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.mdsource 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:
- Prepare Batch: Collect all prompts and parameters
- Rate Limit Planning: Calculate submission pace
- Parallel Submission: Submit jobs within limits
- Track Progress: Monitor all jobs simultaneously
- 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.