archive/task_management/task_supervisor_base.md

🎯 SupervisorAgent Base Implementation

📋 Task Overview

Task ID: Task-1.1.1
Phase: Phase 1 - Core Enhancement
Priority: Critical
Duration: 2 weeks
Owner: AI Agent Team

🎯 Objective

Complete the multi-agent architecture by implementing the missing SupervisorAgent for quality assurance and error recovery coordination.

📊 Current Status

• Missing entirely - This is the biggest architectural gap in the current implementation
• SimplePlannerAgent and McpExecutorAgent are production-ready (516+ tests, 99.8% pass rate)
• Need coordination layer for multi-agent workflows

📋 Requirements

• SupervisorAgent class with monitoring capabilities
• Integration with existing SimplePlannerAgent and McpExecutorAgent
• Error detection and categorization system enhancement
• Quality metrics collection and analysis beyond current executor metrics
• Comprehensive unit and integration tests

💻 Implementation Details

class SupervisorAgent:
    """Quality assurance and coordination agent for multi-agent workflows."""
    
    def __init__(self, planner: SimplePlannerAgent, executor: McpExecutorAgent):
        self.planner = planner
        self.executor = executor
        self.quality_monitor = QualityMonitor()
        self.error_recovery = ErrorRecoverySystem()
    
    def supervise_execution(self, plan: PlannedStep, inputs: dict) -> SupervisedResult:
        """Monitor and supervise plan execution with quality assurance."""
        
    def diagnose_execution_quality(self, result: dict) -> QualityAssessment:
        """Analyze execution results for quality and suggest improvements."""
        
    def coordinate_error_recovery(self, error_context: ErrorContext) -> RecoveryPlan:
        """Coordinate error recovery across multiple agents."""

✅ Acceptance Criteria

• SupervisorAgent class implemented in agents/supervisor/supervisor.py
• Quality monitoring framework integrated
• Error recovery coordination functional
• Integration tests with existing agents pass
• Maintains existing 99.8% test pass rate
• Documentation updated with supervisor architecture

🔗 Dependencies

• Builds on existing agent infrastructure (SimplePlannerAgent, McpExecutorAgent)
• No blocking dependencies - can start immediately

📈 Success Metrics

• 95%+ quality score for supervised executions
• Error recovery success rate > 90%
• Integration with existing agents seamless

🏷️ Tags

agent-architecture, quality-assurance, phase-1, critical-priority

📂 File Structure

agents/
  supervisor/
    __init__.py
    supervisor.py
    quality_monitor.py 
    error_recovery.py
tests/
  agents/
    supervisor/
      test_supervisor.py
      test_quality_monitor.py
      test_error_recovery.py