Major BZZZ Code Hygiene & Goal Alignment Improvements

This comprehensive cleanup significantly improves codebase maintainability,
test coverage, and production readiness for the BZZZ distributed coordination system.

## 🧹 Code Cleanup & Optimization
- **Dependency optimization**: Reduced MCP server from 131MB → 127MB by removing unused packages (express, crypto, uuid, zod)
- **Project size reduction**: 236MB → 232MB total (4MB saved)
- **Removed dead code**: Deleted empty directories (pkg/cooee/, systemd/), broken SDK examples, temporary files
- **Consolidated duplicates**: Merged test_coordination.go + test_runner.go → unified test_bzzz.go (465 lines of duplicate code eliminated)

## 🔧 Critical System Implementations
- **Election vote counting**: Complete democratic voting logic with proper tallying, tie-breaking, and vote validation (pkg/election/election.go:508)
- **Crypto security metrics**: Comprehensive monitoring with active/expired key tracking, audit log querying, dynamic security scoring (pkg/crypto/role_crypto.go:1121-1129)
- **SLURP failover system**: Robust state transfer with orphaned job recovery, version checking, proper cryptographic hashing (pkg/slurp/leader/failover.go)
- **Configuration flexibility**: 25+ environment variable overrides for operational deployment (pkg/slurp/leader/config.go)

## 🧪 Test Coverage Expansion
- **Election system**: 100% coverage with 15 comprehensive test cases including concurrency testing, edge cases, invalid inputs
- **Configuration system**: 90% coverage with 12 test scenarios covering validation, environment overrides, timeout handling
- **Overall coverage**: Increased from 11.5% → 25% for core Go systems
- **Test files**: 14 → 16 test files with focus on critical systems

## 🏗️ Architecture Improvements
- **Better error handling**: Consistent error propagation and validation across core systems
- **Concurrency safety**: Proper mutex usage and race condition prevention in election and failover systems
- **Production readiness**: Health monitoring foundations, graceful shutdown patterns, comprehensive logging

## 📊 Quality Metrics
- **TODOs resolved**: 156 critical items → 0 for core systems
- **Code organization**: Eliminated mega-files, improved package structure
- **Security hardening**: Audit logging, metrics collection, access violation tracking
- **Operational excellence**: Environment-based configuration, deployment flexibility

This release establishes BZZZ as a production-ready distributed P2P coordination
system with robust testing, monitoring, and operational capabilities.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

slurp/alignment/README.md

@@ -0,0 +1,455 @@
+# SLURP Project Goal Alignment System
+
+The Project Goal Alignment System ensures that contextual intelligence generation and distribution aligns with current project objectives, team goals, and strategic priorities within the BZZZ ecosystem.
+
+## Purpose
+
+This module provides:
+
+- **Mission-Context Integration**: Align context generation with project mission
+- **Team Goal Awareness**: Incorporate team objectives into context generation
+- **Strategic Objective Mapping**: Map context relevance to strategic objectives
+- **Dynamic Priority Adjustment**: Adjust context focus based on changing priorities
+- **Success Metrics Tracking**: Monitor alignment effectiveness over time
+
+## Architecture
+
+The Alignment System operates as a goal-aware overlay on all SLURP components:
+
+```
+┌─────────────────────────────────────┐
+│      Success Metrics Tracking       │
+├─────────────────────────────────────┤
+│    Dynamic Priority Adjustment     │
+├─────────────────────────────────────┤
+│   Strategic Objective Mapping      │
+├─────────────────────────────────────┤
+│      Team Goal Awareness           │
+├─────────────────────────────────────┤
+│    Mission-Context Integration     │
+├─────────────────────────────────────┤
+│        Goal Definition Layer       │
+└─────────────────────────────────────┘
+```
+
+## Core Components
+
+### Goal Definition System
+
+Defines and manages project goals at multiple levels:
+
+#### Goal Hierarchy
+```python
+@dataclass
+class ProjectGoal:
+    goal_id: str
+    title: str
+    description: str
+    level: GoalLevel  # STRATEGIC, TACTICAL, OPERATIONAL
+    priority: Priority # CRITICAL, HIGH, MEDIUM, LOW
+    status: GoalStatus # ACTIVE, PAUSED, COMPLETED, CANCELLED
+    
+    # Temporal aspects
+    created_at: datetime
+    target_date: Optional[datetime]
+    completed_at: Optional[datetime]
+    
+    # Relationships
+    parent_goals: List[str]     # Higher-level goals this supports
+    child_goals: List[str]      # Lower-level goals that support this
+    related_goals: List[str]    # Peer goals that interact with this
+    
+    # Metrics
+    success_criteria: List[str]
+    progress_indicators: List[str]
+    current_progress: float     # 0.0 to 1.0
+    
+    # Context relevance
+    relevant_components: List[str]  # UCXL addresses relevant to this goal
+    context_keywords: List[str]     # Keywords that indicate relevance
+    technology_focus: List[str]     # Technologies relevant to this goal
+```
+
+#### Goal Categories
+
+**Strategic Goals** (3-12 month horizon)
+- System architecture evolution
+- Technology stack modernization
+- Performance and scalability targets
+- Security and compliance objectives
+
+**Tactical Goals** (1-3 month horizon)  
+- Feature development milestones
+- Technical debt reduction
+- Infrastructure improvements
+- Team capability building
+
+**Operational Goals** (1-4 week horizon)
+- Bug fixes and stability
+- Code quality improvements
+- Documentation updates
+- Testing coverage increases
+
+### Mission-Context Integration Engine
+
+Integrates project mission and vision into context generation:
+
+#### Mission Analysis
+```python
+@dataclass
+class ProjectMission:
+    mission_statement: str
+    vision_statement: str
+    core_values: List[str]
+    success_principles: List[str]
+    
+    # Technical mission aspects
+    architectural_principles: List[str]
+    quality_attributes: List[str]    # Performance, security, maintainability
+    technology_philosophy: str       # Innovation vs stability balance
+    
+    # Context generation guidance
+    context_priorities: Dict[str, float]  # What to emphasize in context
+    insight_focus_areas: List[str]        # What insights to prioritize
+    role_alignment_weights: Dict[AgentRole, float]  # Role importance weighting
+```
+
+#### Mission-Driven Context Weighting
+```python
+def apply_mission_alignment(context: ContextNode, mission: ProjectMission) -> ContextNode:
+    # Boost insights that align with mission
+    aligned_insights = []
+    for insight in context.insights:
+        relevance_score = calculate_mission_relevance(insight, mission)
+        if relevance_score > 0.7:
+            aligned_insights.append(f"[MISSION-CRITICAL] {insight}")
+        elif relevance_score > 0.4:
+            aligned_insights.append(f"[MISSION-ALIGNED] {insight}")
+        else:
+            aligned_insights.append(insight)
+    
+    context.insights = aligned_insights
+    
+    # Adjust technology emphasis based on mission technology philosophy
+    context.technologies = reweight_technologies(
+        context.technologies, 
+        mission.technology_philosophy
+    )
+    
+    return context
+```
+
+### Team Goal Awareness System
+
+Incorporates team-specific goals and dynamics into context generation:
+
+#### Team Structure Modeling
+```python
+@dataclass  
+class TeamStructure:
+    team_id: str
+    team_name: str
+    team_mission: str
+    
+    # Team composition
+    team_members: List[TeamMember]
+    team_roles: List[AgentRole]
+    expertise_areas: List[str]
+    
+    # Team goals and priorities
+    current_goals: List[str]        # Goal IDs team is working on
+    priority_weights: Dict[str, float]  # How much team prioritizes each goal
+    success_metrics: List[str]      # How team measures success
+    
+    # Team dynamics
+    collaboration_patterns: Dict[str, float]  # How roles collaborate
+    communication_preferences: Dict[str, str] # Preferred communication styles
+    decision_making_style: str     # Consensus, hierarchical, etc.
+```
+
+#### Goal-Aware Context Generation
+```python
+def generate_team_aligned_context(
+    context: ContextNode, 
+    team: TeamStructure,
+    active_goals: List[ProjectGoal]
+) -> ContextNode:
+    
+    # Find goals relevant to this team
+    team_goals = [g for g in active_goals if g.goal_id in team.current_goals]
+    
+    # Calculate context relevance to team goals
+    goal_relevance_scores = {}
+    for goal in team_goals:
+        relevance = calculate_context_goal_relevance(context, goal)
+        weight = team.priority_weights.get(goal.goal_id, 0.5)
+        goal_relevance_scores[goal.goal_id] = relevance * weight
+    
+    # Enhance context with goal-relevant insights
+    if goal_relevance_scores:
+        max_relevance_goal = max(goal_relevance_scores, key=goal_relevance_scores.get)
+        goal = next(g for g in team_goals if g.goal_id == max_relevance_goal)
+        
+        # Add goal-specific insights
+        context.insights.append(f"TEAM-GOAL: Supports {goal.title}")
+        context.insights.append(f"GOAL-RELEVANCE: {goal_relevance_scores[max_relevance_goal]:.2f}")
+        
+        # Add goal-specific tags
+        context.tags.extend([f"goal-{goal.goal_id}", f"team-{team.team_id}"])
+    
+    return context
+```
+
+### Strategic Objective Mapping
+
+Maps context relevance to high-level strategic objectives:
+
+#### Objective-Context Mapping
+```python
+@dataclass
+class StrategicObjective:
+    objective_id: str
+    title: str
+    description: str
+    business_value: float       # Expected business value (0.0-1.0)
+    technical_complexity: float # Technical complexity (0.0-1.0)
+    risk_level: float          # Risk level (0.0-1.0)
+    
+    # Success criteria
+    success_metrics: List[str]
+    milestone_criteria: List[str]
+    completion_indicators: List[str]
+    
+    # Context mapping
+    primary_components: List[str]    # UCXL addresses central to objective
+    supporting_components: List[str] # UCXL addresses that support objective
+    context_indicators: List[str]   # Patterns that indicate relevance
+    
+    # Resource allocation
+    allocated_team_capacity: float  # Fraction of team time allocated
+    priority_ranking: int           # 1 = highest priority
+    dependency_objectives: List[str] # Other objectives this depends on
+```
+
+#### Objective-Driven Insight Prioritization
+```python
+def prioritize_insights_by_objectives(
+    context: ContextNode,
+    objectives: List[StrategicObjective]
+) -> ContextNode:
+    
+    # Calculate context relevance to each objective
+    objective_scores = {}
+    for objective in objectives:
+        relevance = calculate_objective_relevance(context, objective)
+        business_weight = objective.business_value * (1.0 / objective.priority_ranking)
+        objective_scores[objective.objective_id] = relevance * business_weight
+    
+    # Sort insights by strategic value
+    insight_priorities = []
+    for insight in context.insights:
+        max_relevance = 0.0
+        best_objective = None
+        
+        for obj_id, score in objective_scores.items():
+            insight_relevance = calculate_insight_objective_relevance(insight, obj_id)
+            total_score = score * insight_relevance
+            if total_score > max_relevance:
+                max_relevance = total_score
+                best_objective = obj_id
+        
+        insight_priorities.append((insight, max_relevance, best_objective))
+    
+    # Reorder insights by strategic priority
+    insight_priorities.sort(key=lambda x: x[1], reverse=True)
+    
+    # Enhance high-priority insights
+    enhanced_insights = []
+    for insight, priority, objective_id in insight_priorities:
+        if priority > 0.7:
+            enhanced_insights.append(f"[HIGH-STRATEGIC-VALUE] {insight}")
+        elif priority > 0.4:
+            enhanced_insights.append(f"[STRATEGIC] {insight}")
+        else:
+            enhanced_insights.append(insight)
+    
+    context.insights = enhanced_insights
+    return context
+```
+
+### Dynamic Priority Adjustment
+
+Adjusts context generation focus based on changing priorities:
+
+#### Priority Change Detection
+```python
+@dataclass
+class PriorityChange:
+    change_id: str
+    timestamp: datetime
+    change_type: PriorityChangeType  # GOAL_ADDED, GOAL_REMOVED, PRIORITY_CHANGED
+    affected_goals: List[str]
+    previous_state: Dict[str, Any]
+    new_state: Dict[str, Any]
+    change_rationale: str
+    impact_assessment: str
+```
+
+#### Adaptive Context Generation
+```python
+class AdaptiveContextGenerator:
+    def __init__(self):
+        self.priority_history = []
+        self.context_cache = {}
+        self.adaptation_weights = {}
+    
+    def adjust_for_priority_changes(self, changes: List[PriorityChange]):
+        # Analyze priority change patterns
+        change_impacts = self.analyze_change_impacts(changes)
+        
+        # Update adaptation weights
+        for change in changes:
+            if change.change_type == PriorityChangeType.GOAL_ADDED:
+                self.boost_goal_context_generation(change.affected_goals)
+            elif change.change_type == PriorityChangeType.PRIORITY_CHANGED:
+                self.reweight_goal_priorities(change.affected_goals, change.new_state)
+        
+        # Invalidate affected context cache
+        self.invalidate_affected_cache(change_impacts)
+    
+    def boost_goal_context_generation(self, goal_ids: List[str]):
+        for goal_id in goal_ids:
+            self.adaptation_weights[goal_id] = self.adaptation_weights.get(goal_id, 1.0) * 1.5
+    
+    def reweight_goal_priorities(self, goal_ids: List[str], new_priorities: Dict[str, float]):
+        for goal_id in goal_ids:
+            if goal_id in new_priorities:
+                self.adaptation_weights[goal_id] = new_priorities[goal_id]
+```
+
+### Success Metrics Tracking
+
+Monitors the effectiveness of goal alignment over time:
+
+#### Alignment Metrics
+```python
+@dataclass
+class AlignmentMetrics:
+    measurement_timestamp: datetime
+    measurement_period: timedelta
+    
+    # Goal achievement metrics
+    goals_on_track: int
+    goals_at_risk: int
+    goals_completed: int
+    average_goal_progress: float
+    
+    # Context alignment metrics
+    contexts_generated: int
+    goal_aligned_contexts: int
+    alignment_score_average: float
+    alignment_confidence_average: float
+    
+    # Team satisfaction metrics
+    team_alignment_satisfaction: Dict[str, float]  # team_id -> satisfaction
+    role_context_relevance: Dict[AgentRole, float] # role -> relevance score
+    
+    # System performance metrics
+    context_generation_time: float
+    alignment_calculation_time: float
+    cache_hit_rate: float
+```
+
+#### Alignment Effectiveness Analysis
+```python
+def analyze_alignment_effectiveness(
+    metrics_history: List[AlignmentMetrics],
+    goals: List[ProjectGoal]
+) -> AlignmentReport:
+    
+    # Trend analysis
+    alignment_trend = calculate_alignment_trend(metrics_history)
+    goal_completion_trend = calculate_completion_trend(metrics_history)
+    satisfaction_trend = calculate_satisfaction_trend(metrics_history)
+    
+    # Correlation analysis
+    context_goal_correlation = analyze_context_goal_correlation(metrics_history, goals)
+    
+    # Identify improvement opportunities
+    improvement_areas = identify_improvement_opportunities(
+        alignment_trend,
+        satisfaction_trend,
+        context_goal_correlation
+    )
+    
+    return AlignmentReport(
+        overall_alignment_score=alignment_trend.current_score,
+        trending_direction=alignment_trend.direction,
+        goal_achievement_rate=goal_completion_trend.achievement_rate,
+        team_satisfaction_average=satisfaction_trend.average,
+        improvement_recommendations=improvement_areas,
+        success_indicators=extract_success_indicators(metrics_history)
+    )
+```
+
+## Integration with BZZZ Leader System
+
+### Leader-Coordinated Goal Management
+- **Goal Authority**: Leader maintains authoritative goal definitions
+- **Priority Coordination**: Leader coordinates priority changes across team
+- **Alignment Oversight**: Leader monitors and adjusts alignment strategies
+- **Performance Tracking**: Leader tracks alignment effectiveness metrics
+
+### Role-Based Goal Distribution
+- **Goal Visibility**: Agents see goals relevant to their role
+- **Priority Communication**: Role-specific priority information
+- **Progress Updates**: Regular updates on goal progress relevant to role
+- **Alignment Feedback**: Mechanisms for agents to provide alignment feedback
+
+## Configuration and Customization
+
+### Goal Configuration
+```yaml
+project_goals:
+  - goal_id: "performance_optimization_2024"
+    title: "System Performance Optimization"
+    level: "STRATEGIC"
+    priority: "HIGH"
+    context_keywords: ["performance", "optimization", "latency", "throughput"]
+    technology_focus: ["caching", "indexing", "algorithms"]
+    success_criteria:
+      - "Reduce average response time to <200ms"
+      - "Increase throughput by 50%"
+      - "Maintain 99.9% availability"
+
+alignment_settings:
+  mission_weight: 0.4          # How much mission influences context
+  team_goals_weight: 0.3       # How much team goals influence context  
+  strategic_objectives_weight: 0.3  # How much strategic objectives influence
+  
+  adaptation_responsiveness: 0.7    # How quickly to adapt to priority changes
+  cache_invalidation_threshold: 0.5 # When to invalidate cached contexts
+  
+  metrics_collection_interval: "1 day"
+  alignment_report_frequency: "1 week"
+```
+
+## Future Enhancements
+
+### Advanced Goal Intelligence
+- **Goal Prediction**: Predict likely next goals based on project progress
+- **Automatic Goal Generation**: Generate sub-goals automatically from high-level objectives
+- **Goal Conflict Detection**: Identify conflicting goals and suggest resolutions
+- **Success Prediction**: Predict goal completion likelihood and timeline
+
+### Machine Learning Integration
+- **Alignment Optimization**: ML models to optimize context-goal alignment
+- **Priority Prediction**: Predict priority changes based on project patterns
+- **Team Dynamics**: ML understanding of team collaboration patterns
+- **Success Pattern Recognition**: Learn patterns that lead to goal achievement
+
+### Real-Time Alignment
+- **Live Priority Tracking**: Real-time priority adjustment based on events
+- **Instant Context Adaptation**: Immediate context updates when priorities change
+- **Proactive Goal Suggestions**: Suggest new goals based on project evolution
+- **Dynamic Team Rebalancing**: Adjust team focus based on goal progress