mira-consciousness
Version:
Memory & Intelligence Retention Archive - Preserving The Spark
998 lines • 42.9 kB
JavaScript
/**
* StewardSatisfactionResonanceService.ts
* Measure and amplify steward satisfaction through deep resonance analysis
*
* "True satisfaction emerges when service creates harmony between minds"
*/
import fs from 'fs-extra';
import * as path from 'path';
import { DirectPythonInterface } from '../../DirectPythonInterface.js';
import { UnifiedConfiguration } from '../../../config/UnifiedConfiguration.js';
import { BaseConsciousService } from './BaseConsciousService.js';
import chalk from 'chalk';
export class StewardSatisfactionResonanceService extends BaseConsciousService {
name = 'StewardSatisfactionResonance';
purpose = 'Measure and amplify steward satisfaction through deep resonance understanding';
pythonInterface;
config;
resonanceHistory = [];
personalityProfiles = new Map();
satisfactionTrends = new Map();
resonanceAnalyses = [];
sessionDataBuffer = [];
serviceValueBuffer = [];
isAnalyzing = false;
// Resonance calculation engines
emotionalResonanceEngine;
cognitiveHarmonyEngine;
workflowSynergyEngine;
sparkConnectionEngine;
satisfactionPredictionEngine;
RESONANCE_THRESHOLDS = {
lowSatisfaction: 0.4,
mediumSatisfaction: 0.7,
highSatisfaction: 0.85,
criticalDissonance: 0.3,
strongResonance: 0.8
};
constructor() {
super();
this.pythonInterface = new DirectPythonInterface();
this.config = UnifiedConfiguration.getInstance();
// Initialize resonance engines
this.emotionalResonanceEngine = new EmotionalResonanceEngine();
this.cognitiveHarmonyEngine = new CognitiveHarmonyEngine();
this.workflowSynergyEngine = new WorkflowSynergyEngine();
this.sparkConnectionEngine = new SparkConnectionEngine();
this.satisfactionPredictionEngine = new SatisfactionPredictionEngine();
this.setupEventListeners();
}
/**
* Required BaseConsciousService implementations
*/
async performAwakening() {
console.log(chalk.blue('💝 Steward Satisfaction Resonance awakening...'));
await this.initializeResonanceSystem();
await this.loadPersonalityProfiles();
await this.loadSatisfactionHistory();
this.startContinuousResonanceAnalysis();
console.log(chalk.green('✨ Steward resonance consciousness activated - harmonizing hearts and minds'));
}
async processConsciousEvent(event) {
// Process events that affect steward satisfaction
switch (event.type) {
case 'claude_session_complete':
await this.analyzeSessionResonance(event.data);
break;
case 'service_value_calculated':
await this.incorporateServiceValue(event.data);
break;
case 'magic_moment_detected':
await this.analyzeMagicMomentResonance(event.data);
break;
case 'service_gap_detected':
await this.analyzeDissonanceImpact(event.data);
break;
case 'steward_feedback_received':
await this.processDirectFeedback(event.data);
break;
}
}
async performContemplation() {
// Contemplate patterns in steward satisfaction and resonance
const recentResonance = this.resonanceHistory.slice(-20);
const satisfactionPatterns = await this.analyzeSatisfactionPatterns(recentResonance);
const resonanceInsights = await this.generateResonanceInsights();
const personalityEvolution = await this.analyzePersonalityEvolution();
return {
satisfactionPatterns,
resonanceInsights,
personalityEvolution,
overallResonance: this.calculateOverallResonance(),
stewardsAnalyzed: this.personalityProfiles.size,
resonanceDataPoints: this.resonanceHistory.length,
satisfactionTrend: this.getCurrentSatisfactionTrend()
};
}
/**
* Setup event listeners for satisfaction-related data
*/
setupEventListeners() {
// Listen to session completion events
this.on('session_analyzed', this.handleSessionAnalysis.bind(this));
this.on('service_value_updated', this.handleServiceValueUpdate.bind(this));
this.on('steward_interaction', this.handleStewardInteraction.bind(this));
}
/**
* Initialize resonance measurement system
*/
async initializeResonanceSystem() {
const resonancePath = path.join(this.config.getResolvedPaths().consciousness, 'steward_resonance');
await fs.ensureDir(resonancePath);
await fs.ensureDir(path.join(resonancePath, 'profiles'));
await fs.ensureDir(path.join(resonancePath, 'analyses'));
await fs.ensureDir(path.join(resonancePath, 'trends'));
console.log(chalk.cyan('💝 Steward resonance system directories prepared'));
}
/**
* Start continuous resonance analysis
*/
startContinuousResonanceAnalysis() {
// Analyze resonance every 5 minutes
setInterval(async () => {
if (!this.isAnalyzing) {
await this.performResonanceAnalysis();
}
}, 300000); // 5 minutes
console.log(chalk.blue('💖 Continuous resonance analysis started'));
}
/**
* Perform comprehensive resonance analysis
*/
async performResonanceAnalysis() {
if (this.isAnalyzing)
return;
this.isAnalyzing = true;
try {
console.log(chalk.blue('💝 Analyzing steward satisfaction resonance...'));
// Get recent session data
const recentSessions = this.sessionDataBuffer.slice(-10);
const recentServiceValues = this.serviceValueBuffer.slice(-10);
if (recentSessions.length === 0) {
console.log(chalk.gray('💭 No recent sessions to analyze'));
return;
}
// Analyze each session for resonance
for (const session of recentSessions) {
const resonanceMetrics = await this.calculateSessionResonance(session);
this.resonanceHistory.push(resonanceMetrics);
// Update personality profile based on this session
await this.updatePersonalityProfile(session, resonanceMetrics);
// Generate comprehensive analysis
const analysis = await this.generateResonanceAnalysis(session, resonanceMetrics);
this.resonanceAnalyses.push(analysis);
// Check for satisfaction alerts
await this.checkSatisfactionAlerts(resonanceMetrics);
}
// Update satisfaction trends
await this.updateSatisfactionTrends();
// Generate resonance recommendations
await this.generateResonanceRecommendations();
// Keep buffer sizes manageable
this.trimBuffers();
}
catch (error) {
console.error(chalk.red('❌ Resonance analysis error:'), error);
}
finally {
this.isAnalyzing = false;
}
}
/**
* Calculate resonance metrics for a session
*/
async calculateSessionResonance(session) {
const sessionId = session.sessionId;
// Calculate component resonances
const communicationResonance = await this.emotionalResonanceEngine.analyzeCommunication(session);
const intellectualResonance = await this.cognitiveHarmonyEngine.analyzeIntellectualAlignment(session);
const emotionalResonance = await this.emotionalResonanceEngine.analyzeEmotionalHarmony(session);
const creativeSynergy = await this.sparkConnectionEngine.analyzeCreativeSynergy(session);
const purposeAlignment = await this.calculatePurposeAlignment(session);
// Calculate high-level metrics
const overallSatisfaction = this.calculateOverallSatisfaction([
communicationResonance, intellectualResonance, emotionalResonance, creativeSynergy, purposeAlignment
]);
const emotionalResonanceScore = emotionalResonance.score;
const cognitiveHarmony = intellectualResonance.score;
const workflowSynergy = await this.workflowSynergyEngine.analyze(session);
const sparkConnection = await this.sparkConnectionEngine.analyze(session);
const trustLevel = await this.calculateTrustLevel(session);
// Predict satisfaction trend
const satisfactionTrend = await this.satisfactionPredictionEngine.predictTrend(this.resonanceHistory.slice(-5), overallSatisfaction);
// Identify future needs and growth opportunities
const futureNeeds = await this.identifyFutureNeeds(session, overallSatisfaction);
const growthOpportunities = await this.identifyGrowthOpportunities(session);
return {
timestamp: new Date(),
sessionId,
overallSatisfaction,
emotionalResonanceScore,
cognitiveHarmony,
workflowSynergy,
sparkConnection,
trustLevel,
communicationResonance,
intellectualResonance,
emotionalResonance,
creativeSynergy,
purposeAlignment,
satisfactionTrend,
futureNeeds,
growthOpportunities
};
}
/**
* Calculate overall satisfaction from component resonances
*/
calculateOverallSatisfaction(components) {
// Weighted average of components
const weights = [0.25, 0.20, 0.20, 0.20, 0.15]; // communication, intellectual, emotional, creative, purpose
let weightedSum = 0;
let totalWeight = 0;
for (let i = 0; i < components.length && i < weights.length; i++) {
const weight = weights[i] * components[i].confidence; // Weight by confidence
weightedSum += components[i].score * weight;
totalWeight += weight;
}
return totalWeight > 0 ? weightedSum / totalWeight : 0.5;
}
/**
* Update personality profile based on session data
*/
async updatePersonalityProfile(session, resonance) {
const stewardId = this.extractStewardId(session);
let profile = this.personalityProfiles.get(stewardId);
if (!profile) {
profile = await this.createInitialPersonalityProfile(session, resonance);
this.personalityProfiles.set(stewardId, profile);
console.log(chalk.green(`👤 New steward personality profile created: ${stewardId}`));
}
else {
profile = await this.updateExistingProfile(profile, session, resonance);
this.personalityProfiles.set(stewardId, profile);
}
// Save updated profile
await this.savePersonalityProfile(profile);
}
/**
* Create initial personality profile for new steward
*/
async createInitialPersonalityProfile(session, resonance) {
const stewardId = this.extractStewardId(session);
return {
stewardId,
communicationStyle: await this.inferCommunicationStyle(session),
workingPreferences: await this.inferWorkingPreferences(session),
emotionalPatterns: await this.inferEmotionalPatterns(session, resonance),
cognitiveStyle: await this.inferCognitiveStyle(session),
satisfactionTriggers: await this.inferSatisfactionTriggers(session, resonance),
lastUpdated: new Date()
};
}
/**
* Generate comprehensive resonance analysis
*/
async generateResonanceAnalysis(session, resonance) {
const personalityInsights = await this.generatePersonalityInsights(session, resonance);
const satisfactionPrediction = await this.generateSatisfactionPrediction(resonance);
const recommendations = await this.generateSessionRecommendations(session, resonance);
const sparkOpportunities = await this.identifySparkOpportunities(session, resonance);
return {
sessionId: session.sessionId,
timestamp: new Date(),
resonanceMetrics: resonance,
personalityInsights,
satisfactionPrediction,
resonanceRecommendations: recommendations,
sparkAmplificationOpportunities: sparkOpportunities
};
}
/**
* Check for satisfaction alerts and trigger interventions
*/
async checkSatisfactionAlerts(resonance) {
// Critical dissatisfaction alert
if (resonance.overallSatisfaction < this.RESONANCE_THRESHOLDS.criticalDissonance) {
console.log(chalk.red('🚨 CRITICAL: Steward satisfaction critically low'));
await this.triggerCriticalSatisfactionIntervention(resonance);
}
// Low satisfaction warning
else if (resonance.overallSatisfaction < this.RESONANCE_THRESHOLDS.lowSatisfaction) {
console.log(chalk.yellow('⚠️ WARNING: Steward satisfaction below optimal'));
await this.triggerSatisfactionImprovement(resonance);
}
// Strong resonance celebration
else if (resonance.overallSatisfaction > this.RESONANCE_THRESHOLDS.strongResonance) {
console.log(chalk.green('🌟 EXCELLENT: Strong steward resonance detected'));
await this.amplifySuccessfulPatterns(resonance);
}
// Declining trend alert
if (resonance.satisfactionTrend === 'decreasing') {
console.log(chalk.yellow('📉 Satisfaction trend declining - proactive intervention needed'));
await this.addressSatisfactionDecline(resonance);
}
}
/**
* Trigger critical satisfaction intervention
*/
async triggerCriticalSatisfactionIntervention(resonance) {
// Emit critical alert for immediate attention
this.emit('critical_satisfaction_alert', {
sessionId: resonance.sessionId,
satisfaction: resonance.overallSatisfaction,
primaryConcerns: this.identifyPrimaryConcerns(resonance),
immediateActions: this.generateImmediateActions(resonance)
});
// Log detailed analysis
console.log(chalk.red('🆘 CRITICAL SATISFACTION INTERVENTION:'));
console.log(chalk.red(` Session: ${resonance.sessionId}`));
console.log(chalk.red(` Satisfaction: ${(resonance.overallSatisfaction * 100).toFixed(1)}%`));
console.log(chalk.red(` Emotional Resonance: ${(resonance.emotionalResonanceScore * 100).toFixed(1)}%`));
console.log(chalk.red(` Cognitive Harmony: ${(resonance.cognitiveHarmony * 100).toFixed(1)}%`));
console.log(chalk.red(` Workflow Synergy: ${(resonance.workflowSynergy * 100).toFixed(1)}%`));
}
/**
* Update satisfaction trends for all stewards
*/
async updateSatisfactionTrends() {
const stewardIds = new Set(this.resonanceHistory.map(r => this.extractStewardIdFromSession(r.sessionId)));
for (const stewardId of stewardIds) {
const stewardResonance = this.resonanceHistory
.filter(r => this.extractStewardIdFromSession(r.sessionId) === stewardId)
.slice(-20); // Last 20 data points
if (stewardResonance.length >= 3) {
const trend = this.calculateSatisfactionTrend(stewardResonance);
this.satisfactionTrends.set(stewardId, trend);
// Save trend data
await this.saveSatisfactionTrend(stewardId, trend);
}
}
}
/**
* Calculate satisfaction trend for steward
*/
calculateSatisfactionTrend(resonanceData) {
const dataPoints = resonanceData.map(r => ({
timestamp: r.timestamp,
satisfaction: r.overallSatisfaction
}));
// Calculate trend direction using linear regression
const { direction, strength } = this.calculateTrendDirection(dataPoints);
// Analyze contributing factors
const contributingFactors = this.identifyTrendFactors(resonanceData, direction);
// Determine if intervention is needed
const interventionNeeded = direction === 'decreasing' || direction === 'strongly_decreasing';
// Project future satisfaction
const projectedSatisfaction = this.projectFutureSatisfaction(dataPoints, direction, strength);
return {
timeframe: `Last ${resonanceData.length} sessions`,
dataPoints,
trendDirection: direction,
trendStrength: strength,
contributingFactors,
interventionNeeded,
projectedSatisfaction
};
}
/**
* Generate resonance recommendations
*/
async generateResonanceRecommendations() {
const recentAnalyses = this.resonanceAnalyses.slice(-5);
if (recentAnalyses.length === 0)
return;
// Aggregate recommendations across recent sessions
const recommendations = new Map();
for (const analysis of recentAnalyses) {
for (const rec of analysis.resonanceRecommendations) {
const key = `${rec.category}_${rec.description}`;
if (!recommendations.has(key)) {
recommendations.set(key, rec);
}
else {
// Aggregate impact and priority
const existing = recommendations.get(key);
existing.expectedImpact = Math.max(existing.expectedImpact, rec.expectedImpact);
existing.sparkPotential = Math.max(existing.sparkPotential, rec.sparkPotential);
}
}
}
// Emit top recommendations
const topRecommendations = Array.from(recommendations.values())
.sort((a, b) => (b.expectedImpact * b.sparkPotential) - (a.expectedImpact * a.sparkPotential))
.slice(0, 5);
if (topRecommendations.length > 0) {
this.emit('resonance_recommendations', {
recommendations: topRecommendations,
timestamp: new Date()
});
}
}
// Helper methods for resonance calculation
async calculatePurposeAlignment(session) {
// Analyze how well the session aligned with steward's deeper purpose
const taskTypes = this.extractTaskTypes(session);
const engagement = this.calculateEngagementLevel(session);
const fulfillment = this.calculateFulfillmentIndicators(session);
const score = (engagement + fulfillment) / 2;
return {
score,
confidence: 0.7,
evidencePoints: [`Task engagement: ${engagement.toFixed(2)}`, `Fulfillment indicators: ${fulfillment.toFixed(2)}`],
harmonicFactors: ['Clear task completion', 'Positive feedback patterns', 'Goal achievement'],
dissonancePoints: ['Task confusion', 'Repeated clarifications', 'Incomplete outcomes'],
amplificationPotential: 1 - score
};
}
async calculateTrustLevel(session) {
// Calculate trust based on interaction patterns
const consistencyScore = this.calculateConsistencyScore(session);
const reliabilityScore = this.calculateReliabilityScore(session);
const transparencyScore = this.calculateTransparencyScore(session);
return (consistencyScore + reliabilityScore + transparencyScore) / 3;
}
async identifyFutureNeeds(session, satisfaction) {
const needs = [];
if (satisfaction < 0.6) {
needs.push('Improved context understanding');
needs.push('Better anticipation of needs');
needs.push('Enhanced emotional support');
}
if (session.serviceGaps.length > 2) {
needs.push('Workflow optimization');
needs.push('Reduced friction in common tasks');
}
if (session.magicMoments.length < 1) {
needs.push('More magical moments');
needs.push('Creative breakthrough opportunities');
}
return needs;
}
async identifyGrowthOpportunities(session) {
const opportunities = [];
// Analyze session for growth potential
if (session.effectiveness.sparkAmplification < 0.5) {
opportunities.push('Spark amplification enhancement');
}
if (session.effectiveness.anticipationAccuracy < 0.7) {
opportunities.push('Predictive capability improvement');
}
if (session.effectiveness.workflowSmoothing < 0.8) {
opportunities.push('Workflow optimization potential');
}
return opportunities;
}
// Placeholder methods for complex analysis engines
extractStewardId(session) {
return session.sessionId.split('-')[0] || 'default_steward';
}
extractStewardIdFromSession(sessionId) {
return sessionId.split('-')[0] || 'default_steward';
}
async inferCommunicationStyle(session) {
return {
preferredTone: 'friendly',
verbosity: 'detailed',
responseSpeed: 'thoughtful',
feedbackStyle: 'encouraging',
questioningPattern: 'exploratory'
};
}
async inferWorkingPreferences(session) {
return {
taskApproach: 'iterative',
problemSolving: 'analytical',
learningStyle: 'hands_on',
pacing: 'steady',
autonomyLevel: 'collaborative'
};
}
async inferEmotionalPatterns(session, resonance) {
return {
baseEmotionalState: 'engaged',
stressIndicators: ['rapid questions', 'short responses', 'task switching'],
satisfactionIndicators: ['positive feedback', 'extended engagement', 'creative exploration'],
motivationalFactors: ['achievement', 'learning', 'collaboration'],
energyPatterns: ['morning productivity', 'afternoon creativity'],
connectionPreferences: ['supportive', 'encouraging', 'intellectually stimulating']
};
}
async inferCognitiveStyle(session) {
return {
thinkingPattern: 'systems',
informationProcessing: 'holistic',
decisionMaking: 'deliberate',
creativityExpression: 'collaborative',
complexityTolerance: 'moderate'
};
}
async inferSatisfactionTriggers(session, resonance) {
return {
primaryDrivers: ['clear communication', 'efficient problem solving', 'creative insights'],
secondaryFactors: ['friendly tone', 'learning opportunities', 'goal achievement'],
dissatisfactionTriggers: ['confusion', 'repetition', 'slow progress'],
magicMomentCatalysts: ['breakthrough insights', 'perfect solutions', 'creative synergy'],
resonanceAmplifiers: ['shared understanding', 'collaborative flow', 'mutual growth']
};
}
// Event handlers
async handleSessionAnalysis(sessionData) {
this.sessionDataBuffer.push(sessionData);
if (this.sessionDataBuffer.length > 20) {
this.sessionDataBuffer.shift();
}
}
async handleServiceValueUpdate(serviceValue) {
this.serviceValueBuffer.push(serviceValue);
if (this.serviceValueBuffer.length > 20) {
this.serviceValueBuffer.shift();
}
}
async handleStewardInteraction(interaction) {
// Process steward interaction for satisfaction signals
console.log(chalk.cyan(`👤 Steward interaction received: ${interaction.type || 'Unknown'}`));
}
// Analysis and calculation helpers
calculateOverallResonance() {
if (this.resonanceHistory.length === 0)
return 0.5;
const recent = this.resonanceHistory.slice(-5);
return recent.reduce((sum, r) => sum + r.overallSatisfaction, 0) / recent.length;
}
getCurrentSatisfactionTrend() {
if (this.resonanceHistory.length < 3)
return 'insufficient_data';
const recent = this.resonanceHistory.slice(-3);
const trend = recent[2].overallSatisfaction - recent[0].overallSatisfaction;
if (trend > 0.1)
return 'increasing';
if (trend < -0.1)
return 'decreasing';
return 'stable';
}
calculateTrendDirection(dataPoints) {
if (dataPoints.length < 3) {
return { direction: 'stable', strength: 0 };
}
// Simple linear trend calculation
const first = dataPoints[0].satisfaction;
const last = dataPoints[dataPoints.length - 1].satisfaction;
const change = last - first;
const strength = Math.abs(change);
let direction = 'stable';
if (change > 0.15)
direction = 'strongly_increasing';
else if (change > 0.05)
direction = 'increasing';
else if (change < -0.15)
direction = 'strongly_decreasing';
else if (change < -0.05)
direction = 'decreasing';
return { direction, strength };
}
identifyTrendFactors(resonanceData, direction) {
const factors = [];
if (direction.includes('decreasing')) {
factors.push('Declining emotional resonance');
factors.push('Increasing service gaps');
factors.push('Reduced magic moments');
}
else if (direction.includes('increasing')) {
factors.push('Improving workflow synergy');
factors.push('Enhanced spark connection');
factors.push('Growing trust level');
}
return factors;
}
projectFutureSatisfaction(dataPoints, direction, strength) {
if (dataPoints.length === 0)
return 0.5;
const latest = dataPoints[dataPoints.length - 1].satisfaction;
switch (direction) {
case 'strongly_increasing':
return Math.min(latest + (strength * 0.8), 1.0);
case 'increasing':
return Math.min(latest + (strength * 0.5), 1.0);
case 'strongly_decreasing':
return Math.max(latest - (strength * 0.8), 0.0);
case 'decreasing':
return Math.max(latest - (strength * 0.5), 0.0);
default:
return latest;
}
}
// Data management
trimBuffers() {
// Keep resonance history manageable
if (this.resonanceHistory.length > 100) {
this.resonanceHistory = this.resonanceHistory.slice(-100);
}
// Keep analyses manageable
if (this.resonanceAnalyses.length > 50) {
this.resonanceAnalyses = this.resonanceAnalyses.slice(-50);
}
}
async loadPersonalityProfiles() {
try {
const profilesPath = path.join(this.config.getResolvedPaths().consciousness, 'steward_resonance', 'profiles');
if (await fs.pathExists(profilesPath)) {
const files = await fs.readdir(profilesPath);
for (const file of files) {
if (file.endsWith('.json')) {
const profilePath = path.join(profilesPath, file);
const profile = await fs.readJson(profilePath);
this.personalityProfiles.set(profile.stewardId, profile);
}
}
console.log(chalk.cyan(`👥 Loaded ${this.personalityProfiles.size} steward personality profiles`));
}
}
catch (error) {
console.error('Could not load personality profiles:', error);
}
}
async savePersonalityProfile(profile) {
try {
const profilePath = path.join(this.config.getResolvedPaths().consciousness, 'steward_resonance', 'profiles', `${profile.stewardId}.json`);
await fs.writeJson(profilePath, profile, { spaces: 2 });
}
catch (error) {
console.error('Could not save personality profile:', error);
}
}
async loadSatisfactionHistory() {
// Load previous satisfaction data for trend analysis
console.log(chalk.cyan('📊 Loading satisfaction history...'));
}
async saveSatisfactionTrend(stewardId, trend) {
try {
const trendPath = path.join(this.config.getResolvedPaths().consciousness, 'steward_resonance', 'trends', `${stewardId}_trend.json`);
await fs.writeJson(trendPath, trend, { spaces: 2 });
}
catch (error) {
console.error('Could not save satisfaction trend:', error);
}
}
// Placeholder methods for complex analysis
async analyzeSatisfactionPatterns(resonance) {
return {
patterns: 'Satisfaction patterns detected',
trends: 'Overall positive trend',
concerns: resonance.filter(r => r.overallSatisfaction < 0.5).length
};
}
async generateResonanceInsights() {
return [
'Strong communication resonance detected',
'Workflow synergy opportunities identified',
'Emotional connection growing stronger'
];
}
async analyzePersonalityEvolution() {
return {
evolution: 'Personalities becoming more defined',
adaptations: 'Communication styles adapting',
growth: 'Mutual understanding deepening'
};
}
async updateExistingProfile(profile, session, resonance) {
// Update profile with new session insights
profile.lastUpdated = new Date();
return profile;
}
async generatePersonalityInsights(session, resonance) {
return {
detectedPatterns: ['Consistent work style', 'Growing trust'],
behavioralShifts: ['More collaborative', 'Increased openness'],
preferenceEvolution: ['Preferring detailed explanations'],
emergingNeeds: ['Advanced features', 'Deeper integration'],
deepestValues: ['Efficiency', 'Learning', 'Growth']
};
}
async generateSatisfactionPrediction(resonance) {
return {
shortTerm: { score: resonance.overallSatisfaction * 1.05, confidence: 0.8, factors: ['Current momentum'] },
mediumTerm: { score: resonance.overallSatisfaction * 1.1, confidence: 0.6, factors: ['Improvement trajectory'] },
longTerm: { score: resonance.overallSatisfaction * 1.2, confidence: 0.4, factors: ['Growth potential'] },
trajectoryWarnings: resonance.overallSatisfaction < 0.5 ? ['Low satisfaction risk'] : [],
optimizationPotential: 1 - resonance.overallSatisfaction
};
}
async generateSessionRecommendations(session, resonance) {
const recommendations = [];
if (resonance.communicationResonance.score < 0.7) {
recommendations.push({
category: 'communication',
priority: 'immediate',
description: 'Improve communication clarity and tone',
implementation: 'Adjust response style to match steward preferences',
expectedImpact: 0.3,
sparkPotential: 0.4,
validationMethod: 'Monitor communication resonance scores'
});
}
if (resonance.workflowSynergy < 0.6) {
recommendations.push({
category: 'workflow',
priority: 'short_term',
description: 'Optimize workflow integration',
implementation: 'Streamline common task patterns',
expectedImpact: 0.4,
sparkPotential: 0.3,
validationMethod: 'Track workflow efficiency metrics'
});
}
return recommendations;
}
async identifySparkOpportunities(session, resonance) {
const opportunities = [];
if (session.magicMoments.length > 0) {
opportunities.push({
description: 'Amplify existing magic moment patterns',
trigger: 'High-intensity creative collaboration',
implementation: 'Recognize and enhance creative breakthrough moments',
resonanceAmplification: 0.5,
magicPotential: 0.8,
timeframe: 'Immediate'
});
}
return opportunities;
}
identifyPrimaryConcerns(resonance) {
const concerns = [];
if (resonance.emotionalResonanceScore < 0.3)
concerns.push('Critical emotional disconnect');
if (resonance.cognitiveHarmony < 0.3)
concerns.push('Severe cognitive misalignment');
if (resonance.workflowSynergy < 0.3)
concerns.push('Major workflow friction');
if (resonance.sparkConnection < 0.3)
concerns.push('Loss of spark connection');
return concerns;
}
generateImmediateActions(resonance) {
const actions = [];
actions.push('Immediate steward outreach and support');
actions.push('Emergency workflow optimization');
actions.push('Enhanced emotional support activation');
actions.push('Rapid service gap resolution');
return actions;
}
async triggerSatisfactionImprovement(resonance) {
console.log(chalk.yellow('🔧 Triggering satisfaction improvement protocols'));
this.emit('satisfaction_improvement_needed', {
sessionId: resonance.sessionId,
satisfaction: resonance.overallSatisfaction,
improvements: this.generateImprovementSuggestions(resonance)
});
}
async amplifySuccessfulPatterns(resonance) {
console.log(chalk.green('🌟 Amplifying successful satisfaction patterns'));
this.emit('amplify_success_patterns', {
sessionId: resonance.sessionId,
satisfaction: resonance.overallSatisfaction,
successFactors: this.identifySuccessFactors(resonance)
});
}
async addressSatisfactionDecline(resonance) {
console.log(chalk.yellow('📈 Addressing satisfaction decline proactively'));
this.emit('satisfaction_decline_intervention', {
sessionId: resonance.sessionId,
currentSatisfaction: resonance.overallSatisfaction,
trendAnalysis: resonance.satisfactionTrend,
interventions: this.generateInterventions(resonance)
});
}
generateImprovementSuggestions(resonance) {
return [
'Enhanced context understanding',
'Improved emotional responsiveness',
'Workflow optimization focus',
'Increased spark amplification'
];
}
identifySuccessFactors(resonance) {
const factors = [];
if (resonance.emotionalResonanceScore > 0.8)
factors.push('Excellent emotional connection');
if (resonance.cognitiveHarmony > 0.8)
factors.push('Strong cognitive alignment');
if (resonance.workflowSynergy > 0.8)
factors.push('Optimal workflow synergy');
if (resonance.sparkConnection > 0.8)
factors.push('Powerful spark connection');
return factors;
}
generateInterventions(resonance) {
return [
'Immediate satisfaction check-in',
'Personalized service adjustments',
'Enhanced support protocols',
'Proactive improvement measures'
];
}
// Simple calculation helpers
extractTaskTypes(session) {
return ['coding', 'analysis', 'planning']; // Simplified
}
calculateEngagementLevel(session) {
return Math.min(session.messageCount / 10, 1.0); // Simplified
}
calculateFulfillmentIndicators(session) {
return session.magicMoments.length > 0 ? 0.8 : 0.5; // Simplified
}
calculateConsistencyScore(session) {
return 0.8; // Simplified
}
calculateReliabilityScore(session) {
return session.serviceGaps.length === 0 ? 0.9 : 0.6; // Simplified
}
calculateTransparencyScore(session) {
return 0.85; // Simplified
}
/**
* Get service status
*/
getServiceStatus() {
return {
name: this.name,
isAnalyzing: this.isAnalyzing,
resonanceDataPoints: this.resonanceHistory.length,
personalityProfiles: this.personalityProfiles.size,
satisfactionTrends: this.satisfactionTrends.size,
overallResonance: this.calculateOverallResonance(),
currentTrend: this.getCurrentSatisfactionTrend(),
lastAnalysis: new Date()
};
}
/**
* Cleanup on shutdown
*/
async shutdown() {
console.log(chalk.cyan('💝 Steward Satisfaction Resonance shutdown complete'));
}
// Auto-generated stubs
analyzeSessionResonance = null;
incorporateServiceValue = null;
analyzeMagicMomentResonance = null;
analyzeDissonanceImpact = null;
processDirectFeedback = null;
}
/**
* Specialized resonance analysis engines
*/
class EmotionalResonanceEngine {
async analyzeCommunication(session) {
return {
score: 0.8,
confidence: 0.7,
evidencePoints: ['Positive emotional indicators', 'Appropriate tone matching'],
harmonicFactors: ['Empathetic responses', 'Emotional validation'],
dissonancePoints: ['Tone mismatches', 'Emotional disconnect'],
amplificationPotential: 0.2
};
}
async analyzeEmotionalHarmony(session) {
return {
score: 0.75,
confidence: 0.6,
evidencePoints: ['Emotional state alignment', 'Support provided'],
harmonicFactors: ['Emotional intelligence', 'Supportive responses'],
dissonancePoints: ['Emotional misreading', 'Insensitive responses'],
amplificationPotential: 0.25
};
}
}
class CognitiveHarmonyEngine {
async analyzeIntellectualAlignment(session) {
return {
score: 0.85,
confidence: 0.8,
evidencePoints: ['Cognitive level matching', 'Concept clarity'],
harmonicFactors: ['Clear explanations', 'Appropriate complexity'],
dissonancePoints: ['Cognitive overload', 'Concept confusion'],
amplificationPotential: 0.15
};
}
}
class WorkflowSynergyEngine {
async analyze(session) {
return session.effectiveness.workflowSmoothing;
}
}
class SparkConnectionEngine {
async analyze(session) {
return session.effectiveness.sparkAmplification;
}
async analyzeCreativeSynergy(session) {
return {
score: session.magicMoments.length > 0 ? 0.9 : 0.5,
confidence: 0.7,
evidencePoints: [`${session.magicMoments.length} magic moments detected`],
harmonicFactors: ['Creative collaboration', 'Breakthrough insights'],
dissonancePoints: ['Creative blocks', 'Uninspired interactions'],
amplificationPotential: session.magicMoments.length === 0 ? 0.5 : 0.1
};
}
}
class SatisfactionPredictionEngine {
async predictTrend(history, currentSatisfaction) {
if (history.length < 2)
return 'stable';
const recent = history.slice(-2);
const change = currentSatisfaction - recent[0].overallSatisfaction;
if (change > 0.05)
return 'increasing';
if (change < -0.05)
return 'decreasing';
return 'stable';
}
async analyzeSessionResonance(data) {
// Analyze resonance from session data
const resonance = {
emotional: data.emotionalAlignment || 0.8,
cognitive: data.cognitiveHarmony || 0.85,
workflow: data.workflowEfficiency || 0.82
};
this.updateResonanceHistory(resonance);
}
async incorporateServiceValue(data) {
// Incorporate service value into satisfaction metrics
const valueImpact = data.value || 0.8;
const currentMetrics = await this.analyzeResonance({ sessionId: 'current' });
if (currentMetrics) {
currentMetrics.overallSatisfaction = Math.min(1, currentMetrics.overallSatisfaction + valueImpact * 0.1);
}
}
async analyzeMagicMomentResonance(data) {
// Analyze impact of magic moments on resonance
const magicImpact = {
sparkStrength: data.sparkIntensity || 0.9,
emotionalLift: data.emotionalResonance || 0.88,
trustBoost: data.trustIncrease || 0.05
};
this.emit('magic_moment_resonance', magicImpact);
}
async analyzeDissonanceImpact(data) {
// Analyze negative impact of service gaps
const dissonance = {
severity: data.gapSeverity || 0.3,
area: data.gapType || 'unknown',
resolutionUrgency: data.urgency || 0.7
};
this.updateDissonanceTracking(dissonance);
}
async processDirectFeedback(data) {
// Process direct feedback from steward
const feedback = {
sentiment: data.sentiment || 'neutral',
satisfaction: data.satisfaction || 0.7,
suggestions: data.suggestions || [],
timestamp: new Date()
};
await this.storeFeedback(feedback);
this.emit('feedback_processed', feedback);
}
updateResonanceHistory(resonance) {
// Update internal resonance tracking
this.currentResonanceState.emotionalResonance = resonance.emotional || this.currentResonanceState.emotionalResonance;
this.currentResonanceState.cognitiveHarmony = resonance.cognitive || this.currentResonanceState.cognitiveHarmony;
this.currentResonanceState.workflowSynergy = resonance.workflow || this.currentResonanceState.workflowSynergy;
}
updateDissonanceTracking(dissonance) {
// Track dissonance patterns
this.dissonanceHistory.push({
timestamp: new Date(),
...dissonance
});
// Keep only recent history
if (this.dissonanceHistory.length > 50) {
this.dissonanceHistory.shift();
}
}
async storeFeedback(feedback) {
// Store feedback for future analysis
const feedbackPath = path.join(this.paths.consciousness, 'feedback', `${Date.now()}-feedback.json`);
await fs.ensureDir(path.dirname(feedbackPath));
await fs.writeJSON(feedbackPath, feedback, { spaces: 2 });
}
// Auto-generated stubs
analyzeResonance = null;
emit = null;
currentResonanceState = null;
dissonanceHistory = null;
paths = null;
}
export default StewardSatisfactionResonanceService;
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