retellai-performance-tuning

Quick Review

This skill provides comprehensive technical knowledge for optimizing Retell AI API performance through caching, batching, and connection pooling. The description clearly articulates when to use the skill with good trigger phrases. The task knowledge is strong with concrete TypeScript code examples covering LRU caching, Redis, DataLoader batching, connection pooling, and pagination. The structure is logical with clear sections and benchmarks. However, the novelty score is low because these are standard performance optimization patterns (caching, batching, connection pooling) that a capable CLI agent could implement with general web development knowledge. The techniques are not particularly unique to Retell AI, and most examples use generic libraries. The skill is well-executed but represents common performance engineering practices rather than complex domain-specific optimizations that would significantly reduce token usage or require specialized expertise.