vastai-performance-tuning

Quick Review

This skill provides comprehensive implementation patterns for optimizing Vast.ai API performance through caching, batching, and connection pooling. The description is clear and trigger phrases are well-defined. Task knowledge is strong with concrete TypeScript code examples for LRU caching, Redis caching, DataLoader batching, connection pooling, and performance monitoring. Structure is logical with clear sections and step-by-step instructions. However, novelty is low because these are standard performance optimization patterns (caching, batching, connection pooling) that a CLI agent could reasonably implement with sufficient prompting. The techniques are well-documented general practices rather than Vast.ai-specific optimizations. The skill is useful as a reference template but doesn't significantly reduce token cost compared to asking an AI to 'implement caching and batching for API calls'.