The interface is localized. Skill descriptions and documents are machine-translated by AI into your language; code, commands, paths and technical terms stay in the original, and the author's document governs.
Explore skills
Productivity · SKILL.md

klingai-rate-limits

klingai-rate-limits

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'.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill documentation

GitHub

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

Saved skills