Enhanced Command System Expansion with Intelligence

Purpose

Comprehensive command system expansion with real-time validation and research integration
Conduct command implementation with validated methodologies and collaborative intelligence
Ensure command excellence with current command system standards and implementation practices
Integrate web research for current command system frameworks and expansion patterns
Provide validated command strategies with cross-team coordination and continuous optimization

Enhanced Capabilities

Command Intelligence

Command Validation: Real-time command system validation against current command standards
Research Integration: Current command system best practices and expansion frameworks
System Assessment: Comprehensive command system analysis and optimization
Quality Validation: Command quality analysis and validation with continuous improvement

Collaborative Intelligence

Shared Context Integration: Access to all command contexts and system requirements
Cross-Team Coordination: Seamless collaboration with command teams and system stakeholders
Quality Assurance: Professional-grade command implementation with validation reports
Research Integration: Current command methodologies, system coordination, and expansion best practices

[[LLM: VALIDATION CHECKPOINT - All command procedures must be validated for effectiveness, coverage, and current command system standards. Include research-backed command methodologies and expansion principles.]]

Complete Command System Expansion Implementation

1. Core Command Architecture Enhancement

Enhanced Command Processing System

class EnhancedCommandProcessor:
    """Enhanced command processor with full team participation support"""
    
    def __init__(self):
        self.command_registry = CommandRegistry()
        self.participation_manager = ParticipationManager()
        self.command_validator = CommandValidator()
        self.execution_engine = ExecutionEngine()
        self.response_formatter = ResponseFormatter()
    
    def register_full_team_commands(self):
        """Register all full team participation commands"""
        
        # Register new commands
        self.command_registry.register_command(FullTeamOnCommand())
        self.command_registry.register_command(FullTeamOffCommand())
        self.command_registry.register_command(FullTeamStatusCommand())
        
        # Update existing commands for full team compatibility
        self.update_existing_commands_for_full_team()
        
        return CommandRegistrationResult(
            registered_commands=["full_team_on", "full_team_off", "full_team_status"],
            updated_commands=["pre_select_agents", "yolo", "full_yolo", "agent-list"],
            registration_success=True
        )
    
    def process_command(self, command_input, session_context):
        """Process command with enhanced full team participation support"""
        
        # Parse command
        command_parse_result = self.parse_command(command_input)
        
        # Validate command
        command_validation = self.command_validator.validate_command(
            command_parse_result,
            session_context
        )
        
        if not command_validation.valid:
            return CommandExecutionResult(
                success=False,
                error=command_validation.error_message,
                suggestions=command_validation.suggestions
            )
        
        # Execute command
        execution_result = self.execution_engine.execute_command(
            command_parse_result.command,
            command_parse_result.parameters,
            session_context
        )
        
        # Format response
        formatted_response = self.response_formatter.format_command_response(
            execution_result,
            command_parse_result.command
        )
        
        return CommandExecutionResult(
            success=execution_result.success,
            response=formatted_response,
            session_updates=execution_result.session_updates
        )

class CommandRegistry:
    """Registry for all system commands including full team participation commands"""
    
    def __init__(self):
        self.commands = {}
        self.command_categories = {
            "system_control": [],
            "agent_management": [],
            "workflow_control": [],
            "participation_management": [],
            "information_display": []
        }
    
    def register_command(self, command_instance):
        """Register command instance with full metadata"""
        
        command_metadata = CommandMetadata(
            name=command_instance.name,
            category=command_instance.category,
            description=command_instance.description,
            parameters=command_instance.parameters,
            examples=command_instance.examples,
            compatibility=command_instance.compatibility,
            validation_rules=command_instance.validation_rules
        )
        
        self.commands[command_instance.name] = {
            "instance": command_instance,
            "metadata": command_metadata
        }
        
        self.command_categories[command_instance.category].append(command_instance.name)
        
        return CommandRegistrationResult(
            command_name=command_instance.name,
            registration_success=True
        )

2. Full Team On Command Implementation

`/full_team_on` Command

class FullTeamOnCommand:
    """Command to enable full team participation mode"""
    
    def __init__(self):
        self.name = "full_team_on"
        self.category = "participation_management"
        self.description = "Enable full team participation mode for comprehensive project coverage"
        self.parameters = []
        self.examples = ["/full_team_on"]
        self.compatibility = ["documentation_mode", "full_development_mode"]
        self.validation_rules = ["session_active", "orchestrator_mode"]
    
    def execute(self, parameters, session_context):
        """Execute full team on command"""
        
        # Validate current session state
        if not session_context.session_active:
            return CommandResult(
                success=False,
                error="No active session. Please start a workflow session first."
            )
        
        # Enable full team participation
        participation_result = session_context.participation_manager.enable_full_team_participation()
        
        # Get all available agents
        all_agents = session_context.agent_registry.get_all_agents()
        
        # Determine integration points
        integration_points = session_context.integration_scheduler.get_integration_points(
            session_context.workflow_type,
            all_agents
        )
        
        # Generate confirmation response
        confirmation_response = self.generate_confirmation_response(
            all_agents,
            integration_points,
            participation_result
        )
        
        # Update session configuration
        session_context.update_configuration({
            "full_team_participation": True,
            "participating_agents": all_agents,
            "integration_points": integration_points
        })
        
        return CommandResult(
            success=True,
            response=confirmation_response,
            session_updates={
                "full_team_participation": True,
                "participating_agents": [agent.name for agent in all_agents]
            }
        )
    
    def generate_confirmation_response(self, all_agents, integration_points, participation_result):
        """Generate comprehensive confirmation response"""
        
        response_lines = []
        
        # Header
        response_lines.append("🤝 **Full Team Participation: ACTIVATED**")
        response_lines.append("")
        
        # Participation overview
        response_lines.append(f"✅ **Status**: Full team participation is now ACTIVE")
        response_lines.append(f"👥 **Team Size**: {len(all_agents)} agents will collaborate")
        response_lines.append("")
        
        # Agent list with roles
        response_lines.append("**Participating Agents:**")
        
        # Primary agents
        primary_agents = [agent for agent in all_agents if agent.classification == "PRIMARY"]
        response_lines.append("*Primary Agents (Always Active):*")
        for agent in primary_agents:
            response_lines.append(f"  • **{agent.name}** ({agent.title}) - {agent.primary_expertise}")
        
        response_lines.append("")
        
        # Secondary agents
        secondary_agents = [agent for agent in all_agents if agent.classification == "SECONDARY"]
        response_lines.append("*Secondary Agents (Full Team Participation):*")
        for agent in secondary_agents:
            response_lines.append(f"  • **{agent.name}** ({agent.title}) - {agent.primary_expertise}")
        
        response_lines.append("")
        
        # Integration points overview
        response_lines.append("**Integration Points:**")
        integration_phases = self.group_integration_points_by_phase(integration_points)
        for phase_name, phase_points in integration_phases.items():
            response_lines.append(f"*{phase_name.replace('_', ' ').title()}:*")
            for point in phase_points:
                response_lines.append(f"  • {point.agent_name}: {point.contribution_description}")
        
        response_lines.append("")
        
        # Expected benefits
        response_lines.append("**Expected Benefits:**")
        response_lines.append("  ✅ Comprehensive expertise coverage across all project aspects")
        response_lines.append("  ✅ Enhanced quality through multi-perspective validation")
        response_lines.append("  ✅ Reduced risk through collaborative decision-making")
        response_lines.append("  ✅ Professional-grade deliverables with domain expert input")
        
        response_lines.append("")
        response_lines.append("🚀 **Ready to proceed with full team collaboration!**")
        
        return "\n".join(response_lines)
    
    def group_integration_points_by_phase(self, integration_points):
        """Group integration points by workflow phase"""
        
        phase_groups = {}
        
        for point in integration_points:
            phase_name = point.workflow_phase
            if phase_name not in phase_groups:
                phase_groups[phase_name] = []
            phase_groups[phase_name].append(point)
        
        return phase_groups

3. Full Team Off Command Implementation

`/full_team_off` Command

class FullTeamOffCommand:
    """Command to disable full team participation mode"""
    
    def __init__(self):
        self.name = "full_team_off"
        self.category = "participation_management"
        self.description = "Disable full team participation mode and revert to selective agent activation"
        self.parameters = []
        self.examples = ["/full_team_off"]
        self.compatibility = ["documentation_mode", "full_development_mode"]
        self.validation_rules = ["session_active", "full_team_enabled"]
    
    def execute(self, parameters, session_context):
        """Execute full team off command"""
        
        # Validate current state
        if not session_context.full_team_participation_enabled:
            return CommandResult(
                success=False,
                error="Full team participation is not currently enabled."
            )
        
        # Get current participation status
        current_participation = session_context.participation_manager.get_current_participation_status()
        
        # Disable full team participation
        disable_result = session_context.participation_manager.disable_full_team_participation()
        
        # Determine selective agents for current workflow
        selective_agents = session_context.agent_selector.select_workflow_agents(
            session_context.workflow_type,
            session_context.project_requirements
        )
        
        # Generate confirmation response
        confirmation_response = self.generate_disable_confirmation_response(
            current_participation,
            selective_agents,
            disable_result
        )
        
        # Update session configuration
        session_context.update_configuration({
            "full_team_participation": False,
            "participating_agents": selective_agents,
            "participation_mode": "selective"
        })
        
        return CommandResult(
            success=True,
            response=confirmation_response,
            session_updates={
                "full_team_participation": False,
                "participating_agents": [agent.name for agent in selective_agents]
            }
        )
    
    def generate_disable_confirmation_response(self, current_participation, selective_agents, disable_result):
        """Generate confirmation response for disabling full team participation"""
        
        response_lines = []
        
        # Header
        response_lines.append("🔄 **Full Team Participation: DISABLED**")
        response_lines.append("")
        
        # Status update
        response_lines.append(f"✅ **Status**: Reverted to selective agent activation")
        response_lines.append(f"👥 **New Team Size**: {len(selective_agents)} agents (reduced from {current_participation.total_agents})")
        response_lines.append("")
        
        # Current session impact
        if current_participation.participated_agents:
            response_lines.append("**Current Session Impact:**")
            response_lines.append(f"  • {len(current_participation.participated_agents)} agents have already contributed")
            response_lines.append(f"  • Their contributions will be preserved in the current session")
            response_lines.append("")
        
        # New selective agent list
        response_lines.append("**Active Agents (Selective Mode):**")
        for agent in selective_agents:
            response_lines.append(f"  • **{agent.name}** ({agent.title}) - {agent.primary_expertise}")
        
        response_lines.append("")
        
        # Deactivated agents
        deactivated_agents = [agent for agent in current_participation.all_agents if agent not in selective_agents]
        if deactivated_agents:
            response_lines.append("**Deactivated Agents:**")
            for agent in deactivated_agents:
                response_lines.append(f"  • {agent.name} ({agent.title})")
            response_lines.append("")
        
        # Impact summary
        response_lines.append("**Impact Summary:**")
        response_lines.append("  ✅ Faster workflow execution with focused agent team")
        response_lines.append("  ✅ Reduced complexity with essential agents only")
        response_lines.append("  ✅ Maintained quality with core expertise coverage")
        
        response_lines.append("")
        response_lines.append("🎯 **Continuing with selective agent activation mode**")
        
        return "\n".join(response_lines)

4. Full Team Status Command Implementation

`/full_team_status` Command

class FullTeamStatusCommand:
    """Command to display current full team participation status"""
    
    def __init__(self):
        self.name = "full_team_status"
        self.category = "information_display"
        self.description = "Display detailed full team participation status and progress"
        self.parameters = []
        self.examples = ["/full_team_status"]
        self.compatibility = ["documentation_mode", "full_development_mode"]
        self.validation_rules = ["session_active"]
    
    def execute(self, parameters, session_context):
        """Execute full team status command"""
        
        # Get current participation status
        participation_status = session_context.participation_manager.get_detailed_participation_status()
        
        # Get session progress
        session_progress = session_context.progress_calculator.calculate_session_progress()
        
        # Get upcoming opportunities
        upcoming_opportunities = session_context.opportunity_analyzer.get_upcoming_opportunities()
        
        # Generate comprehensive status response
        status_response = self.generate_comprehensive_status_response(
            participation_status,
            session_progress,
            upcoming_opportunities
        )
        
        return CommandResult(
            success=True,
            response=status_response,
            metadata={
                "participation_status": participation_status,
                "session_progress": session_progress
            }
        )
    
    def generate_comprehensive_status_response(self, participation_status, session_progress, upcoming_opportunities):
        """Generate comprehensive status response"""
        
        response_lines = []
        
        # Header with overall status
        if participation_status.full_team_enabled:
            response_lines.append("🤝 **Full Team Participation Status: ACTIVE**")
        else:
            response_lines.append("🎯 **Selective Agent Participation Status: ACTIVE**")
        
        response_lines.append("")
        
        # Overall progress metrics
        response_lines.append("**📊 Overall Progress:**")
        response_lines.append(f"  • **Participation Rate**: {session_progress.participation_rate:.1f}% ({session_progress.participated_count}/{session_progress.total_agents} agents)")
        response_lines.append(f"  • **Average Quality Score**: {session_progress.average_quality_score:.1f}/10")
        response_lines.append(f"  • **Session Duration**: {self.format_duration(session_progress.session_duration)}")
        response_lines.append(f"  • **Current Phase**: {session_progress.current_phase}")
        response_lines.append("")
        
        # Detailed agent participation status
        response_lines.append("**👥 Agent Participation Details:**")
        response_lines.append("")
        
        # Create participation table
        response_lines.append("| Agent | Title | Status | Contributions | Quality | Last Activity |")
        response_lines.append("|-------|-------|--------|---------------|---------|---------------|")
        
        for agent_name, agent_status in participation_status.agent_statuses.items():
            status_emoji = self.get_status_emoji(agent_status.participation_status)
            contribution_count = len(agent_status.contributions)
            quality_score = f"{agent_status.average_quality:.1f}" if agent_status.average_quality else "N/A"
            last_activity = self.format_last_activity(agent_status.last_contribution_time)
            
            response_lines.append(f"| {agent_name} | {agent_status.title} | {status_emoji} | {contribution_count} | {quality_score} | {last_activity} |")
        
        response_lines.append("")
        
        # Participation breakdown by status
        response_lines.append("**📈 Participation Breakdown:**")
        status_counts = self.calculate_status_counts(participation_status.agent_statuses)
        for status, count in status_counts.items():
            emoji = self.get_status_emoji(status)
            response_lines.append(f"  • {emoji}: {count} agents")
        
        response_lines.append("")
        
        # Upcoming integration opportunities
        if upcoming_opportunities:
            response_lines.append("**🔮 Upcoming Integration Opportunities:**")
            for opportunity in upcoming_opportunities[:5]:  # Show top 5
                response_lines.append(f"  • **{opportunity.agent_name}**: {opportunity.opportunity_description}")
                response_lines.append(f"    *Expected in {opportunity.phase_name} phase*")
            
            if len(upcoming_opportunities) > 5:
                response_lines.append(f"  • ... and {len(upcoming_opportunities) - 5} more opportunities")
            
            response_lines.append("")
        
        # Quality insights
        response_lines.append("**🎯 Quality Insights:**")
        quality_insights = self.generate_quality_insights(participation_status, session_progress)
        for insight in quality_insights:
            response_lines.append(f"  • {insight}")
        
        response_lines.append("")
        
        # Recommendations
        recommendations = self.generate_participation_recommendations(participation_status, session_progress)
        if recommendations:
            response_lines.append("**💡 Recommendations:**")
            for recommendation in recommendations:
                response_lines.append(f"  • {recommendation}")
        
        return "\n".join(response_lines)
    
    def get_status_emoji(self, participation_status):
        """Get emoji representation of participation status"""
        
        status_emoji_map = {
            "PENDING": "⏳ Pending",
            "ACTIVE": "🔄 Contributing",
            "CONTRIBUTED": "✅ Contributed",
            "COMPLETED": "✅ Complete",
            "INSUFFICIENT": "❌ Needs Improvement",
            "SKIPPED": "⏭️ Skipped"
        }
        
        return status_emoji_map.get(participation_status, "❓ Unknown")
    
    def format_duration(self, duration_seconds):
        """Format duration in human-readable format"""
        
        if duration_seconds < 60:
            return f"{int(duration_seconds)}s"
        elif duration_seconds < 3600:
            minutes = int(duration_seconds / 60)
            seconds = int(duration_seconds % 60)
            return f"{minutes}m {seconds}s"
        else:
            hours = int(duration_seconds / 3600)
            minutes = int((duration_seconds % 3600) / 60)
            return f"{hours}h {minutes}m"
    
    def format_last_activity(self, last_activity_timestamp):
        """Format last activity timestamp"""
        
        if not last_activity_timestamp:
            return "Never"
        
        time_diff = time.time() - last_activity_timestamp
        
        if time_diff < 60:
            return "Just now"
        elif time_diff < 3600:
            minutes = int(time_diff / 60)
            return f"{minutes}m ago"
        elif time_diff < 86400:
            hours = int(time_diff / 3600)
            return f"{hours}h ago"
        else:
            days = int(time_diff / 86400)
            return f"{days}d ago"
    
    def generate_quality_insights(self, participation_status, session_progress):
        """Generate quality insights based on participation data"""
        
        insights = []
        
        # Quality distribution analysis
        high_quality_agents = sum(1 for status in participation_status.agent_statuses.values() 
                                 if status.average_quality and status.average_quality >= 8.0)
        
        if high_quality_agents > 0:
            insights.append(f"{high_quality_agents} agents are delivering high-quality contributions (8.0+)")
        
        # Participation efficiency
        if session_progress.participation_rate >= 80:
            insights.append("Excellent participation rate - most agents are actively contributing")
        elif session_progress.participation_rate >= 60:
            insights.append("Good participation rate - majority of agents are engaged")
        else:
            insights.append("Participation rate could be improved - consider agent activation strategies")
        
        # Quality consistency
        quality_scores = [status.average_quality for status in participation_status.agent_statuses.values() 
                         if status.average_quality]
        if quality_scores:
            quality_variance = self.calculate_variance(quality_scores)
            if quality_variance < 1.0:
                insights.append("Consistent quality across all contributing agents")
            else:
                insights.append("Quality variance detected - some agents may need additional guidance")
        
        return insights
    
    def generate_participation_recommendations(self, participation_status, session_progress):
        """Generate recommendations for improving participation"""
        
        recommendations = []
        
        # Check for pending agents
        pending_agents = [name for name, status in participation_status.agent_statuses.items() 
                         if status.participation_status == "PENDING"]
        
        if pending_agents:
            recommendations.append(f"Consider activating {len(pending_agents)} pending agents: {', '.join(pending_agents[:3])}")
        
        # Check for insufficient contributions
        insufficient_agents = [name for name, status in participation_status.agent_statuses.items() 
                              if status.participation_status == "INSUFFICIENT"]
        
        if insufficient_agents:
            recommendations.append(f"Provide guidance to agents with insufficient contributions: {', '.join(insufficient_agents)}")
        
        # Check participation balance
        if session_progress.participation_rate < 50:
            recommendations.append("Consider enabling full team participation mode for comprehensive coverage")
        
        return recommendations

5. Command Integration with Existing System

Enhanced Command Compatibility

class CommandCompatibilityManager:
    """Manage compatibility between new and existing commands"""
    
    def __init__(self):
        self.compatibility_matrix = self.build_compatibility_matrix()
        self.command_enhancer = CommandEnhancer()
    
    def enhance_existing_commands(self):
        """Enhance existing commands for full team participation compatibility"""
        
        enhancement_results = {}
        
        # Enhance /pre_select_agents command
        enhancement_results["pre_select_agents"] = self.enhance_pre_select_agents_command()
        
        # Enhance /yolo and /full_yolo commands
        enhancement_results["yolo"] = self.enhance_yolo_commands()
        
        # Enhance /agent-list command
        enhancement_results["agent_list"] = self.enhance_agent_list_command()
        
        return CommandEnhancementResult(
            enhanced_commands=enhancement_results,
            enhancement_success=all(result.success for result in enhancement_results.values())
        )
    
    def enhance_pre_select_agents_command(self):
        """Enhance /pre_select_agents command for full team compatibility"""
        
        # Add full team participation option to agent selection interface
        enhanced_interface = PreSelectAgentsEnhancedInterface(
            show_full_team_option=True,
            integration_with_full_team_commands=True,
            enhanced_agent_grouping=True
        )
        
        return CommandEnhancementResult(
            command_name="pre_select_agents",
            enhancements=[
                "Added full team participation toggle",
                "Enhanced agent grouping by expertise",
                "Integration with full team status tracking"
            ],
            success=True
        )
    
    def enhance_yolo_commands(self):
        """Enhance YOLO commands for full team participation"""
        
        # Enhance /yolo command
        yolo_enhancements = YoloCommandEnhancements(
            full_team_rapid_execution=True,
            parallel_agent_processing=True,
            quality_validation_maintained=True
        )
        
        # Enhance /full_yolo command
        full_yolo_enhancements = FullYoloCommandEnhancements(
            auto_approval_with_full_team=True,
            comprehensive_collaboration_maintained=True,
            quality_assurance_preserved=True
        )
        
        return CommandEnhancementResult(
            command_name="yolo_commands",
            enhancements=[
                "Full team rapid execution support",
                "Parallel processing for multiple agents",
                "Maintained quality validation in rapid mode"
            ],
            success=True
        )

6. Success Metrics and Validation

Command System Success Criteria

Command Functionality: 100% successful execution of all new commands
Integration Compatibility: Seamless integration with existing command system
User Experience: Clear, informative command responses with actionable information
Performance Impact: < 2 seconds response time for all status commands
Error Handling: Comprehensive error handling with helpful suggestions
Documentation: Complete command documentation with examples and use cases

PreviousEnhanced Code Polish & Refinement with Quality Intelligence NextEnhanced Complete Command Reference Manual with Intelligence

Last updated 2 months ago

class EnhancedCommandProcessor: """Enhanced command processor with full team participation support""" def __init__(self): self.command_registry = CommandRegistry() self.participation_manager = ParticipationManager() self.command_validator = CommandValidator() self.execution_engine = ExecutionEngine() self.response_formatter = ResponseFormatter() def register_full_team_commands(self): """Register all full team participation commands""" # Register new commands self.command_registry.register_command(FullTeamOnCommand()) self.command_registry.register_command(FullTeamOffCommand()) self.command_registry.register_command(FullTeamStatusCommand()) # Update existing commands for full team compatibility self.update_existing_commands_for_full_team() return CommandRegistrationResult( registered_commands=["full_team_on", "full_team_off", "full_team_status"], updated_commands=["pre_select_agents", "yolo", "full_yolo", "agent-list"], registration_success=True ) def process_command(self, command_input, session_context): """Process command with enhanced full team participation support""" # Parse command command_parse_result = self.parse_command(command_input) # Validate command command_validation = self.command_validator.validate_command( command_parse_result, session_context ) if not command_validation.valid: return CommandExecutionResult( success=False, error=command_validation.error_message, suggestions=command_validation.suggestions ) # Execute command execution_result = self.execution_engine.execute_command( command_parse_result.command, command_parse_result.parameters, session_context ) # Format response formatted_response = self.response_formatter.format_command_response( execution_result, command_parse_result.command ) return CommandExecutionResult( success=execution_result.success, response=formatted_response, session_updates=execution_result.session_updates ) class CommandRegistry: """Registry for all system commands including full team participation commands""" def __init__(self): self.commands = {} self.command_categories = { "system_control": [], "agent_management": [], "workflow_control": [], "participation_management": [], "information_display": [] } def register_command(self, command_instance): """Register command instance with full metadata""" command_metadata = CommandMetadata( name=command_instance.name, category=command_instance.category, description=command_instance.description, parameters=command_instance.parameters, examples=command_instance.examples, compatibility=command_instance.compatibility, validation_rules=command_instance.validation_rules ) self.commands[command_instance.name] = { "instance": command_instance, "metadata": command_metadata } self.command_categories[command_instance.category].append(command_instance.name) return CommandRegistrationResult( command_name=command_instance.name, registration_success=True )

class FullTeamOnCommand: """Command to enable full team participation mode""" def __init__(self): self.name = "full_team_on" self.category = "participation_management" self.description = "Enable full team participation mode for comprehensive project coverage" self.parameters = [] self.examples = ["/full_team_on"] self.compatibility = ["documentation_mode", "full_development_mode"] self.validation_rules = ["session_active", "orchestrator_mode"] def execute(self, parameters, session_context): """Execute full team on command""" # Validate current session state if not session_context.session_active: return CommandResult( success=False, error="No active session. Please start a workflow session first." ) # Enable full team participation participation_result = session_context.participation_manager.enable_full_team_participation() # Get all available agents all_agents = session_context.agent_registry.get_all_agents() # Determine integration points integration_points = session_context.integration_scheduler.get_integration_points( session_context.workflow_type, all_agents ) # Generate confirmation response confirmation_response = self.generate_confirmation_response( all_agents, integration_points, participation_result ) # Update session configuration session_context.update_configuration({ "full_team_participation": True, "participating_agents": all_agents, "integration_points": integration_points }) return CommandResult( success=True, response=confirmation_response, session_updates={ "full_team_participation": True, "participating_agents": [agent.name for agent in all_agents] } ) def generate_confirmation_response(self, all_agents, integration_points, participation_result): """Generate comprehensive confirmation response""" response_lines = [] # Header response_lines.append("🤝 **Full Team Participation: ACTIVATED**") response_lines.append("") # Participation overview response_lines.append(f"✅ **Status**: Full team participation is now ACTIVE") response_lines.append(f"👥 **Team Size**: {len(all_agents)} agents will collaborate") response_lines.append("") # Agent list with roles response_lines.append("**Participating Agents:**") # Primary agents primary_agents = [agent for agent in all_agents if agent.classification == "PRIMARY"] response_lines.append("*Primary Agents (Always Active):*") for agent in primary_agents: response_lines.append(f" • **{agent.name}** ({agent.title}) - {agent.primary_expertise}") response_lines.append("") # Secondary agents secondary_agents = [agent for agent in all_agents if agent.classification == "SECONDARY"] response_lines.append("*Secondary Agents (Full Team Participation):*") for agent in secondary_agents: response_lines.append(f" • **{agent.name}** ({agent.title}) - {agent.primary_expertise}") response_lines.append("") # Integration points overview response_lines.append("**Integration Points:**") integration_phases = self.group_integration_points_by_phase(integration_points) for phase_name, phase_points in integration_phases.items(): response_lines.append(f"*{phase_name.replace('_', ' ').title()}:*") for point in phase_points: response_lines.append(f" • {point.agent_name}: {point.contribution_description}") response_lines.append("") # Expected benefits response_lines.append("**Expected Benefits:**") response_lines.append(" ✅ Comprehensive expertise coverage across all project aspects") response_lines.append(" ✅ Enhanced quality through multi-perspective validation") response_lines.append(" ✅ Reduced risk through collaborative decision-making") response_lines.append(" ✅ Professional-grade deliverables with domain expert input") response_lines.append("") response_lines.append("🚀 **Ready to proceed with full team collaboration!**") return "\n".join(response_lines) def group_integration_points_by_phase(self, integration_points): """Group integration points by workflow phase""" phase_groups = {} for point in integration_points: phase_name = point.workflow_phase if phase_name not in phase_groups: phase_groups[phase_name] = [] phase_groups[phase_name].append(point) return phase_groups

class FullTeamOffCommand: """Command to disable full team participation mode""" def __init__(self): self.name = "full_team_off" self.category = "participation_management" self.description = "Disable full team participation mode and revert to selective agent activation" self.parameters = [] self.examples = ["/full_team_off"] self.compatibility = ["documentation_mode", "full_development_mode"] self.validation_rules = ["session_active", "full_team_enabled"] def execute(self, parameters, session_context): """Execute full team off command""" # Validate current state if not session_context.full_team_participation_enabled: return CommandResult( success=False, error="Full team participation is not currently enabled." ) # Get current participation status current_participation = session_context.participation_manager.get_current_participation_status() # Disable full team participation disable_result = session_context.participation_manager.disable_full_team_participation() # Determine selective agents for current workflow selective_agents = session_context.agent_selector.select_workflow_agents( session_context.workflow_type, session_context.project_requirements ) # Generate confirmation response confirmation_response = self.generate_disable_confirmation_response( current_participation, selective_agents, disable_result ) # Update session configuration session_context.update_configuration({ "full_team_participation": False, "participating_agents": selective_agents, "participation_mode": "selective" }) return CommandResult( success=True, response=confirmation_response, session_updates={ "full_team_participation": False, "participating_agents": [agent.name for agent in selective_agents] } ) def generate_disable_confirmation_response(self, current_participation, selective_agents, disable_result): """Generate confirmation response for disabling full team participation""" response_lines = [] # Header response_lines.append("🔄 **Full Team Participation: DISABLED**") response_lines.append("") # Status update response_lines.append(f"✅ **Status**: Reverted to selective agent activation") response_lines.append(f"👥 **New Team Size**: {len(selective_agents)} agents (reduced from {current_participation.total_agents})") response_lines.append("") # Current session impact if current_participation.participated_agents: response_lines.append("**Current Session Impact:**") response_lines.append(f" • {len(current_participation.participated_agents)} agents have already contributed") response_lines.append(f" • Their contributions will be preserved in the current session") response_lines.append("") # New selective agent list response_lines.append("**Active Agents (Selective Mode):**") for agent in selective_agents: response_lines.append(f" • **{agent.name}** ({agent.title}) - {agent.primary_expertise}") response_lines.append("") # Deactivated agents deactivated_agents = [agent for agent in current_participation.all_agents if agent not in selective_agents] if deactivated_agents: response_lines.append("**Deactivated Agents:**") for agent in deactivated_agents: response_lines.append(f" • {agent.name} ({agent.title})") response_lines.append("") # Impact summary response_lines.append("**Impact Summary:**") response_lines.append(" ✅ Faster workflow execution with focused agent team") response_lines.append(" ✅ Reduced complexity with essential agents only") response_lines.append(" ✅ Maintained quality with core expertise coverage") response_lines.append("") response_lines.append("🎯 **Continuing with selective agent activation mode**") return "\n".join(response_lines)

class FullTeamStatusCommand: """Command to display current full team participation status""" def __init__(self): self.name = "full_team_status" self.category = "information_display" self.description = "Display detailed full team participation status and progress" self.parameters = [] self.examples = ["/full_team_status"] self.compatibility = ["documentation_mode", "full_development_mode"] self.validation_rules = ["session_active"] def execute(self, parameters, session_context): """Execute full team status command""" # Get current participation status participation_status = session_context.participation_manager.get_detailed_participation_status() # Get session progress session_progress = session_context.progress_calculator.calculate_session_progress() # Get upcoming opportunities upcoming_opportunities = session_context.opportunity_analyzer.get_upcoming_opportunities() # Generate comprehensive status response status_response = self.generate_comprehensive_status_response( participation_status, session_progress, upcoming_opportunities ) return CommandResult( success=True, response=status_response, metadata={ "participation_status": participation_status, "session_progress": session_progress } ) def generate_comprehensive_status_response(self, participation_status, session_progress, upcoming_opportunities): """Generate comprehensive status response""" response_lines = [] # Header with overall status if participation_status.full_team_enabled: response_lines.append("🤝 **Full Team Participation Status: ACTIVE**") else: response_lines.append("🎯 **Selective Agent Participation Status: ACTIVE**") response_lines.append("") # Overall progress metrics response_lines.append("**📊 Overall Progress:**") response_lines.append(f" • **Participation Rate**: {session_progress.participation_rate:.1f}% ({session_progress.participated_count}/{session_progress.total_agents} agents)") response_lines.append(f" • **Average Quality Score**: {session_progress.average_quality_score:.1f}/10") response_lines.append(f" • **Session Duration**: {self.format_duration(session_progress.session_duration)}") response_lines.append(f" • **Current Phase**: {session_progress.current_phase}") response_lines.append("") # Detailed agent participation status response_lines.append("**👥 Agent Participation Details:**") response_lines.append("") # Create participation table response_lines.append("| Agent | Title | Status | Contributions | Quality | Last Activity |") response_lines.append("|-------|-------|--------|---------------|---------|---------------|") for agent_name, agent_status in participation_status.agent_statuses.items(): status_emoji = self.get_status_emoji(agent_status.participation_status) contribution_count = len(agent_status.contributions) quality_score = f"{agent_status.average_quality:.1f}" if agent_status.average_quality else "N/A" last_activity = self.format_last_activity(agent_status.last_contribution_time) response_lines.append(f"| {agent_name} | {agent_status.title} | {status_emoji} | {contribution_count} | {quality_score} | {last_activity} |") response_lines.append("") # Participation breakdown by status response_lines.append("**📈 Participation Breakdown:**") status_counts = self.calculate_status_counts(participation_status.agent_statuses) for status, count in status_counts.items(): emoji = self.get_status_emoji(status) response_lines.append(f" • {emoji}: {count} agents") response_lines.append("") # Upcoming integration opportunities if upcoming_opportunities: response_lines.append("**🔮 Upcoming Integration Opportunities:**") for opportunity in upcoming_opportunities[:5]: # Show top 5 response_lines.append(f" • **{opportunity.agent_name}**: {opportunity.opportunity_description}") response_lines.append(f" *Expected in {opportunity.phase_name} phase*") if len(upcoming_opportunities) > 5: response_lines.append(f" • ... and {len(upcoming_opportunities) - 5} more opportunities") response_lines.append("") # Quality insights response_lines.append("**🎯 Quality Insights:**") quality_insights = self.generate_quality_insights(participation_status, session_progress) for insight in quality_insights: response_lines.append(f" • {insight}") response_lines.append("") # Recommendations recommendations = self.generate_participation_recommendations(participation_status, session_progress) if recommendations: response_lines.append("**💡 Recommendations:**") for recommendation in recommendations: response_lines.append(f" • {recommendation}") return "\n".join(response_lines) def get_status_emoji(self, participation_status): """Get emoji representation of participation status""" status_emoji_map = { "PENDING": "⏳ Pending", "ACTIVE": "🔄 Contributing", "CONTRIBUTED": "✅ Contributed", "COMPLETED": "✅ Complete", "INSUFFICIENT": "❌ Needs Improvement", "SKIPPED": "⏭️ Skipped" } return status_emoji_map.get(participation_status, "❓ Unknown") def format_duration(self, duration_seconds): """Format duration in human-readable format""" if duration_seconds < 60: return f"{int(duration_seconds)}s" elif duration_seconds < 3600: minutes = int(duration_seconds / 60) seconds = int(duration_seconds % 60) return f"{minutes}m {seconds}s" else: hours = int(duration_seconds / 3600) minutes = int((duration_seconds % 3600) / 60) return f"{hours}h {minutes}m" def format_last_activity(self, last_activity_timestamp): """Format last activity timestamp""" if not last_activity_timestamp: return "Never" time_diff = time.time() - last_activity_timestamp if time_diff < 60: return "Just now" elif time_diff < 3600: minutes = int(time_diff / 60) return f"{minutes}m ago" elif time_diff < 86400: hours = int(time_diff / 3600) return f"{hours}h ago" else: days = int(time_diff / 86400) return f"{days}d ago" def generate_quality_insights(self, participation_status, session_progress): """Generate quality insights based on participation data""" insights = [] # Quality distribution analysis high_quality_agents = sum(1 for status in participation_status.agent_statuses.values() if status.average_quality and status.average_quality >= 8.0) if high_quality_agents > 0: insights.append(f"{high_quality_agents} agents are delivering high-quality contributions (8.0+)") # Participation efficiency if session_progress.participation_rate >= 80: insights.append("Excellent participation rate - most agents are actively contributing") elif session_progress.participation_rate >= 60: insights.append("Good participation rate - majority of agents are engaged") else: insights.append("Participation rate could be improved - consider agent activation strategies") # Quality consistency quality_scores = [status.average_quality for status in participation_status.agent_statuses.values() if status.average_quality] if quality_scores: quality_variance = self.calculate_variance(quality_scores) if quality_variance < 1.0: insights.append("Consistent quality across all contributing agents") else: insights.append("Quality variance detected - some agents may need additional guidance") return insights def generate_participation_recommendations(self, participation_status, session_progress): """Generate recommendations for improving participation""" recommendations = [] # Check for pending agents pending_agents = [name for name, status in participation_status.agent_statuses.items() if status.participation_status == "PENDING"] if pending_agents: recommendations.append(f"Consider activating {len(pending_agents)} pending agents: {', '.join(pending_agents[:3])}") # Check for insufficient contributions insufficient_agents = [name for name, status in participation_status.agent_statuses.items() if status.participation_status == "INSUFFICIENT"] if insufficient_agents: recommendations.append(f"Provide guidance to agents with insufficient contributions: {', '.join(insufficient_agents)}") # Check participation balance if session_progress.participation_rate < 50: recommendations.append("Consider enabling full team participation mode for comprehensive coverage") return recommendations

class CommandCompatibilityManager: """Manage compatibility between new and existing commands""" def __init__(self): self.compatibility_matrix = self.build_compatibility_matrix() self.command_enhancer = CommandEnhancer() def enhance_existing_commands(self): """Enhance existing commands for full team participation compatibility""" enhancement_results = {} # Enhance /pre_select_agents command enhancement_results["pre_select_agents"] = self.enhance_pre_select_agents_command() # Enhance /yolo and /full_yolo commands enhancement_results["yolo"] = self.enhance_yolo_commands() # Enhance /agent-list command enhancement_results["agent_list"] = self.enhance_agent_list_command() return CommandEnhancementResult( enhanced_commands=enhancement_results, enhancement_success=all(result.success for result in enhancement_results.values()) ) def enhance_pre_select_agents_command(self): """Enhance /pre_select_agents command for full team compatibility""" # Add full team participation option to agent selection interface enhanced_interface = PreSelectAgentsEnhancedInterface( show_full_team_option=True, integration_with_full_team_commands=True, enhanced_agent_grouping=True ) return CommandEnhancementResult( command_name="pre_select_agents", enhancements=[ "Added full team participation toggle", "Enhanced agent grouping by expertise", "Integration with full team status tracking" ], success=True ) def enhance_yolo_commands(self): """Enhance YOLO commands for full team participation""" # Enhance /yolo command yolo_enhancements = YoloCommandEnhancements( full_team_rapid_execution=True, parallel_agent_processing=True, quality_validation_maintained=True ) # Enhance /full_yolo command full_yolo_enhancements = FullYoloCommandEnhancements( auto_approval_with_full_team=True, comprehensive_collaboration_maintained=True, quality_assurance_preserved=True ) return CommandEnhancementResult( command_name="yolo_commands", enhancements=[ "Full team rapid execution support", "Parallel processing for multiple agents", "Maintained quality validation in rapid mode" ], success=True )

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