk parameters
* Pattern recognition for symbol/timeframe combinations
* Next trade adjustments based on learning
- 🎓 Intelligent Learning from Outcomes
* Automatic trade outcome analysis (winner/loser)
* AI generates learning insights from each trade result
* Confidence adjustment based on trade performance
* Pattern reinforcement or correction based on results
- Beautiful gradient panels with color-coded sections
- Clear winner/loser indicators with visual feedback
- Expandable detailed analysis view
- Real-time learning progress tracking
- Completely isolated paper trading (no real money risk)
- Real market data integration for authentic learning
- Safe practice environment with professional analysis tools
This provides a complete AI learning trading simulation where users can:
1. Get real market analysis with detailed reasoning
2. Execute safe paper trades with zero risk
3. See immediate feedback on trade outcomes
4. Learn from AI reflections and insights
5. Understand how AI adapts and improves over time
- Add new section on auto-restart loop detection and prevention
- Include critical debugging commands for automation cycles
- Document hardcoded recommendation anti-patterns that cause loops
- Add prevention checklist for automation interference
- Include order cancellation monitoring commands
- Expand debugging strategies for complex automation systems
Wisdom gained from resolving rapid order cancellation issue caused by
auto-restart loops in position monitor system.
- Merged duplicate .github/copilot-instructions.instructions.md into main copilot-instructions.md
- Combined development patterns, architecture details, and AI learning system docs
- Added comprehensive references to all technical documentation files
- Single source of truth for GitHub Copilot development guidance
- Includes Docker workflow, cleanup systems, error handling patterns
ADVANCED SYSTEM KNOWLEDGE:
- Superior parallel screenshot system (60% performance gain)
- AI learning system architecture and decision flow
- Orphaned order cleanup integration patterns
- Critical technical fixes and troubleshooting guide
- Database schema best practices
- Memory leak prevention strategies
- AI learning system patterns and functions
- Error handling best practices for trading systems
- Integration patterns for position monitoring
- Performance optimization rules
- UI/UX consistency requirements
- Critical anti-patterns to avoid
- Added links to new knowledge base documents
- Comprehensive documentation structure
- Development guides and best practices
- Performance optimizations summary
- 60% screenshot performance improvement techniques
- AI learning system that adapts trading decisions
- Container stability and crash prevention
- Frontend-backend consistency requirements
- Integration strategies for existing infrastructure
This documentation preserves critical insights from complex debugging sessions and provides patterns for future development.
- Add TECHNICAL_ANALYSIS_BASICS.md with complete indicator explanations
- Add TA_QUICK_REFERENCE.md for quick lookup
- Enhance AI analysis prompts with TA principles integration
- Improve JSON response structure with dedicated analysis sections
- Add cross-layout consensus analysis for higher confidence signals
- Include timeframe-specific risk assessment and position sizing
- Add educational content for RSI, MACD, EMAs, Stochastic RSI, VWAP, OBV
- Implement layout-specific analysis (AI vs DIY layouts)
- Add momentum, trend, and volume analysis separation
- Update README with TA documentation references
- Create implementation summary and test files
- Emphasize Docker container development as required environment
- Add Docker Compose v2 usage with specific port mappings (9001:3000 dev, 9000:3000 prod)
- Define Git branch strategy: development branch for active work, main for stable code
- Include complete development workflow with Git commands
- Clarify external/internal port configuration for both environments
- Remove 'AI Trading Dashboard' title and description text
- Remove grid of quick action cards (AI Analysis, Trading, etc.)
- Keep only StatusOverview component for cleaner interface
- Update .github/copilot-instructions.md with comprehensive AI agent guidance
