groq-performance-tuning

Quick Review

The skill provides a well-structured guide to optimizing Groq API performance with practical code examples for caching, batching, and connection pooling. The description clearly conveys when to use the skill and appropriate trigger phrases. Task knowledge is strong with concrete TypeScript implementations covering multiple optimization strategies. However, novelty is limited as these are standard performance optimization patterns (LRU caching, DataLoader batching, HTTP agent pooling) that a competent CLI agent could implement with appropriate prompting, though the consolidated approach does save tokens. The structure is clear but could benefit from separation into multiple files for complex implementations. Overall, this is a solid reference skill that reduces implementation friction but doesn't represent highly novel or complex functionality that would be difficult for an LLM to generate independently.