Claude-skill-registry klingai-reference-architecture

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 "$T/skills/data/klingai-reference-architecture" ~/.claude/skills/majiayu000-claude-skill-registry-klingai-reference-architecture && rm -rf "$T"

manifest: skills/data/klingai-reference-architecture/SKILL.md

Klingai Reference Architecture

Overview

This skill provides production-ready reference architectures for building scalable video generation platforms using Kling AI, including microservices design, event-driven patterns, and infrastructure recommendations.

Prerequisites

Understanding of distributed systems
Cloud infrastructure experience (AWS/GCP/Azure)
Docker/Kubernetes knowledge helpful

Instructions

Follow these steps to design your architecture:

Choose Pattern: Select appropriate architecture pattern
Design Components: Map out service boundaries
Plan Infrastructure: Choose cloud services
Implement Resilience: Add fault tolerance
Monitor & Scale: Set up observability

Output

Successful execution produces:

Scalable video generation platform
Event-driven processing pipeline
Container-ready deployment configs
Auto-scaling based on queue depth

Error Handling

See

{baseDir}/references/errors.md

for comprehensive error handling.

Examples

See

{baseDir}/references/examples.md

for detailed examples.