klingai-rate-limits

name	klingai-rate-limits
description	Handle Kling AI rate limits with proper backoff strategies. Use when experiencing 429 errors or building high-throughput systems. Trigger with phrases like 'klingai rate limit', 'kling ai 429', 'klingai throttle', 'klingai backoff'.
allowed-tools	Read, Write, Edit, Grep
version	1.0.0
license	MIT
author	Jeremy Longshore <[e-mail]>

Klingai Rate Limits

Overview

This skill teaches rate limit handling patterns including exponential backoff, token bucket algorithms, request queuing, and concurrent job management for reliable Kling AI integrations.

Prerequisites

• Kling AI integration
• Understanding of HTTP status codes
• Python 3.8+ or Node.js 18+

Instructions

Follow these steps to handle rate limits:

1. Understand Limits: Know the rate limit structure
2. Implement Detection: Detect rate limit responses
3. Add Backoff: Implement exponential backoff
4. Queue Requests: Add request queuing
5. Monitor Usage: Track rate limit consumption

Output

Successful execution produces:

• Rate limit handling without errors
• Smooth request throughput
• Proper backoff behavior
• Concurrent job management

Error Handling

See {baseDir}/references/errors.md for comprehensive error handling.

Examples

See {baseDir}/references/examples.md for detailed examples.

Resources

• Kling AI Rate Limits
• Exponential Backoff
• Token Bucket Algorithm