jeremylongshore

klingai-rate-limits

@jeremylongshore/klingai-rate-limits
jeremylongshore
1,004
123 forks
Updated 1/18/2026
View on GitHub

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'.

Installation

$skills install @jeremylongshore/klingai-rate-limits
Claude Code
Cursor
Copilot
Codex
Antigravity

Details

Pathplugins/saas-packs/klingai-pack/skills/klingai-rate-limits/SKILL.md
Branchmain
Scoped Name@jeremylongshore/klingai-rate-limits

Usage

After installing, this skill will be available to your AI coding assistant.

Verify installation:

skills list

Skill Instructions


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

More by jeremylongshore

View all
rabbitmq-queue-setup
1,004

Rabbitmq Queue Setup - Auto-activating skill for Backend Development. Triggers on: rabbitmq queue setup, rabbitmq queue setup Part of the Backend Development skill category.

model-evaluation-suite
1,004

evaluating-machine-learning-models: This skill allows Claude to evaluate machine learning models using a comprehensive suite of metrics. It should be used when the user requests model performance analysis, validation, or testing. Claude can use this skill to assess model accuracy, precision, recall, F1-score, and other relevant metrics. Trigger this skill when the user mentions "evaluate model", "model performance", "testing metrics", "validation results", or requests a comprehensive "model evaluation".

neural-network-builder
1,004

building-neural-networks: This skill allows Claude to construct and configure neural network architectures using the neural-network-builder plugin. It should be used when the user requests the creation of a new neural network, modification of an existing one, or assistance with defining the layers, parameters, and training process. The skill is triggered by requests involving terms like "build a neural network," "define network architecture," "configure layers," or specific mentions of neural network types (e.g., "CNN," "RNN," "transformer").

oauth-callback-handler
1,004

Oauth Callback Handler - Auto-activating skill for API Integration. Triggers on: oauth callback handler, oauth callback handler Part of the API Integration skill category.