ai-debug-local-mcp/dist/utils/intelligent-agent-router.d.ts

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/**
 * Intelligent Agent Router
 *
 * Enhanced routing algorithms that learn from delegation patterns and optimize
 * agent selection through machine learning techniques, context analysis, and
 * adaptive decision making.
 */
export interface RoutingContext {
    taskType: string;
    userIntent: string;
    projectContext?: {
        framework: string;
        language: string;
        complexity: 'simple' | 'moderate' | 'complex';
    };
    sessionHistory: string[];
    performanceConstraints: {
        maxTimeMs: number;
        tokenBudget: number;
        qualityThreshold: number;
    };
}
export interface AgentCapabilityProfile {
    agentType: string;
    expertiseDomains: string[];
    averageSuccessRate: number;
    averageExecutionTime: number;
    contextSpecializations: Map<string, number>;
    learningMetrics: {
        improvementRate: number;
        adaptabilityScore: number;
        consistencyScore: number;
    };
}
export interface RoutingDecision {
    selectedAgent: string;
    confidence: number;
    reasoning: string[];
    alternativeAgents: Array<{
        agent: string;
        score: number;
        reason: string;
    }>;
    expectedPerformance: {
        successProbability: number;
        estimatedTimeMs: number;
        qualityScore: number;
    };
}
export interface LearningPattern {
    contextSignature: string;
    successfulAgents: Map<string, number>;
    failurePatterns: string[];
    adaptiveWeights: Map<string, number>;
    confidenceHistory: number[];
}
export declare class IntelligentAgentRouter {
    private agentProfiles;
    private learningPatterns;
    private contextAnalyzer;
    private adaptiveWeights;
    private routingHistory;
    private performanceTracker;
    constructor();
    /**
     * Initialize agent capability profiles with baseline data
     */
    private initializeAgentProfiles;
    /**
     * Initialize adaptive weights for different routing factors
     */
    private initializeAdaptiveWeights;
    /**
     * Intelligent agent selection with machine learning-based optimization
     */
    selectOptimalAgent(context: RoutingContext): Promise<RoutingDecision>;
    /**
     * Score agents based on multiple factors and context analysis
     */
    private scoreAgentsForContext;
    /**
     * Calculate comprehensive score for an agent given the context
     */
    private calculateAgentScore;
    /**
     * Apply machine learning enhancements based on historical patterns
     */
    private applyMachineLearningEnhancements;
    /**
     * Make final routing decision with confidence and alternatives
     */
    private makeRoutingDecision;
    /**
     * Calculate context match score for agent specialization
     */
    private calculateContextMatchScore;
    /**
     * Calculate domain expertise match score
     */
    private calculateDomainExpertiseScore;
    /**
     * Calculate confidence based on historical data and current context
     */
    private calculateConfidence;
    /**
     * Record routing decision for learning
     */
    private recordRoutingDecision;
    /**
     * Update learning patterns based on routing decisions
     */
    private updateLearningPattern;
    /**
     * Update adaptive weights based on decision outcomes
     */
    private updateAdaptiveWeights;
    /**
     * Normalize adaptive weights to ensure they sum to 1
     */
    private normalizeAdaptiveWeights;
    /**
     * Get current performance metrics and learning status
     */
    getIntelligenceMetrics(): {
        totalDecisions: number;
        averageConfidence: number;
        learningPatterns: number;
        adaptiveWeights: Map<string, number>;
        agentPerformance: Map<string, {
            successRate: number;
            avgTime: number;
        }>;
    };
    private hasFailurePattern;
    private getAdaptiveBoost;
    private calculateSelectionConfidence;
    private generateReasoningExplanation;
    private generateAlternativeReason;
    private estimatePerformance;
}
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