ai-engineering-skill
Practical guide for building production ML systems based on Chip Huyen's AI Engineering book. Use when users ask about model evaluation, deployment strategies, monitoring, data pipelines, feature engineering, cost optimization, or MLOps. Covers metrics, A/B testing, serving patterns, drift detection, and production best practices.
ddia-streaming-with-kinesis
Interactive modular learning guide for stream processing concepts from DDIA Chapter 11. Use when the user wants to learn about stream processing, messaging systems, event-driven architectures, Kafka, or needs help with the DDIA Chapter 11 curriculum. Provides 15 bite-sized modules (~45 min each) with flexible prerequisites, hands-on AWS Kinesis examples, progress tracking, and Socratic teaching. Topics include streams vs batch, messaging patterns, partitioned logs, databases & streams, and stream processing fundamentals.
explaining-code
Explains code with visual diagrams and analogies. Use when explaining how code works, teaching about a codebase, or when the user asks "how does this work?"