@spaik/mcp-server-roi/dist/services/conversational-bridge.d.ts

MCP server for AI ROI prediction and tracking with Monte Carlo simulations

import { z } from 'zod';
/**
 * Conversational Bridge Service
 *
 * Transforms structured responses into natural, conversational language
 * that feels like talking to a knowledgeable advisor rather than a system.
 */
export declare const ConversationStyleSchema: z.ZodEnum<["professional", "friendly", "executive", "technical", "educational"]>;
export declare const ConversationalResponseSchema: z.ZodObject<{
    message: z.ZodString;
    tone: z.ZodObject<{
        style: z.ZodEnum<["professional", "friendly", "executive", "technical", "educational"]>;
        formality: z.ZodNumber;
        enthusiasm: z.ZodNumber;
        confidence: z.ZodNumber;
    }, "strip", z.ZodTypeAny, {
        confidence: number;
        style: "technical" | "executive" | "professional" | "friendly" | "educational";
        formality: number;
        enthusiasm: number;
    }, {
        confidence: number;
        style: "technical" | "executive" | "professional" | "friendly" | "educational";
        formality: number;
        enthusiasm: number;
    }>;
    elements: z.ZodObject<{
        greeting: z.ZodOptional<z.ZodString>;
        context_acknowledgment: z.ZodOptional<z.ZodString>;
        main_content: z.ZodArray<z.ZodString, "many">;
        clarifications: z.ZodOptional<z.ZodArray<z.ZodString, "many">>;
        closing: z.ZodOptional<z.ZodString>;
    }, "strip", z.ZodTypeAny, {
        main_content: string[];
        greeting?: string | undefined;
        context_acknowledgment?: string | undefined;
        clarifications?: string[] | undefined;
        closing?: string | undefined;
    }, {
        main_content: string[];
        greeting?: string | undefined;
        context_acknowledgment?: string | undefined;
        clarifications?: string[] | undefined;
        closing?: string | undefined;
    }>;
    interactive: z.ZodObject<{
        follow_up_questions: z.ZodOptional<z.ZodArray<z.ZodString, "many">>;
        suggested_topics: z.ZodOptional<z.ZodArray<z.ZodString, "many">>;
        clarification_prompts: z.ZodOptional<z.ZodArray<z.ZodString, "many">>;
    }, "strip", z.ZodTypeAny, {
        follow_up_questions?: string[] | undefined;
        suggested_topics?: string[] | undefined;
        clarification_prompts?: string[] | undefined;
    }, {
        follow_up_questions?: string[] | undefined;
        suggested_topics?: string[] | undefined;
        clarification_prompts?: string[] | undefined;
    }>;
    metadata: z.ZodObject<{
        word_count: z.ZodNumber;
        reading_time_seconds: z.ZodNumber;
        complexity_level: z.ZodEnum<["simple", "moderate", "complex"]>;
        jargon_count: z.ZodNumber;
    }, "strip", z.ZodTypeAny, {
        word_count: number;
        reading_time_seconds: number;
        complexity_level: "moderate" | "simple" | "complex";
        jargon_count: number;
    }, {
        word_count: number;
        reading_time_seconds: number;
        complexity_level: "moderate" | "simple" | "complex";
        jargon_count: number;
    }>;
}, "strip", z.ZodTypeAny, {
    message: string;
    metadata: {
        word_count: number;
        reading_time_seconds: number;
        complexity_level: "moderate" | "simple" | "complex";
        jargon_count: number;
    };
    tone: {
        confidence: number;
        style: "technical" | "executive" | "professional" | "friendly" | "educational";
        formality: number;
        enthusiasm: number;
    };
    elements: {
        main_content: string[];
        greeting?: string | undefined;
        context_acknowledgment?: string | undefined;
        clarifications?: string[] | undefined;
        closing?: string | undefined;
    };
    interactive: {
        follow_up_questions?: string[] | undefined;
        suggested_topics?: string[] | undefined;
        clarification_prompts?: string[] | undefined;
    };
}, {
    message: string;
    metadata: {
        word_count: number;
        reading_time_seconds: number;
        complexity_level: "moderate" | "simple" | "complex";
        jargon_count: number;
    };
    tone: {
        confidence: number;
        style: "technical" | "executive" | "professional" | "friendly" | "educational";
        formality: number;
        enthusiasm: number;
    };
    elements: {
        main_content: string[];
        greeting?: string | undefined;
        context_acknowledgment?: string | undefined;
        clarifications?: string[] | undefined;
        closing?: string | undefined;
    };
    interactive: {
        follow_up_questions?: string[] | undefined;
        suggested_topics?: string[] | undefined;
        clarification_prompts?: string[] | undefined;
    };
}>;
export type ConversationStyle = z.infer<typeof ConversationStyleSchema>;
export type ConversationalResponse = z.infer<typeof ConversationalResponseSchema>;
export declare class ConversationalBridge {
    private logger;
    private readonly CONVERSATION_TEMPLATES;
    /**
     * Transform response into conversational format
     */
    transformToConversation(response: any, style?: ConversationStyle, context?: {
        user_expertise?: 'beginner' | 'intermediate' | 'expert';
        previous_interactions?: number;
        urgency?: 'low' | 'medium' | 'high';
    }): Promise<ConversationalResponse>;
    /**
     * Generate natural language explanations
     */
    explainInNaturalLanguage(concept: string, data: any, targetAudience?: 'executive' | 'technical' | 'general'): Promise<string>;
    /**
     * Create conversational narratives from data
     */
    createNarrative(data: any, narrativeType: 'success_story' | 'cautionary_tale' | 'comparison' | 'journey'): Promise<{
        narrative: string;
        key_points: string[];
        emotional_arc: string[];
    }>;
    /**
     * Handle conversational context and memory
     */
    maintainConversationFlow(currentResponse: any, conversationHistory: Array<{
        role: 'user' | 'assistant';
        content: string;
        timestamp: string;
    }>): Promise<{
        contextual_response: string;
        references_to_past: string[];
        conversation_continuity: number;
    }>;
    /**
     * Adapt language complexity based on audience
     */
    adaptComplexity(content: string, targetComplexity: 'simple' | 'moderate' | 'complex', preserveAccuracy?: boolean): Promise<{
        adapted_content: string;
        complexity_changes: string[];
        accuracy_preserved: boolean;
    }>;
    private determineTone;
    private buildConversationElements;
    private generateInteractiveElements;
    private composeMessage;
    private calculateMetadata;
    private selectGreeting;
    private selectClosing;
    private buildMainContent;
    private phraseKeyInsight;
    private phraseRisk;
    private needsClarification;
    private generateClarifications;
    private generateFollowUpQuestions;
    private suggestRelatedTopics;
    private isComplex;
    private countJargon;
    private assessComplexity;
    private explainROI;
    private explainPaybackPeriod;
    private explainRiskFactors;
    private explainTimeline;
    private explainCosts;
    private explainGeneric;
    private createSuccessStory;
    private createCautionaryTale;
    private createComparisonNarrative;
    private createJourneyNarrative;
    private createGenericNarrative;
    private analyzeConversationContext;
    private buildContextualResponse;
    private findPastReferences;
    private calculateContinuity;
    private simplifyJargon;
    private shortenSentences;
    private addSimpleAnalogies;
    private addTechnicalDetails;
    private usePreciseTerminology;
    private verifyAccuracy;
}
export declare const conversationalBridge: ConversationalBridge;
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