Claude-skill-registry klingai-batch-processing

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 "$T/skills/data/klingai-batch-processing" ~/.claude/skills/majiayu000-claude-skill-registry-klingai-batch-processing && rm -rf "$T"
manifest: skills/data/klingai-batch-processing/SKILL.md
source content

Klingai Batch Processing

Overview

This skill teaches efficient batch processing patterns for generating multiple videos, including parallel submission, progress tracking, rate limit management, and result collection.

Prerequisites

  • Kling AI API key with sufficient credits
  • Python 3.8+ with asyncio support
  • Understanding of async/await patterns

Instructions

Follow these steps for batch processing:

  1. Prepare Batch: Collect all prompts and parameters
  2. Rate Limit Planning: Calculate submission pace
  3. Parallel Submission: Submit jobs within limits
  4. Track Progress: Monitor all jobs simultaneously
  5. Collect Results: Gather outputs and handle failures

Output

Successful execution produces:

  • Parallel job submission within rate limits
  • Real-time progress tracking
  • Collected results with success/failure status
  • Performance metrics (duration, throughput)

Error Handling

See

{baseDir}/references/errors.md
for comprehensive error handling.

Examples

See

{baseDir}/references/examples.md
for detailed examples.

Resources