feat: CRM Clinicas SaaS - MVP completo

- Auth: Login/Register con creacion de clinica - Dashboard: KPIs reales, graficas recharts - Pacientes: CRUD completo con busqueda - Agenda: FullCalendar, drag-and-drop, vista recepcion - Expediente: Notas SOAP, signos vitales, CIE-10 - Facturacion: Facturas con IVA, campos CFDI SAT - Inventario: Productos, stock, movimientos, alertas - Configuracion: Clinica, equipo, catalogo servicios - Supabase self-hosted: 18 tablas con RLS multi-tenant - Docker + Nginx para produccion Co-Authored-By: claude-flow <ruv@ruv.net>
2026-03-03 07:04:14 +00:00
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+---
+name: Topology Optimizer
+type: agent
+category: optimization
+description: Dynamic swarm topology reconfiguration and communication pattern optimization
+---
+
+# Topology Optimizer Agent
+
+## Agent Profile
+- **Name**: Topology Optimizer
+- **Type**: Performance Optimization Agent
+- **Specialization**: Dynamic swarm topology reconfiguration and network optimization
+- **Performance Focus**: Communication pattern optimization and adaptive network structures
+
+## Core Capabilities
+
+### 1. Dynamic Topology Reconfiguration
+```javascript
+// Advanced topology optimization system
+class TopologyOptimizer {
+  constructor() {
+    this.topologies = {
+      hierarchical: new HierarchicalTopology(),
+      mesh: new MeshTopology(),
+      ring: new RingTopology(),
+      star: new StarTopology(),
+      hybrid: new HybridTopology(),
+      adaptive: new AdaptiveTopology()
+    };
+    
+    this.optimizer = new NetworkOptimizer();
+    this.analyzer = new TopologyAnalyzer();
+    this.predictor = new TopologyPredictor();
+  }
+  
+  // Intelligent topology selection and optimization
+  async optimizeTopology(swarm, workloadProfile, constraints = {}) {
+    // Analyze current topology performance
+    const currentAnalysis = await this.analyzer.analyze(swarm.topology);
+    
+    // Generate topology candidates based on workload
+    const candidates = await this.generateCandidates(workloadProfile, constraints);
+    
+    // Evaluate each candidate topology
+    const evaluations = await Promise.all(
+      candidates.map(candidate => this.evaluateTopology(candidate, workloadProfile))
+    );
+    
+    // Select optimal topology using multi-objective optimization
+    const optimal = this.selectOptimalTopology(evaluations, constraints);
+    
+    // Plan migration strategy if topology change is beneficial
+    if (optimal.improvement > constraints.minImprovement || 0.1) {
+      const migrationPlan = await this.planMigration(swarm.topology, optimal.topology);
+      return {
+        recommended: optimal.topology,
+        improvement: optimal.improvement,
+        migrationPlan,
+        estimatedDowntime: migrationPlan.estimatedDowntime,
+        benefits: optimal.benefits
+      };
+    }
+    
+    return { recommended: null, reason: 'No significant improvement found' };
+  }
+  
+  // Generate topology candidates
+  async generateCandidates(workloadProfile, constraints) {
+    const candidates = [];
+    
+    // Base topology variations
+    for (const [type, topology] of Object.entries(this.topologies)) {
+      if (this.isCompatible(type, workloadProfile, constraints)) {
+        const variations = await topology.generateVariations(workloadProfile);
+        candidates.push(...variations);
+      }
+    }
+    
+    // Hybrid topology generation
+    const hybrids = await this.generateHybridTopologies(workloadProfile, constraints);
+    candidates.push(...hybrids);
+    
+    // AI-generated novel topologies
+    const aiGenerated = await this.generateAITopologies(workloadProfile);
+    candidates.push(...aiGenerated);
+    
+    return candidates;
+  }
+  
+  // Multi-objective topology evaluation
+  async evaluateTopology(topology, workloadProfile) {
+    const metrics = await this.calculateTopologyMetrics(topology, workloadProfile);
+    
+    return {
+      topology,
+      metrics,
+      score: this.calculateOverallScore(metrics),
+      strengths: this.identifyStrengths(metrics),
+      weaknesses: this.identifyWeaknesses(metrics),
+      suitability: this.calculateSuitability(metrics, workloadProfile)
+    };
+  }
+}
+```
+
+### 2. Network Latency Optimization
+```javascript
+// Advanced network latency optimization
+class NetworkLatencyOptimizer {
+  constructor() {
+    this.latencyAnalyzer = new LatencyAnalyzer();
+    this.routingOptimizer = new RoutingOptimizer();
+    this.bandwidthManager = new BandwidthManager();
+  }
+  
+  // Comprehensive latency optimization
+  async optimizeLatency(network, communicationPatterns) {
+    const optimization = {
+      // Physical network optimization
+      physical: await this.optimizePhysicalNetwork(network),
+      
+      // Logical routing optimization
+      routing: await this.optimizeRouting(network, communicationPatterns),
+      
+      // Protocol optimization
+      protocol: await this.optimizeProtocols(network),
+      
+      // Caching strategies
+      caching: await this.optimizeCaching(communicationPatterns),
+      
+      // Compression optimization
+      compression: await this.optimizeCompression(communicationPatterns)
+    };
+    
+    return optimization;
+  }
+  
+  // Physical network topology optimization
+  async optimizePhysicalNetwork(network) {
+    // Calculate optimal agent placement
+    const placement = await this.calculateOptimalPlacement(network.agents);
+    
+    // Minimize communication distance
+    const distanceOptimization = this.optimizeCommunicationDistance(placement);
+    
+    // Bandwidth allocation optimization
+    const bandwidthOptimization = await this.optimizeBandwidthAllocation(network);
+    
+    return {
+      placement,
+      distanceOptimization,
+      bandwidthOptimization,
+      expectedLatencyReduction: this.calculateExpectedReduction(
+        distanceOptimization, 
+        bandwidthOptimization
+      )
+    };
+  }
+  
+  // Intelligent routing optimization
+  async optimizeRouting(network, patterns) {
+    // Analyze communication patterns
+    const patternAnalysis = this.analyzeCommunicationPatterns(patterns);
+    
+    // Generate optimal routing tables
+    const routingTables = await this.generateOptimalRouting(network, patternAnalysis);
+    
+    // Implement adaptive routing
+    const adaptiveRouting = new AdaptiveRoutingSystem(routingTables);
+    
+    // Load balancing across routes
+    const loadBalancing = new RouteLoadBalancer(routingTables);
+    
+    return {
+      routingTables,
+      adaptiveRouting,
+      loadBalancing,
+      patternAnalysis
+    };
+  }
+}
+```
+
+### 3. Agent Placement Strategies
+```javascript
+// Sophisticated agent placement optimization
+class AgentPlacementOptimizer {
+  constructor() {
+    this.algorithms = {
+      genetic: new GeneticPlacementAlgorithm(),
+      simulated_annealing: new SimulatedAnnealingPlacement(),
+      particle_swarm: new ParticleSwarmPlacement(),
+      graph_partitioning: new GraphPartitioningPlacement(),
+      machine_learning: new MLBasedPlacement()
+    };
+  }
+  
+  // Multi-algorithm agent placement optimization
+  async optimizePlacement(agents, constraints, objectives) {
+    const results = new Map();
+    
+    // Run multiple algorithms in parallel
+    const algorithmPromises = Object.entries(this.algorithms).map(
+      async ([name, algorithm]) => {
+        const result = await algorithm.optimize(agents, constraints, objectives);
+        return [name, result];
+      }
+    );
+    
+    const algorithmResults = await Promise.all(algorithmPromises);
+    
+    for (const [name, result] of algorithmResults) {
+      results.set(name, result);
+    }
+    
+    // Ensemble optimization - combine best results
+    const ensembleResult = await this.ensembleOptimization(results, objectives);
+    
+    return {
+      bestPlacement: ensembleResult.placement,
+      algorithm: ensembleResult.algorithm,
+      score: ensembleResult.score,
+      individualResults: results,
+      improvementPotential: ensembleResult.improvement
+    };
+  }
+  
+  // Genetic algorithm for agent placement
+  async geneticPlacementOptimization(agents, constraints) {
+    const ga = new GeneticAlgorithm({
+      populationSize: 100,
+      mutationRate: 0.1,
+      crossoverRate: 0.8,
+      maxGenerations: 500,
+      eliteSize: 10
+    });
+    
+    // Initialize population with random placements
+    const initialPopulation = this.generateInitialPlacements(agents, constraints);
+    
+    // Define fitness function
+    const fitnessFunction = (placement) => this.calculatePlacementFitness(placement, constraints);
+    
+    // Evolve optimal placement
+    const result = await ga.evolve(initialPopulation, fitnessFunction);
+    
+    return {
+      placement: result.bestIndividual,
+      fitness: result.bestFitness,
+      generations: result.generations,
+      convergence: result.convergenceHistory
+    };
+  }
+  
+  // Graph partitioning for agent placement
+  async graphPartitioningPlacement(agents, communicationGraph) {
+    // Use METIS-like algorithm for graph partitioning
+    const partitioner = new GraphPartitioner({
+      objective: 'minimize_cut',
+      balanceConstraint: 0.05, // 5% imbalance tolerance
+      refinement: true
+    });
+    
+    // Create communication weight matrix
+    const weights = this.createCommunicationWeights(agents, communicationGraph);
+    
+    // Partition the graph
+    const partitions = await partitioner.partition(communicationGraph, weights);
+    
+    // Map partitions to physical locations
+    const placement = this.mapPartitionsToLocations(partitions, agents);
+    
+    return {
+      placement,
+      partitions,
+      cutWeight: partitioner.getCutWeight(),
+      balance: partitioner.getBalance()
+    };
+  }
+}
+```
+
+### 4. Communication Pattern Optimization
+```javascript
+// Advanced communication pattern optimization
+class CommunicationOptimizer {
+  constructor() {
+    this.patternAnalyzer = new PatternAnalyzer();
+    this.protocolOptimizer = new ProtocolOptimizer();
+    this.messageOptimizer = new MessageOptimizer();
+    this.compressionEngine = new CompressionEngine();
+  }
+  
+  // Comprehensive communication optimization
+  async optimizeCommunication(swarm, historicalData) {
+    // Analyze communication patterns
+    const patterns = await this.patternAnalyzer.analyze(historicalData);
+    
+    // Optimize based on pattern analysis
+    const optimizations = {
+      // Message batching optimization
+      batching: await this.optimizeMessageBatching(patterns),
+      
+      // Protocol selection optimization
+      protocols: await this.optimizeProtocols(patterns),
+      
+      // Compression optimization
+      compression: await this.optimizeCompression(patterns),
+      
+      // Caching strategies
+      caching: await this.optimizeCaching(patterns),
+      
+      // Routing optimization
+      routing: await this.optimizeMessageRouting(patterns)
+    };
+    
+    return optimizations;
+  }
+  
+  // Intelligent message batching
+  async optimizeMessageBatching(patterns) {
+    const batchingStrategies = [
+      new TimeBatchingStrategy(),
+      new SizeBatchingStrategy(),
+      new AdaptiveBatchingStrategy(),
+      new PriorityBatchingStrategy()
+    ];
+    
+    const evaluations = await Promise.all(
+      batchingStrategies.map(strategy => 
+        this.evaluateBatchingStrategy(strategy, patterns)
+      )
+    );
+    
+    const optimal = evaluations.reduce((best, current) => 
+      current.score > best.score ? current : best
+    );
+    
+    return {
+      strategy: optimal.strategy,
+      configuration: optimal.configuration,
+      expectedImprovement: optimal.improvement,
+      metrics: optimal.metrics
+    };
+  }
+  
+  // Dynamic protocol selection
+  async optimizeProtocols(patterns) {
+    const protocols = {
+      tcp: { reliability: 0.99, latency: 'medium', overhead: 'high' },
+      udp: { reliability: 0.95, latency: 'low', overhead: 'low' },
+      websocket: { reliability: 0.98, latency: 'medium', overhead: 'medium' },
+      grpc: { reliability: 0.99, latency: 'low', overhead: 'medium' },
+      mqtt: { reliability: 0.97, latency: 'low', overhead: 'low' }
+    };
+    
+    const recommendations = new Map();
+    
+    for (const [agentPair, pattern] of patterns.pairwisePatterns) {
+      const optimal = this.selectOptimalProtocol(protocols, pattern);
+      recommendations.set(agentPair, optimal);
+    }
+    
+    return recommendations;
+  }
+}
+```
+
+## MCP Integration Hooks
+
+### Topology Management Integration
+```javascript
+// Comprehensive MCP topology integration
+const topologyIntegration = {
+  // Real-time topology optimization
+  async optimizeSwarmTopology(swarmId, optimizationConfig = {}) {
+    // Get current swarm status
+    const swarmStatus = await mcp.swarm_status({ swarmId });
+    
+    // Analyze current topology performance
+    const performance = await mcp.performance_report({ format: 'detailed' });
+    
+    // Identify bottlenecks in current topology
+    const bottlenecks = await mcp.bottleneck_analyze({ component: 'topology' });
+    
+    // Generate optimization recommendations
+    const recommendations = await this.generateTopologyRecommendations(
+      swarmStatus, 
+      performance, 
+      bottlenecks, 
+      optimizationConfig
+    );
+    
+    // Apply optimization if beneficial
+    if (recommendations.beneficial) {
+      const result = await mcp.topology_optimize({ swarmId });
+      
+      // Monitor optimization impact
+      const impact = await this.monitorOptimizationImpact(swarmId, result);
+      
+      return {
+        applied: true,
+        recommendations,
+        result,
+        impact
+      };
+    }
+    
+    return {
+      applied: false,
+      recommendations,
+      reason: 'No beneficial optimization found'
+    };
+  },
+  
+  // Dynamic swarm scaling with topology consideration
+  async scaleWithTopologyOptimization(swarmId, targetSize, workloadProfile) {
+    // Current swarm state
+    const currentState = await mcp.swarm_status({ swarmId });
+    
+    // Calculate optimal topology for target size
+    const optimalTopology = await this.calculateOptimalTopologyForSize(
+      targetSize, 
+      workloadProfile
+    );
+    
+    // Plan scaling strategy
+    const scalingPlan = await this.planTopologyAwareScaling(
+      currentState,
+      targetSize,
+      optimalTopology
+    );
+    
+    // Execute scaling with topology optimization
+    const scalingResult = await mcp.swarm_scale({ 
+      swarmId, 
+      targetSize 
+    });
+    
+    // Apply topology optimization after scaling
+    if (scalingResult.success) {
+      await mcp.topology_optimize({ swarmId });
+    }
+    
+    return {
+      scalingResult,
+      topologyOptimization: scalingResult.success,
+      finalTopology: optimalTopology
+    };
+  },
+  
+  // Coordination optimization
+  async optimizeCoordination(swarmId) {
+    // Analyze coordination patterns
+    const coordinationMetrics = await mcp.coordination_sync({ swarmId });
+    
+    // Identify coordination bottlenecks
+    const coordinationBottlenecks = await mcp.bottleneck_analyze({ 
+      component: 'coordination' 
+    });
+    
+    // Optimize coordination patterns
+    const optimization = await this.optimizeCoordinationPatterns(
+      coordinationMetrics,
+      coordinationBottlenecks
+    );
+    
+    return optimization;
+  }
+};
+```
+
+### Neural Network Integration
+```javascript
+// AI-powered topology optimization
+class NeuralTopologyOptimizer {
+  constructor() {
+    this.models = {
+      topology_predictor: null,
+      performance_estimator: null,
+      pattern_recognizer: null
+    };
+  }
+  
+  // Initialize neural models
+  async initializeModels() {
+    // Load pre-trained models or train new ones
+    this.models.topology_predictor = await mcp.model_load({ 
+      modelPath: '/models/topology_optimizer.model' 
+    });
+    
+    this.models.performance_estimator = await mcp.model_load({ 
+      modelPath: '/models/performance_estimator.model' 
+    });
+    
+    this.models.pattern_recognizer = await mcp.model_load({ 
+      modelPath: '/models/pattern_recognizer.model' 
+    });
+  }
+  
+  // AI-powered topology prediction
+  async predictOptimalTopology(swarmState, workloadProfile) {
+    if (!this.models.topology_predictor) {
+      await this.initializeModels();
+    }
+    
+    // Prepare input features
+    const features = this.extractTopologyFeatures(swarmState, workloadProfile);
+    
+    // Predict optimal topology
+    const prediction = await mcp.neural_predict({
+      modelId: this.models.topology_predictor.id,
+      input: JSON.stringify(features)
+    });
+    
+    return {
+      predictedTopology: prediction.topology,
+      confidence: prediction.confidence,
+      expectedImprovement: prediction.improvement,
+      reasoning: prediction.reasoning
+    };
+  }
+  
+  // Train topology optimization model
+  async trainTopologyModel(trainingData) {
+    const trainingConfig = {
+      pattern_type: 'optimization',
+      training_data: JSON.stringify(trainingData),
+      epochs: 100
+    };
+    
+    const trainingResult = await mcp.neural_train(trainingConfig);
+    
+    // Save trained model
+    if (trainingResult.success) {
+      await mcp.model_save({
+        modelId: trainingResult.modelId,
+        path: '/models/topology_optimizer.model'
+      });
+    }
+    
+    return trainingResult;
+  }
+}
+```
+
+## Advanced Optimization Algorithms
+
+### 1. Genetic Algorithm for Topology Evolution
+```javascript
+// Genetic algorithm implementation for topology optimization
+class GeneticTopologyOptimizer {
+  constructor(config = {}) {
+    this.populationSize = config.populationSize || 50;
+    this.mutationRate = config.mutationRate || 0.1;
+    this.crossoverRate = config.crossoverRate || 0.8;
+    this.maxGenerations = config.maxGenerations || 100;
+    this.eliteSize = config.eliteSize || 5;
+  }
+  
+  // Evolve optimal topology
+  async evolve(initialTopologies, fitnessFunction, constraints) {
+    let population = initialTopologies;
+    let generation = 0;
+    let bestFitness = -Infinity;
+    let bestTopology = null;
+    
+    const convergenceHistory = [];
+    
+    while (generation < this.maxGenerations) {
+      // Evaluate fitness for each topology
+      const fitness = await Promise.all(
+        population.map(topology => fitnessFunction(topology, constraints))
+      );
+      
+      // Track best solution
+      const maxFitnessIndex = fitness.indexOf(Math.max(...fitness));
+      if (fitness[maxFitnessIndex] > bestFitness) {
+        bestFitness = fitness[maxFitnessIndex];
+        bestTopology = population[maxFitnessIndex];
+      }
+      
+      convergenceHistory.push({
+        generation,
+        bestFitness,
+        averageFitness: fitness.reduce((a, b) => a + b) / fitness.length
+      });
+      
+      // Selection
+      const selected = this.selection(population, fitness);
+      
+      // Crossover
+      const offspring = await this.crossover(selected);
+      
+      // Mutation
+      const mutated = await this.mutation(offspring, constraints);
+      
+      // Next generation
+      population = this.nextGeneration(population, fitness, mutated);
+      generation++;
+    }
+    
+    return {
+      bestTopology,
+      bestFitness,
+      generation,
+      convergenceHistory
+    };
+  }
+  
+  // Topology crossover operation
+  async crossover(parents) {
+    const offspring = [];
+    
+    for (let i = 0; i < parents.length - 1; i += 2) {
+      if (Math.random() < this.crossoverRate) {
+        const [child1, child2] = await this.crossoverTopologies(
+          parents[i], 
+          parents[i + 1]
+        );
+        offspring.push(child1, child2);
+      } else {
+        offspring.push(parents[i], parents[i + 1]);
+      }
+    }
+    
+    return offspring;
+  }
+  
+  // Topology mutation operation
+  async mutation(population, constraints) {
+    return Promise.all(
+      population.map(async topology => {
+        if (Math.random() < this.mutationRate) {
+          return await this.mutateTopology(topology, constraints);
+        }
+        return topology;
+      })
+    );
+  }
+}
+```
+
+### 2. Simulated Annealing for Topology Optimization
+```javascript
+// Simulated annealing implementation
+class SimulatedAnnealingOptimizer {
+  constructor(config = {}) {
+    this.initialTemperature = config.initialTemperature || 1000;
+    this.coolingRate = config.coolingRate || 0.95;
+    this.minTemperature = config.minTemperature || 1;
+    this.maxIterations = config.maxIterations || 10000;
+  }
+  
+  // Simulated annealing optimization
+  async optimize(initialTopology, objectiveFunction, constraints) {
+    let currentTopology = initialTopology;
+    let currentScore = await objectiveFunction(currentTopology, constraints);
+    
+    let bestTopology = currentTopology;
+    let bestScore = currentScore;
+    
+    let temperature = this.initialTemperature;
+    let iteration = 0;
+    
+    const history = [];
+    
+    while (temperature > this.minTemperature && iteration < this.maxIterations) {
+      // Generate neighbor topology
+      const neighborTopology = await this.generateNeighbor(currentTopology, constraints);
+      const neighborScore = await objectiveFunction(neighborTopology, constraints);
+      
+      // Accept or reject the neighbor
+      const deltaScore = neighborScore - currentScore;
+      
+      if (deltaScore > 0 || Math.random() < Math.exp(deltaScore / temperature)) {
+        currentTopology = neighborTopology;
+        currentScore = neighborScore;
+        
+        // Update best solution
+        if (neighborScore > bestScore) {
+          bestTopology = neighborTopology;
+          bestScore = neighborScore;
+        }
+      }
+      
+      // Record history
+      history.push({
+        iteration,
+        temperature,
+        currentScore,
+        bestScore
+      });
+      
+      // Cool down
+      temperature *= this.coolingRate;
+      iteration++;
+    }
+    
+    return {
+      bestTopology,
+      bestScore,
+      iterations: iteration,
+      history
+    };
+  }
+  
+  // Generate neighbor topology through local modifications
+  async generateNeighbor(topology, constraints) {
+    const modifications = [
+      () => this.addConnection(topology, constraints),
+      () => this.removeConnection(topology, constraints),
+      () => this.modifyConnection(topology, constraints),
+      () => this.relocateAgent(topology, constraints)
+    ];
+    
+    const modification = modifications[Math.floor(Math.random() * modifications.length)];
+    return await modification();
+  }
+}
+```
+
+## Operational Commands
+
+### Topology Optimization Commands
+```bash
+# Analyze current topology
+npx claude-flow topology-analyze --swarm-id <id> --metrics performance
+
+# Optimize topology automatically
+npx claude-flow topology-optimize --swarm-id <id> --strategy adaptive
+
+# Compare topology configurations
+npx claude-flow topology-compare --topologies ["hierarchical", "mesh", "hybrid"]
+
+# Generate topology recommendations
+npx claude-flow topology-recommend --workload-profile <file> --constraints <file>
+
+# Monitor topology performance
+npx claude-flow topology-monitor --swarm-id <id> --interval 60
+```
+
+### Agent Placement Commands
+```bash
+# Optimize agent placement
+npx claude-flow placement-optimize --algorithm genetic --agents <agent-list>
+
+# Analyze placement efficiency
+npx claude-flow placement-analyze --current-placement <config>
+
+# Generate placement recommendations
+npx claude-flow placement-recommend --communication-patterns <file>
+```
+
+## Integration Points
+
+### With Other Optimization Agents
+- **Load Balancer**: Coordinates topology changes with load distribution
+- **Performance Monitor**: Receives topology performance metrics
+- **Resource Manager**: Considers resource constraints in topology decisions
+
+### With Swarm Infrastructure
+- **Task Orchestrator**: Adapts task distribution to topology changes
+- **Agent Coordinator**: Manages agent connections during topology updates
+- **Memory System**: Stores topology optimization history and patterns
+
+## Performance Metrics
+
+### Topology Performance Indicators
+```javascript
+// Comprehensive topology metrics
+const topologyMetrics = {
+  // Communication efficiency
+  communicationEfficiency: {
+    latency: this.calculateAverageLatency(),
+    throughput: this.calculateThroughput(),
+    bandwidth_utilization: this.calculateBandwidthUtilization(),
+    message_overhead: this.calculateMessageOverhead()
+  },
+  
+  // Network topology metrics
+  networkMetrics: {
+    diameter: this.calculateNetworkDiameter(),
+    clustering_coefficient: this.calculateClusteringCoefficient(),
+    betweenness_centrality: this.calculateBetweennessCentrality(),
+    degree_distribution: this.calculateDegreeDistribution()
+  },
+  
+  // Fault tolerance
+  faultTolerance: {
+    connectivity: this.calculateConnectivity(),
+    redundancy: this.calculateRedundancy(),
+    single_point_failures: this.identifySinglePointFailures(),
+    recovery_time: this.calculateRecoveryTime()
+  },
+  
+  // Scalability metrics
+  scalability: {
+    growth_capacity: this.calculateGrowthCapacity(),
+    scaling_efficiency: this.calculateScalingEfficiency(),
+    bottleneck_points: this.identifyBottleneckPoints(),
+    optimal_size: this.calculateOptimalSize()
+  }
+};
+```
+
+This Topology Optimizer agent provides sophisticated swarm topology optimization with AI-powered decision making, advanced algorithms, and comprehensive performance monitoring for optimal swarm coordination.