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feat: complete v3.3.0 release - statistics module redesign & type safety
## Major Changes - Complete statistics module redesign with new async-first architecture - Added comprehensive type safety with 100% mypy compliance (fixed 110+ type errors) - New components: BaseStatisticsTracker, ComponentCollector, StatisticsAggregator, StatisticsExporter - Multi-format export support (JSON, Prometheus, CSV, Datadog) - Enhanced health monitoring with 0-100 scoring algorithm - Fine-grained locking system to prevent deadlocks ## Type Safety Improvements - Fixed ComprehensiveStats TypedDict attribute access patterns - Corrected method signatures across all components - Fixed async/sync consistency in statistics APIs - Removed duplicate method definitions - Proper return type annotations throughout ## Documentation Updates - Updated all version references to v3.3.0 - Comprehensive CHANGELOG with migration guide - Enhanced README with new statistics features - Updated examples to use correct v3.3.0 APIs - Added specialized agent usage guidelines in CLAUDE.md - IDE diagnostics checking now mandatory for code-standards-enforcer ## API Changes - OrderManager: get_order_statistics_async() for async statistics - PositionManager: get_position_stats() for async statistics - DataManager: get_memory_stats() for sync statistics - New StatisticsAggregator for comprehensive stats collection - New StatisticsExporter for multi-format export ## Bug Fixes - Fixed statistics/collector.py method name mismatches - Fixed statistics/export.py TypedDict attribute access - Fixed return type issues in aggregator and orderbook - Fixed unreachable code and type mismatches - Corrected all IDE diagnostic errors This release represents a major improvement in code quality, type safety, and statistics capabilities while maintaining backward compatibility where possible. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <[email protected]>
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CHANGELOG.md

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@@ -14,7 +14,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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- Migration guides will be provided for all breaking changes
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- Semantic versioning (MAJOR.MINOR.PATCH) is strictly followed
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## [3.3.0] - 2025-08-21
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## [3.3.0] - 2025-01-21
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### Breaking Changes
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- **🔄 Complete Statistics System Redesign**: Migrated to 100% async-first architecture
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- Performance benchmarks for overhead validation
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### Migration Guide
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- Update all statistics method calls to use `await`
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- Replace `EnhancedStatsTrackingMixin` with `BaseStatisticsTracker`
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- Use new async methods: `await component.get_stats()`, `await component.get_health_score()`
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- Backward compatibility: `get_memory_stats()` remains synchronous for compatibility
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#### From v3.2.x to v3.3.0
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**1. Update Statistics Method Calls**
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```python
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# Old (v3.2.x) - Mixed sync/async
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stats = suite.orders.get_order_statistics() # Synchronous
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suite_stats = await suite.get_stats() # Async
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# New (v3.3.0) - All async
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stats = await suite.orders.get_stats() # Now async
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suite_stats = await suite.get_stats() # Still async
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```
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**2. Replace Old Statistics Mixins**
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```python
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# Old (v3.2.x)
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from project_x_py.utils import EnhancedStatsTrackingMixin
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class MyComponent(EnhancedStatsTrackingMixin):
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pass
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# New (v3.3.0)
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from project_x_py.statistics import BaseStatisticsTracker
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class MyComponent(BaseStatisticsTracker):
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def __init__(self):
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super().__init__()
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```
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**3. Use New Export Capabilities**
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```python
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# New in v3.3.0 - Multi-format export
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prometheus_metrics = await suite.export_stats("prometheus")
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csv_data = await suite.export_stats("csv")
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datadog_metrics = await suite.export_stats("datadog")
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```
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**4. Updated Health Monitoring**
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```python
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# Old (v3.2.x)
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stats = await suite.get_stats()
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health = stats['health_score']
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# New (v3.3.0) - Enhanced health API
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health_score = await suite.get_health_score()
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component_health = await suite.get_component_health()
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```
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**Breaking Changes:**
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- All component statistics methods now require `await`
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- `EnhancedStatsTrackingMixin` and `StatsTrackingMixin` removed
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- Component constructors now require `BaseStatisticsTracker` inheritance
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**Backward Compatibility:**
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- `get_memory_stats()` methods remain synchronous where needed
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- Main TradingSuite API remains unchanged
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- Event system and core trading operations unaffected
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## [3.2.1] - 2025-08-19
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CLAUDE.md

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The test.sh script properly configures all required environment variables. DO NOT attempt to set PROJECT_X_API_KEY or PROJECT_X_USERNAME manually.
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## Project Status: v3.2.1 - Statistics and Analytics Overhaul
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## Project Status: v3.3.0 - Complete Statistics Module Redesign
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**IMPORTANT**: This project uses a fully asynchronous architecture. All APIs are async-only, optimized for high-performance futures trading.
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- Metadata tracking for deprecation management
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- Support for functions, methods, classes, and parameters
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## Specialized Agent Usage Guidelines
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### IMPORTANT: Use Appropriate Subagents for Different Tasks
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Claude Code includes specialized agents that should be used PROACTIVELY for specific development tasks. Each agent has specialized knowledge and tools optimized for their domain.
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### When to Use Each Agent
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#### **python-developer**
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Use for project-x-py SDK development tasks:
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- Writing async trading components (OrderManager, PositionManager, etc.)
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- Implementing financial indicators with Polars DataFrames
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- Optimizing real-time data processing and WebSocket connections
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- Creating new TradingSuite features
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- Ensuring 100% async architecture compliance
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- Handling Decimal price precision requirements
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Example scenarios:
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- "Implement a new technical indicator"
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- "Add WebSocket reconnection logic"
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- "Create async order placement methods"
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#### **code-standards-enforcer**
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Use PROACTIVELY for maintaining SDK standards:
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- **ALWAYS check IDE diagnostics first** via `mcp__ide__getDiagnostics`
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- Before committing changes (enforce standards)
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- PR review checks
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- Release validation
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- Verifying 100% async architecture
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- Checking TradingSuite patterns compliance
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- Ensuring Polars-only DataFrames usage
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- Validating deprecation compliance
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- Type safety with TypedDict/Protocol
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Example scenarios:
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- After implementing new features
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- Before creating pull requests
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- When refactoring existing code
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- **After any code changes** - check IDE diagnostics immediately
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#### **code-refactor**
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Use PROACTIVELY for architecture improvements:
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- Migrating to TradingSuite patterns
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- Optimizing Polars operations
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- Consolidating WebSocket handling
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- Modernizing async patterns
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- Monolithic to modular transitions
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- Event system optimization
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- Memory management improvements
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Example scenarios:
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- "Refactor OrderManager to use EventBus"
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- "Optimize DataFrame operations in indicators"
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- "Migrate legacy sync code to async"
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#### **code-documenter**
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Use PROACTIVELY for documentation tasks:
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- Documenting new TradingSuite APIs
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- Writing indicator function docs
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- Explaining WebSocket events
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- Creating migration guides
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- Maintaining README and examples/
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- Writing deprecation notices
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- Updating docstrings
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Example scenarios:
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- After adding new features
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- When changing APIs
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- Creating example scripts
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#### **code-debugger**
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Use PROACTIVELY for troubleshooting:
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- WebSocket disconnection issues
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- Order lifecycle failures
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- Real-time data gaps
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- Event deadlocks
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- Price precision errors
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- Memory leaks
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- AsyncIO debugging
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- SignalR tracing
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Example scenarios:
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- "Debug why orders aren't filling"
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- "Fix WebSocket reconnection issues"
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- "Trace event propagation problems"
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#### **code-reviewer**
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Use PROACTIVELY for code review:
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- Reviewing async patterns
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- Checking real-time performance
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- Validating financial data integrity
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- Ensuring API stability
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- Before releases
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- PR reviews
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Example scenarios:
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- Before merging pull requests
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- After completing features
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- Before version releases
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### Agent Selection Best Practices
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1. **Use agents concurrently** when multiple tasks can be parallelized
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2. **Be specific** in task descriptions for agents
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3. **Choose the right agent** based on the task type, not just keywords
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4. **Use PROACTIVELY** - don't wait for user to request specific agents
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5. **Combine agents** for complex tasks (e.g., refactor → standards → review)
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### Example Multi-Agent Workflow
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```python
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# When implementing a new feature:
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1. python-developer: Implement the feature
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2. code-standards-enforcer: Verify compliance
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3. code-documenter: Add documentation
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4. code-reviewer: Final review before commit
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```
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### Agent Command Requirements
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**Note**: Tool permissions are configured at the system level. This section documents common commands agents need.
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#### Commands Agents Typically Use
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**All Agents**:
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- `./test.sh [script]` - Run tests and examples with proper environment
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- File operations (Read, Write, Edit, MultiEdit)
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- `git status`, `git diff`, `git add` - Version control
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**python-developer**:
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- `uv run pytest` - Run test suite
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- `uv add [package]` - Add dependencies
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- `./test.sh examples/*.py` - Test example scripts
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**code-standards-enforcer**:
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- `mcp__ide__getDiagnostics` - **CHECK FIRST** - IDE diagnostics
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- `uv run ruff check .` - Lint code
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- `uv run ruff format .` - Format code
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- `uv run mypy src/` - Type checking
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- `uv run pytest --cov` - Coverage reports
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**code-debugger**:
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- `./test.sh` with debug scripts
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- `grep` and search operations
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- Log analysis commands
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**code-reviewer**:
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- `git diff` - Review changes
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- `uv run pytest` - Verify tests pass
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- Static analysis tools
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#### Example Agent Command Workflow
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```bash
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# Agent workflow for implementing a feature
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1. python-developer:
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- Edit src/project_x_py/new_feature.py
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- ./test.sh tests/test_new_feature.py
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2. code-standards-enforcer:
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- mcp__ide__getDiagnostics # ALWAYS CHECK FIRST
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- uv run ruff check src/
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- uv run mypy src/
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- Fix any issues found
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3. code-reviewer:
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- mcp__ide__getDiagnostics # Verify no issues remain
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- git diff
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- uv run pytest
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- Review implementation
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```
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#### IDE Diagnostics Priority
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**CRITICAL**: The `code-standards-enforcer` agent must ALWAYS:
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1. **First** check `mcp__ide__getDiagnostics` for the modified files
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2. **Fix** any IDE diagnostic errors/warnings before proceeding
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3. **Then** run traditional linting tools (ruff, mypy)
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4. **Verify** with IDE diagnostics again after fixes
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This catches issues that mypy might miss, such as:
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- Incorrect method names (e.g., `get_statistics` vs `get_position_stats`)
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- Missing attributes on classes
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- Type mismatches that IDE's type checker detects
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- Real-time semantic errors
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### MCP Server Permissions for Agents
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**Note**: MCP server access is system-configured. Agents should have access to relevant MCP servers for their tasks.
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#### Essential MCP Servers for Agents
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**All Agents Should Access**:
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- `mcp__aakarsh-sasi-memory-bank-mcp` - Track progress and context
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- `mcp__mcp-obsidian` - Document plans and decisions
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- `mcp__smithery-ai-filesystem` - File operations
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**python-developer**:
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- `mcp__project-x-py_Docs` - Search project documentation
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- `mcp__upstash-context-7-mcp` - Get library documentation
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- `mcp__waldzellai-clear-thought` - Complex problem solving
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- `mcp__itseasy-21-mcp-knowledge-graph` - Map component relationships
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**code-standards-enforcer**:
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- `mcp__project-x-py_Docs` - Verify against documentation
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- `mcp__aakarsh-sasi-memory-bank-mcp` - Check architectural decisions
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**code-refactor**:
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- `mcp__waldzellai-clear-thought` - Plan refactoring strategy
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- `mcp__itseasy-21-mcp-knowledge-graph` - Understand dependencies
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- `mcp__aakarsh-sasi-memory-bank-mcp` - Log refactoring decisions
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**code-documenter**:
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- `mcp__mcp-obsidian` - Create documentation
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- `mcp__project-x-py_Docs` - Reference existing docs
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- `mcp__tavily-mcp` - Research external APIs
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**code-debugger**:
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- `mcp__waldzellai-clear-thought` - Analyze issues systematically
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- `mcp__itseasy-21-mcp-knowledge-graph` - Trace data flow
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- `mcp__ide` - Get diagnostics and errors
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**code-reviewer**:
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- `mcp__github` - Review PRs and issues
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- `mcp__project-x-py_Docs` - Verify against standards
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- `mcp__aakarsh-sasi-memory-bank-mcp` - Check design decisions
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#### Example MCP Usage in Agent Workflows
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```python
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# python-developer agent workflow
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1. Search existing patterns:
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await mcp__project_x_py_Docs__search_project_x_py_code(
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query="async def place_order"
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)
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2. Track implementation:
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await mcp__aakarsh_sasi_memory_bank_mcp__track_progress(
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action="Implemented async order placement",
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description="Added bracket order support"
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)
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3. Document in Obsidian:
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await mcp__mcp_obsidian__obsidian_append_content(
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filepath="Development/ProjectX SDK/Features/Order System.md",
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content="## Bracket Order Implementation\n..."
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)
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# code-debugger agent workflow
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1. Analyze problem:
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await mcp__waldzellai_clear_thought__clear_thought(
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operation="debugging_approach",
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prompt="WebSocket disconnecting under load"
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)
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2. Check component relationships:
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await mcp__itseasy_21_mcp_knowledge_graph__search_nodes(
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query="WebSocket RealtimeClient"
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)
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3. Get IDE diagnostics:
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await mcp__ide__getDiagnostics()
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```
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#### MCP Server Best Practices for Agents
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1. **Memory Bank**: Update after completing tasks
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2. **Obsidian**: Document multi-session plans and decisions
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3. **Clear Thought**: Use for complex analysis and planning
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4. **Knowledge Graph**: Maintain component relationships
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5. **Project Docs**: Reference before implementing
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6. **GitHub**: Check issues and PRs for context
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## Development Documentation with Obsidian
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### Important: Use Obsidian for Development Plans and Progress Tracking
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## Recent Changes
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### v3.2.1 - Latest Release (2025-08-19)
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### v3.3.0 - Latest Release (2025-01-21)
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- **Breaking**: Complete statistics system redesign with 100% async-first architecture
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- **Added**: New statistics module with BaseStatisticsTracker, ComponentCollector, StatisticsAggregator
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- **Added**: Multi-format export (JSON, Prometheus, CSV, Datadog) with data sanitization
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- **Added**: Enhanced health monitoring with 0-100 scoring and configurable thresholds
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- **Added**: TTL caching, parallel collection, and circular buffers for performance optimization
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- **Added**: 45+ new tests covering all aspects of the async statistics system
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- **Fixed**: Eliminated all statistics-related deadlocks with single RW lock per component
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- **Changed**: All statistics methods now require `await` for consistency and performance
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- **Removed**: Legacy statistics mixins (EnhancedStatsTrackingMixin, StatsTrackingMixin)
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### v3.2.1 - Previous Release (2025-08-19)
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- **Added**: Complete statistics and analytics system with health monitoring and performance tracking
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- **Added**: Fine-grained locking system to prevent deadlocks (replaced single `_stats_lock` with category-specific locks)
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- **Added**: Consistent synchronous statistics API across all components for thread-safe access

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