Auditing Genesys Cloud Agent Assist Insight Sources with TypeScript

What You Will Build

A TypeScript module that iterates through Genesys Cloud Agent Assist insights, validates source URLs against schema constraints and maximum source count limits, verifies content freshness and integrity via SHA-256 hash comparison, tracks latency and success metrics, and emits structured audit logs for automated governance.

This tutorial uses the Genesys Cloud Agent Assist REST API (/api/v2/agentassist/insights) and standard Node.js cryptographic utilities.

The programming language covered is TypeScript (Node.js 18+).

Prerequisites

• OAuth 2.0 Client ID and Client Secret with agentassist:insight:read scope
• Node.js 18 or later with TypeScript 5+
• External dependencies: axios, @types/node, p-limit (for concurrency control)
• Install dependencies via npm install axios p-limit && npm install -D @types/node typescript
• A Genesys Cloud environment with at least one configured Agent Assist insight containing external source URLs

Authentication Setup

Genesys Cloud requires OAuth 2.0 client credentials flow for API access. The following manager handles token acquisition, caching, and automatic refresh before expiration. It attaches the bearer token to every API request via an Axios interceptor.

import axios, { AxiosInstance, InternalAxiosRequestConfig } from 'axios';

const OAUTH_URL = 'https://api.mypurecloud.com/oauth/token';
const API_BASE = 'https://api.mypurecloud.com';
const REQUIRED_SCOPE = 'agentassist:insight:read';

interface TokenResponse {
  access_token: string;
  expires_in: number;
  token_type: string;
}

export class AuthManager {
  private token: string | null = null;
  private expiryTimestamp: number = 0;
  private apiClient: AxiosInstance;

  constructor(private clientId: string, private clientSecret: string) {
    this.apiClient = axios.create({
      baseURL: API_BASE,
      timeout: 12000,
      headers: { 'Content-Type': 'application/json' }
    });

    this.apiClient.interceptors.request.use(async (config: InternalAxiosRequestConfig) => {
      const token = await this.getAccessToken();
      config.headers.Authorization = `Bearer ${token}`;
      return config;
    });
  }

  async getAccessToken(): Promise<string> {
    if (this.token && Date.now() < this.expiryTimestamp) {
      return this.token;
    }

    const credentials = Buffer.from(`${this.clientId}:${this.clientSecret}`).toString('base64');
    const formData = `grant_type=client_credentials&scope=${REQUIRED_SCOPE}`;

    const response = await axios.post<TokenResponse>(OAUTH_URL, formData, {
      headers: {
        Authorization: `Basic ${credentials}`,
        'Content-Type': 'application/x-www-form-urlencoded'
      }
    });

    this.token = response.data.access_token;
    // Subtract 30 seconds to prevent edge-case expiration during request flight
    this.expiryTimestamp = Date.now() + ((response.data.expires_in - 30) * 1000);
    return this.token;
  }

  getClient(): AxiosInstance {
    return this.apiClient;
  }
}

Implementation

Step 1: Fetch Insights and Validate Schema Constraints

Genesys Cloud returns insights in paginated responses. This step retrieves all insights, expands the sources array, and validates each insight against platform constraints. The platform enforces a maximum of 10 sources per insight and restricts supported formats to HTML, PDF, DOCX, TXT, and MD. The validation pipeline rejects HTTP URLs and unsupported MIME types before network verification begins.

import { AxiosInstance } from 'axios';

interface InsightSource {
  url: string;
  format: string;
  id?: string;
}

interface Insight {
  id: string;
  name: string;
  sources: InsightSource[];
  updatedAt: string;
}

const MAX_SOURCES_PER_INSIGHT = 10;
const SUPPORTED_FORMATS = ['HTML', 'PDF', 'DOCX', 'TXT', 'MD'];

export async function fetchAllInsights(api: AxiosInstance): Promise<Insight[]> {
  const insights: Insight[] = [];
  let uri = '/api/v2/agentassist/insights?pageSize=100';

  while (uri) {
    const response = await api.get(uri);
    insights.push(...response.data.entities);
    uri = response.data.nextPageUri || null;
  }
  return insights;
}

export function validateInsightSchema(insight: Insight): string[] {
  const errors: string[] = [];

  if (insight.sources.length > MAX_SOURCES_PER_INSIGHT) {
    errors.push(`Insight ${insight.id} exceeds maximum source count limit (${MAX_SOURCES_PER_INSIGHT})`);
  }

  insight.sources.forEach((source, index) => {
    if (!SUPPORTED_FORMATS.includes(source.format.toUpperCase())) {
      errors.push(`Insight ${insight.id} source ${index} uses unsupported format: ${source.format}`);
    }
    if (!source.url.startsWith('https://')) {
      errors.push(`Insight ${insight.id} source ${index} URL must use HTTPS`);
    }
  });

  return errors;
}

Step 2: Source Verification via Atomic GET Operations

Each source URL undergoes atomic verification. The pipeline performs a direct HTTP GET request, measures latency, validates the Content-Type header against the expected format, computes a SHA-256 hash for integrity tracking, and evaluates staleness based on the Last-Modified header. Sources older than 30 days trigger a staleness directive without marking them as failed.

import axios from 'axios';
import { createHash } from 'crypto';

export interface SourceAuditResult {
  insightId: string;
  sourceUrl: string;
  status: 'PASS' | 'FAIL' | 'STALE';
  latencyMs: number;
  contentType: string;
  contentHash: string;
  lastModified: string | null;
  errorMessage?: string;
}

export async function verifySourceUrl(
  insightId: string,
  url: string,
  expectedFormat: string
): Promise<SourceAuditResult> {
  const startTimestamp = Date.now();
  const result: SourceAuditResult = {
    insightId,
    sourceUrl: url,
    status: 'PASS',
    latencyMs: 0,
    contentType: '',
    contentHash: '',
    lastModified: null
  };

  try {
    const response = await axios.get(url, {
      responseType: 'arraybuffer',
      timeout: 15000,
      validateStatus: (status) => status < 500
    });

    result.latencyMs = Date.now() - startTimestamp;
    result.contentType = response.headers['content-type'] || '';
    result.lastModified = response.headers['last-modified'] || null;

    // Format verification against expected directive
    const formatNormalized = expectedFormat.toLowerCase();
    const formatMatch = result.contentType.includes(formatNormalized) ||
      (formatNormalized === 'html' && result.contentType.includes('text/html'));

    if (!formatMatch) {
      result.status = 'FAIL';
      result.errorMessage = `Content-Type mismatch: expected ${expectedFormat}, received ${result.contentType}`;
      return result;
    }

    // Content hash verification pipeline
    result.contentHash = createHash('sha256').update(response.data).digest('hex');

    // Automatic staleness detection trigger
    if (result.lastModified) {
      const lastModifiedDate = new Date(result.lastModified);
      const stalenessThreshold = new Date(Date.now() - 30 * 24 * 60 * 60 * 1000);
      if (lastModifiedDate < stalenessThreshold) {
        result.status = 'STALE';
        result.errorMessage = 'Source exceeds 30-day freshness timestamp directive';
      }
    }
  } catch (error: any) {
    result.latencyMs = Date.now() - startTimestamp;
    result.status = 'FAIL';
    result.errorMessage = error.response?.status
      ? `HTTP ${error.response.status}: ${error.response.statusText}`
      : error.message;
  }

  return result;
}

Step 3: Audit Metrics, Callback Synchronization, and Log Generation

The auditing process aggregates latency measurements and success rates. It exposes a callback interface for external content crawlers to synchronize audit events. The pipeline generates structured JSON audit logs for source governance and compliance tracking.

import fs from 'fs';
import path from 'path';

export interface AuditMetrics {
  totalSources: number;
  passed: number;
  failed: number;
  stale: number;
  avgLatencyMs: number;
  totalLatencyMs: number;
}

export interface AuditReport {
  timestamp: string;
  insightId: string;
  sourceUrl: string;
  status: string;
  latencyMs: number;
  contentHash: string;
  errorMessage?: string;
}

export type AuditCallback = (report: AuditReport) => Promise<void> | void;

export class AuditMetricsTracker {
  private metrics: AuditMetrics = {
    totalSources: 0,
    passed: 0,
    failed: 0,
    stale: 0,
    avgLatencyMs: 0,
    totalLatencyMs: 0
  };

  record(result: SourceAuditResult): void {
    this.metrics.totalSources++;
    this.metrics.totalLatencyMs += result.latencyMs;
    this.metrics.avgLatencyMs = this.metrics.totalLatencyMs / this.metrics.totalSources;

    if (result.status === 'PASS') this.metrics.passed++;
    else if (result.status === 'FAIL') this.metrics.failed++;
    else if (result.status === 'STALE') this.metrics.stale++;
  }

  getMetrics(): AuditMetrics {
    return { ...this.metrics };
  }
}

export class AuditLogger {
  private logFile: string;

  constructor(logDirectory: string = './audit-logs') {
    if (!fs.existsSync(logDirectory)) fs.mkdirSync(logDirectory, { recursive: true });
    this.logFile = path.join(logDirectory, `agentassist-audit-${new Date().toISOString().split('T')[0]}.jsonl`);
  }

  write(report: AuditReport): void {
    const logEntry = JSON.stringify({
      ...report,
      recordedAt: new Date().toISOString()
    });
    fs.appendFileSync(this.logFile, logEntry + '\n');
  }
}

Complete Working Example

The following module combines authentication, schema validation, source verification, metrics tracking, and callback synchronization into a single executable auditor class. It implements exponential backoff for 429 rate limits, concurrent source verification with p-limit, and exposes a programmatic interface for automated Agent Assist management.

import axios, { AxiosInstance, AxiosResponse } from 'axios';
import pLimit from 'p-limit';
import { AuthManager } from './auth';
import { fetchAllInsights, validateInsightSchema, Insight } from './schema';
import { verifySourceUrl, SourceAuditResult } from './verification';
import { AuditMetricsTracker, AuditLogger, AuditReport, AuditCallback } from './metrics';

const RETRY_BASE_DELAY = 1000;
const MAX_RETRIES = 3;

async function requestWithRetry(api: AxiosInstance, method: 'get' | 'post', url: string, data?: any): Promise<AxiosResponse> {
  let attempt = 0;
  while (true) {
    try {
      return await api.request({ method, url, data });
    } catch (error: any) {
      if (error.response?.status === 429 && attempt < MAX_RETRIES) {
        const retryAfter = error.response.headers['retry-after']
          ? parseInt(error.response.headers['retry-after'], 10) * 1000
          : RETRY_BASE_DELAY * Math.pow(2, attempt);
        console.log(`Rate limited. Retrying in ${retryAfter}ms...`);
        await new Promise(resolve => setTimeout(resolve, retryAfter));
        attempt++;
      } else {
        throw error;
      }
    }
  }
}

export class AgentAssistSourceAuditor {
  private api: AxiosInstance;
  private metrics: AuditMetricsTracker;
  private logger: AuditLogger;
  private callback?: AuditCallback;

  constructor(clientId: string, clientSecret: string, callback?: AuditCallback) {
    const auth = new AuthManager(clientId, clientSecret);
    this.api = auth.getClient();
    this.metrics = new AuditMetricsTracker();
    this.logger = new AuditLogger();
    this.callback = callback;
  }

  async runAudit(): Promise<AuditReport[]> {
    console.log('Fetching Agent Assist insights...');
    const insights = await requestWithRetry(this.api, 'get', '/api/v2/agentassist/insights?pageSize=100&expand=sources');
    const insightList: Insight[] = insights.data.entities;
    const reports: AuditReport[] = [];

    const concurrency = pLimit(5);

    const auditTasks = insightList.flatMap(insight => {
      const schemaErrors = validateInsightSchema(insight);
      if (schemaErrors.length > 0) {
        console.warn(`Schema validation failed for ${insight.id}:`, schemaErrors);
        return [];
      }

      return insight.sources.map(source =>
        concurrency(async () => {
          const result = await verifySourceUrl(insight.id, source.url, source.format);
          this.metrics.record(result);

          const report: AuditReport = {
            timestamp: new Date().toISOString(),
            insightId: insight.id,
            sourceUrl: source.url,
            status: result.status,
            latencyMs: result.latencyMs,
            contentHash: result.contentHash,
            errorMessage: result.errorMessage
          };

          reports.push(report);
          this.logger.write(report);

          if (this.callback) {
            await this.callback(report);
          }

          return report;
        })
      );
    });

    await Promise.all(auditTasks);

    console.log('Audit complete. Metrics:', this.metrics.getMetrics());
    return reports;
  }
}

// Execution entry point
if (require.main === module) {
  const CLIENT_ID = process.env.GENESYS_CLIENT_ID || '';
  const CLIENT_SECRET = process.env.GENESYS_CLIENT_SECRET || '';

  if (!CLIENT_ID || !CLIENT_SECRET) {
    console.error('GENESYS_CLIENT_ID and GENESYS_CLIENT_SECRET environment variables are required');
    process.exit(1);
  }

  const auditor = new AgentAssistSourceAuditor(CLIENT_ID, CLIENT_SECRET, async (report) => {
    // External crawler synchronization example
    console.log(`[CRAWLER SYNC] Triggering update for ${report.sourceUrl} | Status: ${report.status}`);
  });

  auditor.runAudit().catch(console.error);
}

Common Errors & Debugging

Error: 401 Unauthorized

• Cause: The OAuth token expired during the audit run, or the client credentials lack the agentassist:insight:read scope.
• Fix: Verify the token cache logic subtracts 30 seconds from expires_in. Ensure the OAuth client in the Genesys Cloud admin console is assigned the correct scope. The AuthManager interceptor automatically refreshes tokens before expiration.

Error: 403 Forbidden

• Cause: The OAuth client has the correct scope but lacks organizational permissions to read Agent Assist insights.
• Fix: Assign the Agent Assist role with Read permissions to the service account associated with the OAuth client. Verify the client is not restricted to a specific sub-account if insights exist at the organization level.

Error: 429 Too Many Requests

• Cause: The audit process exceeds Genesys Cloud API rate limits or external source URLs implement connection throttling.
• Fix: The requestWithRetry function implements exponential backoff with Retry-After header parsing. For external sources, p-limit restricts concurrent HTTP GET requests to 5. Increase the RETRY_BASE_DELAY or reduce concurrency if external providers enforce strict limits.

Error: 5xx Server Error

• Cause: Genesys Cloud infrastructure outage or external source server failure.
• Fix: The verification pipeline catches 5xx responses and marks the source as FAIL with the exact status text. Implement a dead-letter queue or retry scheduler in production environments. The audit log preserves the failure state for governance review.

Error: Schema Validation Failure

• Cause: An insight contains more than 10 sources or references unsupported formats.
• Fix: Genesys Cloud enforces a maximum of 10 sources per insight. The validation step rejects non-compliant insights before network verification to prevent wasted API calls. Update the insight configuration in the Genesys Cloud admin console or remove excess sources via the PUT /api/v2/agentassist/insights/{insightId} endpoint.

Official References

• Agent Assist Insights API Documentation
• OAuth 2.0 Client Credentials Flow
• Genesys Cloud API Rate Limits
• TypeScript Node.js Documentation