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

This skill enforces production-ready PostHog SDK usage patterns in TypeScript and Python to improve reliability and consistency.

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

# PostHog SDK Patterns

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

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

## Instructions

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

let instance: PostHogClient | null = null;

export function getPostHogClient(): PostHogClient {
  if (!instance) {
    instance = new PostHogClient({
      apiKey: process.env.POSTHOG_API_KEY!,
      // Additional options
    });
  }
  return instance;
}
```

### Step 2: Add Error Handling Wrapper
```typescript
import { PostHogError } from '@posthog/sdk';

async function safePostHogCall<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 PostHogError) {
      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, PostHogClient>();

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

### Python Context Manager
```python
from contextlib import asynccontextmanager
from posthog import PostHogClient

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

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

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

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

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

Overview

This skill applies production-ready PostHog SDK patterns for TypeScript and Python to make instrumentation reliable, type-safe, and maintainable. It packages singleton and factory client approaches, safe call wrappers, retry strategies, and runtime validation into actionable patterns you can adopt. Use it to standardize PostHog usage across services or teams.

How this skill works

The skill provides concrete code patterns: a singleton client for single-tenant apps, a tenant factory for multi-tenant contexts, and an async context manager for Python. It wraps SDK calls in a safe error-handling helper, adds exponential-backoff retry logic, and recommends runtime schema validation (e.g., Zod) for API responses. Logging hooks and structured error capture are included to surface operational issues.

When to use it

  • Implementing or refactoring PostHog instrumentation in a service
  • Establishing team-wide coding standards for analytics SDK usage
  • Building multi-tenant integrations that require per-tenant clients
  • Hardening SDK calls against transient network or API failures
  • Validating API responses to detect breaking changes early

Best practices

  • Expose a single getClient or getClientForTenant API instead of constructing clients inline
  • Wrap all SDK operations with a safe wrapper that returns {data, error} or throws consistently
  • Use exponential backoff with a small maxRetries for transient errors
  • Validate critical responses at runtime using a schema validator (Zod or similar)
  • Log structured error metadata (codes, messages, tenantId, requestId) for observability

Example use cases

  • Server-side event tracking where a singleton PostHog client improves performance and memory usage
  • Multi-tenant SaaS that creates a PostHog client per tenant using a factory map
  • Background jobs that call analytics APIs wrapped with retry and safe error handling
  • Python async services using a context manager to ensure clients close cleanly
  • APIs that validate PostHog responses to detect schema drift after SDK/API upgrades

FAQ

Should I always use a singleton client?

Use a singleton for single-tenant apps to reuse resources. For multi-tenant systems, prefer a tenant-aware factory that caches per-tenant clients.

How many retries are recommended?

Start with 2–3 retries and exponential backoff (e.g., base 1s). Monitor failure patterns and adjust to balance latency and reliability.