Scoring Genesys Cloud Agent Assist Skill Recommendations via WebSocket API with Node.js

What You Will Build

• A Node.js scoring engine that ingests real-time conversation events via WebSocket, calculates skill recommendation scores using agent profiles and priority matrices, and pushes validated results to Genesys Cloud.
• The implementation uses the official genesys-cloud-purecloud-platform-client-v2 SDK for REST interactions and the ws library for WebSocket event routing.
• The tutorial covers Node.js 18+ with TypeScript-compatible JSDoc annotations and production-grade error handling.

Prerequisites

• OAuth 2.0 Client Credentials flow configured in Genesys Cloud with scopes: agentassist:recommendation:write, user:read, skill:read, conversation:read
• Genesys Cloud Platform Client V2 SDK v2.145.0 or later
• Node.js 18.0+ with npm
• External dependencies: npm install genesys-cloud-purecloud-platform-client-v2 ws axios uuid
• A running WebSocket endpoint or mock event generator for testing

Authentication Setup

The Client Credentials flow grants the service account access to Agent Assist and User APIs. Token caching prevents unnecessary refresh calls and reduces 429 rate-limit exposure.

const { PlatformClient } = require('genesys-cloud-purecloud-platform-client-v2');

const OAUTH_CONFIG = {
  clientId: process.env.GENESYS_CLIENT_ID,
  clientSecret: process.env.GENESYS_CLIENT_SECRET,
  region: process.env.GENESYS_REGION || 'mypurecloud.com',
  scopes: ['agentassist:recommendation:write', 'user:read', 'skill:read', 'conversation:read']
};

let cachedToken = null;
let tokenExpiry = 0;

async function getAccessToken() {
  if (cachedToken && Date.now() < tokenExpiry) {
    return cachedToken;
  }

  const client = new PlatformClient();
  const auth = client.AuthApi();

  try {
    const response = await auth.postOAuthTokenClientCredentials({
      body: {
        grant_type: 'client_credentials',
        client_id: OAUTH_CONFIG.clientId,
        client_secret: OAUTH_CONFIG.clientSecret,
        scope: OAUTH_CONFIG.scopes.join(' ')
      }
    });

    cachedToken = response.body.access_token;
    tokenExpiry = Date.now() + (response.body.expires_in * 1000) - 30000;
    return cachedToken;
  } catch (error) {
    if (error.status === 401) {
      throw new Error('OAuth 401: Invalid client credentials. Verify clientId and clientSecret.');
    }
    if (error.status === 429) {
      const retryAfter = error.headers?.['retry-after'] || 5;
      await new Promise(resolve => setTimeout(resolve, retryAfter * 1000));
      return getAccessToken();
    }
    throw error;
  }
}

Implementation

Step 1: WebSocket Event Ingestion and Payload Construction

The WebSocket layer receives raw conversation context and agent identifiers. The engine transforms this data into a structured scoring payload containing agent profile references, skill match matrices, and priority weighting directives.

const WebSocket = require('ws');
const { v4: uuidv4 } = require('uuid');

const SCORING_CONSTRAINTS = {
  MAX_SKILLS_PER_RECOMMENDATION: 5,
  MIN_RELEVANCE_THRESHOLD: 0.65,
  RELEVANCE_DECAY_FACTOR: 0.92,
  PRIORITY_WEIGHTS: {
    COMPLIANCE: 1.5,
    CUSTOMER_SATISFACTION: 1.2,
    FIRST_CONTACT_RESOLUTION: 1.0,
    PRODUCT_KNOWLEDGE: 0.8
  }
};

function constructScoringPayload(wsMessage, agentProfile) {
  const conversationId = wsMessage.conversationId;
  const agentId = agentProfile.id;
  const skillMatrix = wsMessage.skillMatrix || [];

  const weightedSkills = skillMatrix.map(skill => {
    const baseScore = skill.matchScore || 0;
    const priorityWeight = SCORING_CONSTRAINTS.PRIORITY_WEIGHTS[skill.category] || 1.0;
    const decayedScore = baseScore * Math.pow(SCORING_CONSTRAINTS.RELEVANCE_DECAY_FACTOR, wsMessage.turnCount || 0);
    
    return {
      skillId: skill.id,
      skillName: skill.name,
      calculatedScore: Math.min(1.0, decayedScore * priorityWeight),
      category: skill.category,
      timestamp: new Date().toISOString()
    };
  }).filter(s => s.calculatedScore >= SCORING_CONSTRAINTS.MIN_RELEVANCE_THRESHOLD);

  weightedSkills.sort((a, b) => b.calculatedScore - a.calculatedScore);

  return {
    scoringId: uuidv4(),
    conversationId,
    agentId,
    agentProfileReference: {
      userId: agentId,
      name: agentProfile.name,
      queueIds: agentProfile.queueIds || [],
      roleIds: agentProfile.roleIds || []
    },
    skillMatchMatrix: weightedSkills.slice(0, SCORING_CONSTRAINTS.MAX_SKILLS_PER_RECOMMENDATION),
    priorityWeightingDirective: SCORING_CONSTRAINTS.PRIORITY_WEIGHTS,
    metadata: {
      engineVersion: '1.0.0',
      processedAt: new Date().toISOString(),
      source: 'websocket-scorer'
    }
  };
}

Step 2: Schema Validation and Constraint Enforcement

Before sending data to Genesys Cloud, the engine validates the payload against recommendation engine constraints. This prevents recommendation spam failures and ensures compliance with maximum skill count limits.

function validateScoringPayload(payload) {
  const errors = [];

  if (!payload.scoringId || typeof payload.scoringId !== 'string') {
    errors.push('Missing or invalid scoringId');
  }
  if (!payload.conversationId || typeof payload.conversationId !== 'string') {
    errors.push('Missing or invalid conversationId');
  }
  if (!payload.agentId || typeof payload.agentId !== 'string') {
    errors.push('Missing or invalid agentId');
  }
  if (!Array.isArray(payload.skillMatchMatrix)) {
    errors.push('skillMatchMatrix must be an array');
  } else {
    if (payload.skillMatchMatrix.length > SCORING_CONSTRAINTS.MAX_SKILLS_PER_RECOMMENDATION) {
      errors.push(`Exceeded maximum skill count limit of ${SCORING_CONSTRAINTS.MAX_SKILLS_PER_RECOMMENDATION}`);
    }
    payload.skillMatchMatrix.forEach((skill, index) => {
      if (typeof skill.calculatedScore !== 'number' || skill.calculatedScore < 0 || skill.calculatedScore > 1) {
        errors.push(`Invalid calculatedScore at index ${index}`);
      }
      if (!skill.skillId || !skill.category) {
        errors.push(`Missing skillId or category at index ${index}`);
      }
    });
  }

  if (errors.length > 0) {
    throw new Error(`Schema validation failed: ${errors.join('; ')}`);
  }

  return true;
}

Step 3: Atomic SEND Scoring and Cache Refresh

The scoring engine performs an atomic SEND operation to the Genesys Cloud Agent Assist REST endpoint. Format verification ensures the payload matches the Recommendation schema. Automatic cache refresh triggers update local state after successful writes.

const axios = require('axios');

async function pushRecommendationToGenesys(payload, accessToken) {
  const baseUrl = `https://api.${OAUTH_CONFIG.region}`;
  const engineId = process.env.GENESYS_ENGINE_ID;
  
  const endpoint = `${baseUrl}/api/v2/agent-assist/engines/${engineId}/recommendations`;

  const genesysPayload = {
    conversationId: payload.conversationId,
    agentId: payload.agentId,
    skills: payload.skillMatchMatrix.map(s => ({
      skillId: s.skillId,
      score: s.calculatedScore,
      metadata: {
        category: s.category,
        decayApplied: true,
        priorityWeight: SCORING_CONSTRAINTS.PRIORITY_WEIGHTS[s.category]
      }
    })),
    source: payload.metadata.source,
    scoringId: payload.scoringId
  };

  const config = {
    headers: {
      Authorization: `Bearer ${accessToken}`,
      'Content-Type': 'application/json',
      'Accept': 'application/json',
      'X-Genesys-Request-Id': uuidv4()
    }
  };

  try {
    const response = await axios.post(endpoint, genesysPayload, config);
    
    if (response.status !== 201 && response.status !== 200) {
      throw new Error(`Unexpected status: ${response.status}`);
    }

    return {
      success: true,
      recommendationId: response.data.id,
      status: response.status,
      timestamp: new Date().toISOString()
    };
  } catch (error) {
    if (error.response) {
      if (error.response.status === 429) {
        const retryAfter = error.response.headers['retry-after'] || 5;
        await new Promise(resolve => setTimeout(resolve, retryAfter * 1000));
        return pushRecommendationToGenesys(payload, accessToken);
      }
      if (error.response.status === 400) {
        throw new Error(`Bad Request: ${JSON.stringify(error.response.data)}`);
      }
      if (error.response.status === 403) {
        throw new Error('Forbidden: Missing agentassist:recommendation:write scope');
      }
    }
    throw error;
  }
}

Step 4: External Synchronization, Latency Tracking, and Audit Logging

The engine synchronizes scoring events with external training platforms via callback handlers. It tracks scoring latency, calculates skill adoption rates, and generates audit logs for workforce governance.

const fs = require('fs').promises;
const path = require('path');

const LATENCY_TRACKER = {
  totalRequests: 0,
  totalLatencyMs: 0,
  successfulPushes: 0,
  failedPushes: 0
};

function calculateAdoptionRate() {
  if (LATENCY_TRACKER.totalRequests === 0) return 0;
  return (LATENCY_TRACKER.successfulPushes / LATENCY_TRACKER.totalRequests) * 100;
}

async function writeAuditLog(event, level = 'INFO') {
  const logEntry = {
    timestamp: new Date().toISOString(),
    level,
    scoringId: event.scoringId,
    conversationId: event.conversationId,
    agentId: event.agentId,
    skillsCount: event.skillMatchMatrix?.length || 0,
    latencyMs: event.latencyMs,
    status: event.status,
    error: event.error || null
  };

  const logPath = path.join(process.env.LOG_DIR || './logs', `scoring-audit-${new Date().toISOString().split('T')[0]}.jsonl`);
  await fs.appendFile(logPath, JSON.stringify(logEntry) + '\n');
}

async function syncWithExternalTrainingPlatform(payload, result) {
  const callbackUrl = process.env.EXTERNAL_TRAINING_CALLBACK_URL;
  if (!callbackUrl) return;

  const syncPayload = {
    scoringId: payload.scoringId,
    agentId: payload.agentId,
    recommendedSkills: payload.skillMatchMatrix.map(s => s.skillId),
    scores: payload.skillMatchMatrix.map(s => s.calculatedScore),
    pushStatus: result.success ? 'SYNCED' : 'FAILED',
    timestamp: new Date().toISOString()
  };

  try {
    await axios.post(callbackUrl, syncPayload, {
      headers: { 'Content-Type': 'application/json', 'X-Source': 'genesys-scorer' },
      timeout: 5000
    });
  } catch (error) {
    console.warn(`External sync failed for scoringId ${payload.scoringId}: ${error.message}`);
  }
}

async function processScoringEvent(wsMessage, agentProfile) {
  const startTime = performance.now();
  const accessToken = await getAccessToken();

  try {
    const payload = constructScoringPayload(wsMessage, agentProfile);
    validateScoringPayload(payload);

    const result = await pushRecommendationToGenesys(payload, accessToken);
    const latencyMs = performance.now() - startTime;

    LATENCY_TRACKER.totalRequests++;
    LATENCY_TRACKER.totalLatencyMs += latencyMs;
    if (result.success) {
      LATENCY_TRACKER.successfulPushes++;
    } else {
      LATENCY_TRACKER.failedPushes++;
    }

    const auditEvent = {
      ...payload,
      status: result.success ? 'SUCCESS' : 'FAILURE',
      latencyMs,
      recommendationId: result.recommendationId
    };
    await writeAuditLog(auditEvent);
    await syncWithExternalTrainingPlatform(payload, result);

    return {
      scoringId: payload.scoringId,
      recommendationId: result.recommendationId,
      latencyMs,
      adoptionRate: calculateAdoptionRate(),
      success: result.success
    };
  } catch (error) {
    const latencyMs = performance.now() - startTime;
    LATENCY_TRACKER.totalRequests++;
    LATENCY_TRACKER.failedPushes++;

    const auditEvent = {
      scoringId: wsMessage?.scoringId || 'UNKNOWN',
      conversationId: wsMessage?.conversationId,
      agentId: agentProfile?.id,
      status: 'ERROR',
      latencyMs,
      error: error.message
    };
    await writeAuditLog(auditEvent, 'ERROR');
    throw error;
  }
}

Complete Working Example

The following script combines authentication, WebSocket ingestion, scoring validation, REST push, and audit synchronization into a single runnable module. Replace environment variables with valid credentials before execution.

require('dotenv').config();
const { PlatformClient } = require('genesys-cloud-purecloud-platform-client-v2');
const WebSocket = require('ws');
const axios = require('axios');
const { v4: uuidv4 } = require('uuid');
const fs = require('fs').promises;
const path = require('path');

// Configuration
const OAUTH_CONFIG = {
  clientId: process.env.GENESYS_CLIENT_ID,
  clientSecret: process.env.GENESYS_CLIENT_SECRET,
  region: process.env.GENESYS_REGION || 'mypurecloud.com',
  scopes: ['agentassist:recommendation:write', 'user:read', 'skill:read', 'conversation:read']
};

const SCORING_CONSTRAINTS = {
  MAX_SKILLS_PER_RECOMMENDATION: 5,
  MIN_RELEVANCE_THRESHOLD: 0.65,
  RELEVANCE_DECAY_FACTOR: 0.92,
  PRIORITY_WEIGHTS: {
    COMPLIANCE: 1.5,
    CUSTOMER_SATISFACTION: 1.2,
    FIRST_CONTACT_RESOLUTION: 1.0,
    PRODUCT_KNOWLEDGE: 0.8
  }
};

const LATENCY_TRACKER = { totalRequests: 0, totalLatencyMs: 0, successfulPushes: 0, failedPushes: 0 };

let cachedToken = null;
let tokenExpiry = 0;

async function getAccessToken() {
  if (cachedToken && Date.now() < tokenExpiry) return cachedToken;
  const client = new PlatformClient();
  const auth = client.AuthApi();
  try {
    const response = await auth.postOAuthTokenClientCredentials({
      body: { grant_type: 'client_credentials', client_id: OAUTH_CONFIG.clientId, client_secret: OAUTH_CONFIG.clientSecret, scope: OAUTH_CONFIG.scopes.join(' ') }
    });
    cachedToken = response.body.access_token;
    tokenExpiry = Date.now() + (response.body.expires_in * 1000) - 30000;
    return cachedToken;
  } catch (error) {
    if (error.status === 401) throw new Error('OAuth 401: Invalid client credentials');
    if (error.status === 429) {
      const retryAfter = error.headers?.['retry-after'] || 5;
      await new Promise(resolve => setTimeout(resolve, retryAfter * 1000));
      return getAccessToken();
    }
    throw error;
  }
}

function constructScoringPayload(wsMessage, agentProfile) {
  const skillMatrix = wsMessage.skillMatrix || [];
  const weightedSkills = skillMatrix.map(skill => {
    const baseScore = skill.matchScore || 0;
    const priorityWeight = SCORING_CONSTRAINTS.PRIORITY_WEIGHTS[skill.category] || 1.0;
    const decayedScore = baseScore * Math.pow(SCORING_CONSTRAINTS.RELEVANCE_DECAY_FACTOR, wsMessage.turnCount || 0);
    return { skillId: skill.id, skillName: skill.name, calculatedScore: Math.min(1.0, decayedScore * priorityWeight), category: skill.category, timestamp: new Date().toISOString() };
  }).filter(s => s.calculatedScore >= SCORING_CONSTRAINTS.MIN_RELEVANCE_THRESHOLD);
  weightedSkills.sort((a, b) => b.calculatedScore - a.calculatedScore);
  return {
    scoringId: uuidv4(), conversationId: wsMessage.conversationId, agentId: agentProfile.id,
    agentProfileReference: { userId: agentProfile.id, name: agentProfile.name, queueIds: agentProfile.queueIds || [], roleIds: agentProfile.roleIds || [] },
    skillMatchMatrix: weightedSkills.slice(0, SCORING_CONSTRAINTS.MAX_SKILLS_PER_RECOMMENDATION),
    priorityWeightingDirective: SCORING_CONSTRAINTS.PRIORITY_WEIGHTS,
    metadata: { engineVersion: '1.0.0', processedAt: new Date().toISOString(), source: 'websocket-scorer' }
  };
}

function validateScoringPayload(payload) {
  const errors = [];
  if (!payload.scoringId || typeof payload.scoringId !== 'string') errors.push('Invalid scoringId');
  if (!payload.conversationId || typeof payload.conversationId !== 'string') errors.push('Invalid conversationId');
  if (!payload.agentId || typeof payload.agentId !== 'string') errors.push('Invalid agentId');
  if (!Array.isArray(payload.skillMatchMatrix)) errors.push('skillMatchMatrix must be array');
  else {
    if (payload.skillMatchMatrix.length > SCORING_CONSTRAINTS.MAX_SKILLS_PER_RECOMMENDATION) errors.push('Exceeded max skill count');
    payload.skillMatchMatrix.forEach((s, i) => {
      if (typeof s.calculatedScore !== 'number' || s.calculatedScore < 0 || s.calculatedScore > 1) errors.push(`Invalid score at ${i}`);
      if (!s.skillId || !s.category) errors.push(`Missing fields at ${i}`);
    });
  }
  if (errors.length > 0) throw new Error(`Validation failed: ${errors.join('; ')}`);
  return true;
}

async function pushRecommendationToGenesys(payload, accessToken) {
  const baseUrl = `https://api.${OAUTH_CONFIG.region}`;
  const engineId = process.env.GENESYS_ENGINE_ID;
  const endpoint = `${baseUrl}/api/v2/agent-assist/engines/${engineId}/recommendations`;
  const genesysPayload = {
    conversationId: payload.conversationId, agentId: payload.agentId,
    skills: payload.skillMatchMatrix.map(s => ({ skillId: s.skillId, score: s.calculatedScore, metadata: { category: s.category, decayApplied: true, priorityWeight: SCORING_CONSTRAINTS.PRIORITY_WEIGHTS[s.category] } })),
    source: payload.metadata.source, scoringId: payload.scoringId
  };
  try {
    const response = await axios.post(endpoint, genesysPayload, {
      headers: { Authorization: `Bearer ${accessToken}`, 'Content-Type': 'application/json', 'Accept': 'application/json', 'X-Genesys-Request-Id': uuidv4() }
    });
    return { success: true, recommendationId: response.data.id, status: response.status, timestamp: new Date().toISOString() };
  } catch (error) {
    if (error.response) {
      if (error.response.status === 429) {
        await new Promise(resolve => setTimeout(resolve, (error.response.headers['retry-after'] || 5) * 1000));
        return pushRecommendationToGenesys(payload, accessToken);
      }
      if (error.response.status === 400) throw new Error(`Bad Request: ${JSON.stringify(error.response.data)}`);
      if (error.response.status === 403) throw new Error('Forbidden: Missing agentassist:recommendation:write scope');
    }
    throw error;
  }
}

async function writeAuditLog(event, level = 'INFO') {
  const logEntry = { timestamp: new Date().toISOString(), level, scoringId: event.scoringId, conversationId: event.conversationId, agentId: event.agentId, skillsCount: event.skillMatchMatrix?.length || 0, latencyMs: event.latencyMs, status: event.status, error: event.error || null };
  const logPath = path.join(process.env.LOG_DIR || './logs', `scoring-audit-${new Date().toISOString().split('T')[0]}.jsonl`);
  await fs.appendFile(logPath, JSON.stringify(logEntry) + '\n');
}

async function syncWithExternalTrainingPlatform(payload, result) {
  const callbackUrl = process.env.EXTERNAL_TRAINING_CALLBACK_URL;
  if (!callbackUrl) return;
  try {
    await axios.post(callbackUrl, { scoringId: payload.scoringId, agentId: payload.agentId, recommendedSkills: payload.skillMatchMatrix.map(s => s.skillId), scores: payload.skillMatchMatrix.map(s => s.calculatedScore), pushStatus: result.success ? 'SYNCED' : 'FAILED', timestamp: new Date().toISOString() }, { headers: { 'Content-Type': 'application/json', 'X-Source': 'genesys-scorer' }, timeout: 5000 });
  } catch (error) {
    console.warn(`External sync failed for ${payload.scoringId}: ${error.message}`);
  }
}

async function processScoringEvent(wsMessage, agentProfile) {
  const startTime = performance.now();
  const accessToken = await getAccessToken();
  try {
    const payload = constructScoringPayload(wsMessage, agentProfile);
    validateScoringPayload(payload);
    const result = await pushRecommendationToGenesys(payload, accessToken);
    const latencyMs = performance.now() - startTime;
    LATENCY_TRACKER.totalRequests++;
    LATENCY_TRACKER.totalLatencyMs += latencyMs;
    LATENCY_TRACKER.successfulPushes += result.success ? 1 : 0;
    if (!result.success) LATENCY_TRACKER.failedPushes++;
    await writeAuditLog({ ...payload, status: result.success ? 'SUCCESS' : 'FAILURE', latencyMs, recommendationId: result.recommendationId });
    await syncWithExternalTrainingPlatform(payload, result);
    return { scoringId: payload.scoringId, recommendationId: result.recommendationId, latencyMs, adoptionRate: LATENCY_TRACKER.totalRequests > 0 ? (LATENCY_TRACKER.successfulPushes / LATENCY_TRACKER.totalRequests) * 100 : 0, success: result.success };
  } catch (error) {
    const latencyMs = performance.now() - startTime;
    LATENCY_TRACKER.totalRequests++;
    LATENCY_TRACKER.failedPushes++;
    await writeAuditLog({ scoringId: wsMessage?.scoringId || 'UNKNOWN', conversationId: wsMessage?.conversationId, agentId: agentProfile?.id, status: 'ERROR', latencyMs, error: error.message }, 'ERROR');
    throw error;
  }
}

// WebSocket Server Setup
const wss = new WebSocket.Server({ port: process.env.WS_PORT || 8080 });
wss.on('connection', (ws) => {
  console.log('WebSocket client connected');
  ws.on('message', async (data) => {
    try {
      const wsMessage = JSON.parse(data);
      const agentProfile = { id: wsMessage.agentId, name: 'Test Agent', queueIds: ['q1'], roleIds: ['r1'] };
      const result = await processScoringEvent(wsMessage, agentProfile);
      ws.send(JSON.stringify({ status: 'processed', result }));
    } catch (error) {
      ws.send(JSON.stringify({ status: 'error', message: error.message }));
    }
  });
});
console.log(`WebSocket scoring engine listening on port ${wss.options.port}`);

Common Errors & Debugging

Error: 401 Unauthorized

• What causes it: Expired access token, incorrect client credentials, or missing OAuth scopes.
• How to fix it: Verify GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET. Ensure the agentassist:recommendation:write scope is attached to the OAuth client in the Genesys Cloud admin console. The token caching logic automatically refreshes before expiry.
• Code showing the fix: The getAccessToken function checks tokenExpiry and throws a descriptive error on 401 responses.

Error: 429 Too Many Requests

• What causes it: Exceeding Genesys Cloud rate limits on the Agent Assist recommendation endpoint or OAuth token endpoint.
• How to fix it: Implement exponential backoff. The pushRecommendationToGenesys and getAccessToken functions parse the Retry-After header and delay subsequent requests automatically.
• Code showing the fix: Retry logic is embedded in both authentication and REST push functions with header parsing.

Error: Schema Validation Failed

• What causes it: Payload exceeds MAX_SKILLS_PER_RECOMMENDATION, contains invalid score ranges, or missing required fields.
• How to fix it: Review validateScoringPayload output. Ensure skillMatchMatrix contains only skills with calculatedScore between 0 and 1. Trim arrays before validation.
• Code showing the fix: The constructScoringPayload function applies .slice(0, SCORING_CONSTRAINTS.MAX_SKILLS_PER_RECOMMENDATION) and filters by MIN_RELEVANCE_THRESHOLD before validation.

Error: WebSocket Disconnect During Scoring

• What causes it: Network interruption or client timeout during long-running scoring calculations.
• How to fix it: Implement heartbeat pings and reconnection logic. The scoring pipeline processes messages synchronously before responding, preventing mid-calculation disconnects. Add ws.ping() intervals in production deployments.
• Code showing the fix: The processScoringEvent function completes all I/O before sending the response payload, ensuring atomic message handling.

Official References

• Genesys Cloud Agent Assist REST API Documentation
• Genesys Cloud Platform Client V2 Node.js SDK
• OAuth 2.0 Client Credentials Flow
• WebSocket Server Library (ws)