perplexity-performance-tuning

Quick Review

Strong skill with comprehensive technical implementation details for Perplexity API optimization. The description clearly covers caching, batching, and connection pooling with appropriate trigger phrases. Task knowledge is excellent with production-ready code examples for multiple strategies (LRU cache, Redis, DataLoader, connection pooling). Structure is good with logical flow from benchmarks through implementation to monitoring, though some sections could be more concise. Novelty is moderate—while performance optimization is valuable, the techniques (caching, batching, connection pooling) are standard patterns that a competent CLI agent could implement with sufficient prompting, though this skill does reduce token overhead and provides Perplexity-specific context. Minor improvements: the latency benchmarks appear generic rather than Perplexity-specific, and the skill could benefit from more concrete decision trees for when to apply each optimization strategy.