MCP.directory

klingai-rate-limits

by jeremylongshore
9
0
Source

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'.

Install

mkdir -p .claude/skills/klingai-rate-limits && curl -L -o skill.zip "https://mcp.directory/api/skills/download/2748" && unzip -o skill.zip -d .claude/skills/klingai-rate-limits && rm skill.zip

Installs to .claude/skills/klingai-rate-limits

About this skill

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 ${CLAUDE_SKILL_DIR}/references/errors.md for comprehensive error handling.

Examples

See ${CLAUDE_SKILL_DIR}/references/examples.md for detailed examples.

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