Comprehensive README rewrite + community files

- Full 'What Is OrderFlow Analysis?' section explaining microstructure concepts
- System overview with ASCII architecture diagram
- Detailed data flow pipeline showing all engines and detectors
- Module dependency graph with line counts
- 5 Core Patterns: detection logic, strength formulas, source data table
- Volume Profile Framing: ASCII shape diagrams (P/b/D/Double), qualified levels
- State Machine: full lifecycle diagram with all transitions
- 29 instruments with per-instrument threshold tables (indices, metals, forex, stocks, crypto)
- Dual data feed architecture diagram (MT5 + Bybit)
- Dashboard: 8 JS component layout, 9 WebSocket channels with throttling
- Database: full 5-table schema diagram
- API reference: 16 REST endpoints + strategy status labels + scanner priority scoring
- Demo mode documentation with signal quality grading (A+/A/B/C)
- Pattern detection deep-dive (absorption 2-method, initiative 5-criteria)
- Composite scoring system breakdown with SL/TP calculation table
- Signal output examples (entry, daily bias, strategy status)
- Badges: Python 3.10+, MIT, 29 instruments, ~12K lines, 16 API endpoints
- Added: LICENSE (MIT), CONTRIBUTING.md, issue templates (bug, feature, new instrument), PR template

CONTRIBUTING.md

@@ -0,0 +1,47 @@
+# Contributing to OrderFlow Analysis Pro
+
+Thank you for your interest in contributing!
+
+## Getting Started
+
+1. Fork the repository
+2. Create a feature branch (`git checkout -b feature/my-feature`)
+3. Make your changes
+4. Run tests: `pytest orderflow_system/test_integration.py`
+5. Submit a pull request
+
+## Development Setup
+
+```bash
+pip install -e ".[dev]"
+```
+
+## Areas for Contribution
+
+- **New pattern detectors** — add to `patterns/` directory
+- **Additional instruments** — add config in `config/settings.py`
+- **Dashboard improvements** — frontend or API enhancements
+- **Documentation** — guides, tutorials, API docs
+- **Bug fixes** — check GitHub Issues
+
+## Code Style
+
+- Python 3.10+ with type hints
+- Dataclasses for data models
+- Async/await for I/O operations
+- Follow existing patterns in each module
+
+## Reporting Issues
+
+Use GitHub Issues to report:
+- Bugs or unexpected behavior
+- Feature requests
+- Documentation errors
+- Instrument configuration issues
+
+## Pull Request Process
+
+1. Ensure tests pass
+2. Add tests for new features
+3. Update documentation if needed
+4. Keep PRs focused — one feature or fix per PR