deepgram-performance-tuning

Quick Review

This is a high-quality skill that provides comprehensive, production-ready code for optimizing Deepgram API performance. The description clearly articulates when to use the skill, with good trigger phrases. Task knowledge is excellent, offering detailed TypeScript implementations covering audio preprocessing, connection pooling, streaming, parallel processing, caching, and metrics—all essential for real-world performance tuning. The structure is clear with a logical flow from prerequisites through optimization factors to step-by-step instructions and examples. Novelty is solid: while a CLI agent could research these topics, assembling this complete optimization toolkit with working code examples (ffmpeg integration, connection pooling, streaming patterns, parallel processing with p-limit) would require significant tokens and multiple iterations. The skill provides immediate, actionable implementations that would be time-consuming to recreate. Minor areas for improvement: the high-level steps (1-4) could be slightly more detailed, and the structure could benefit from a quick reference table mapping common performance problems to specific code solutions.