Claude-skill-registry klingai-async-workflows

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/klingai-async-workflows" ~/.claude/skills/majiayu000-claude-skill-registry-klingai-async-workflows && rm -rf "$T"

manifest: skills/data/klingai-async-workflows/SKILL.md

Klingai Async Workflows

Overview

This skill demonstrates building asynchronous workflows for video generation, including job queues, state machines, event-driven processing, and integration with workflow orchestration systems.

Prerequisites

Kling AI API key configured
Python 3.8+ or Node.js 18+
Message queue (Redis, RabbitMQ) or workflow engine

Instructions

Follow these steps to build async workflows:

Design Workflow: Map out the video generation pipeline
Implement Queue: Set up job queue for async processing
Create Workers: Build workers to process jobs
Handle States: Manage job state transitions
Add Monitoring: Track workflow progress

Output

Successful execution produces:

Validated and queued workflow jobs
State machine driven processing
Complete audit trail of transitions
Reliable job completion or failure handling

Error Handling

See

{baseDir}/references/errors.md

for comprehensive error handling.

Examples

See

{baseDir}/references/examples.md

for detailed examples.