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@versatil/sdlc-framework

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🚀 AI-Native SDLC framework with 11-MCP ecosystem, RAG memory, OPERA orchestration, and 6 specialized agents achieving ZERO CONTEXT LOSS. Features complete CI/CD pipeline with 7 GitHub workflows (MCP testing, security scanning, performance benchmarking),

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/** * Cross-Agent Learning System * Enables agents to learn from each other's successes and failures */ import { EnhancedVectorMemoryStore } from './enhanced-vector-memory-store.js'; export interface AgentInteraction { sourceAgent: string; targetAgent: string; context: string; outcome: 'success' | 'failure' | 'initiated'; timestamp: number; metadata?: any; } export interface LearningInsight { pattern: string; confidence: number; applicability: string[]; description: string; } export declare class CrossAgentLearning { private vectorStore; private interactionHistory; constructor(vectorStore: EnhancedVectorMemoryStore); /** * Learn from agent interaction */ learnFromAgentInteraction(sourceAgent: string, targetAgent: string, context: string, outcome: 'success' | 'failure' | 'initiated', metadata?: any): Promise<void>; /** * Store successful pattern for future use */ private storeSuccessPattern; /** * Query for similar successful interactions */ querySimilarSuccesses(sourceAgent: string, targetAgent: string, limit?: number): Promise<any[]>; /** * Get recommended next agent based on history */ getRecommendedNextAgent(currentAgent: string, context: string): Promise<{ agentId: string; confidence: number; } | null>; /** * Extract learning insights from interaction history */ extractLearningInsights(): Promise<LearningInsight[]>; /** * Get interaction statistics */ getStatistics(): any; /** * Get statistics by agent pair */ private getAgentPairStatistics; }