langchain-performance-tuning

Quick Review

Excellent skill for LangChain performance optimization with comprehensive, actionable code examples covering caching, batching, streaming, prompt optimization, connection pooling, and model selection. The description clearly defines when to invoke the skill. Task knowledge is strong with 7 concrete optimization steps, benchmarking utilities, and a helpful performance metrics table. Structure is logical and well-organized with clear step progression. Novelty is moderate-to-good: while individual optimizations are documented in LangChain/OpenAI docs, consolidating them into a systematic tuning workflow with comparative metrics and ready-to-use code provides meaningful value and token savings for a CLI agent tackling performance issues holistically.