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SKILL.md

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 <jeremy@intentsolutions.io>

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