home / skills / jeremylongshore / claude-code-plugins-plus-skills / retellai-sdk-patterns

This skill helps you implement production-ready Retell AI SDK patterns in TypeScript and Python, improving reliability, consistency, and team standards.

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---
name: retellai-sdk-patterns
description: |
  Apply production-ready Retell AI SDK patterns for TypeScript and Python.
  Use when implementing Retell AI integrations, refactoring SDK usage,
  or establishing team coding standards for Retell AI.
  Trigger with phrases like "retellai SDK patterns", "retellai best practices",
  "retellai code patterns", "idiomatic retellai".
allowed-tools: Read, Write, Edit
version: 1.0.0
license: MIT
author: Jeremy Longshore <[email protected]>
---

# Retell AI SDK Patterns

## Overview
Production-ready patterns for Retell AI SDK usage in TypeScript and Python.

## Prerequisites
- Completed `retellai-install-auth` setup
- Familiarity with async/await patterns
- Understanding of error handling best practices

## Instructions

### Step 1: Implement Singleton Pattern (Recommended)
```typescript
// src/retellai/client.ts
import { RetellAIClient } from '@retellai/sdk';

let instance: RetellAIClient | null = null;

export function getRetell AIClient(): RetellAIClient {
  if (!instance) {
    instance = new RetellAIClient({
      apiKey: process.env.RETELLAI_API_KEY!,
      // Additional options
    });
  }
  return instance;
}
```

### Step 2: Add Error Handling Wrapper
```typescript
import { Retell AIError } from '@retellai/sdk';

async function safeRetell AICall<T>(
  operation: () => Promise<T>
): Promise<{ data: T | null; error: Error | null }> {
  try {
    const data = await operation();
    return { data, error: null };
  } catch (err) {
    if (err instanceof Retell AIError) {
      console.error({
        code: err.code,
        message: err.message,
      });
    }
    return { data: null, error: err as Error };
  }
}
```

### Step 3: Implement Retry Logic
```typescript
async function withRetry<T>(
  operation: () => Promise<T>,
  maxRetries = 3,
  backoffMs = 1000
): Promise<T> {
  for (let attempt = 1; attempt <= maxRetries; attempt++) {
    try {
      return await operation();
    } catch (err) {
      if (attempt === maxRetries) throw err;
      const delay = backoffMs * Math.pow(2, attempt - 1);
      await new Promise(r => setTimeout(r, delay));
    }
  }
  throw new Error('Unreachable');
}
```

## Output
- Type-safe client singleton
- Robust error handling with structured logging
- Automatic retry with exponential backoff
- Runtime validation for API responses

## Error Handling
| Pattern | Use Case | Benefit |
|---------|----------|---------|
| Safe wrapper | All API calls | Prevents uncaught exceptions |
| Retry logic | Transient failures | Improves reliability |
| Type guards | Response validation | Catches API changes |
| Logging | All operations | Debugging and monitoring |

## Examples

### Factory Pattern (Multi-tenant)
```typescript
const clients = new Map<string, RetellAIClient>();

export function getClientForTenant(tenantId: string): RetellAIClient {
  if (!clients.has(tenantId)) {
    const apiKey = getTenantApiKey(tenantId);
    clients.set(tenantId, new RetellAIClient({ apiKey }));
  }
  return clients.get(tenantId)!;
}
```

### Python Context Manager
```python
from contextlib import asynccontextmanager
from retellai import RetellAIClient

@asynccontextmanager
async def get_retellai_client():
    client = RetellAIClient()
    try:
        yield client
    finally:
        await client.close()
```

### Zod Validation
```typescript
import { z } from 'zod';

const retellaiResponseSchema = z.object({
  id: z.string(),
  status: z.enum(['active', 'inactive']),
  createdAt: z.string().datetime(),
});
```

## Resources
- [Retell AI SDK Reference](https://docs.retellai.com/sdk)
- [Retell AI API Types](https://docs.retellai.com/types)
- [Zod Documentation](https://zod.dev/)

## Next Steps
Apply patterns in `retellai-core-workflow-a` for real-world usage.

Overview

This skill applies production-ready Retell AI SDK patterns for TypeScript and Python to help teams implement reliable, maintainable integrations. It focuses on singleton and factory client creation, structured error handling, retries with exponential backoff, and runtime response validation. Use it to standardize SDK usage and reduce operational errors in production systems.

How this skill works

The skill provides concrete code patterns and utilities: a singleton client for single-tenant apps, a factory pattern for multi-tenant scenarios, an async context manager for Python, and wrapper functions for safe calls and retries. It recommends type/runtime validation (e.g., Zod) and structured logging to detect API changes and surface actionable errors. Combine these patterns to create a type-safe, resilient Retell AI integration.

When to use it

  • Implementing a new Retell AI integration in TypeScript or Python.
  • Refactoring existing code to improve reliability and observability.
  • Building multi-tenant services that need per-tenant API clients.
  • Hardening SDK calls against transient failures and API changes.
  • Establishing team coding standards for Retell AI usage.

Best practices

  • Use a singleton or factory to centralize client creation and configuration.
  • Wrap all SDK calls in a safe wrapper that logs structured error metadata.
  • Add retry with exponential backoff for idempotent operations and transient errors.
  • Validate external responses at runtime with schemas (Zod or Python equivalents).
  • Close or cleanup clients (context managers) to avoid resource leaks in async code.

Example use cases

  • Web service that issues calls to Retell AI for content generation and needs robust retry and logging.
  • Multi-tenant SaaS where each tenant uses its own Retell AI API key via a client factory.
  • Batch processing job that validates API responses before persisting to a database.
  • Interactive notebook tutorial demonstrating safe SDK usage and response schemas.

FAQ

Should I always use the singleton pattern?

Use a singleton for single-tenant apps to centralize config; use a factory when you must support multiple API keys or tenants.

How many retries are appropriate?

Start with 2–3 retries and exponential backoff; tune based on observed transient failure rates and latency constraints.