Research assistant for data engineers, ML engineers, and data scientists — giving answers grounded in the latest academic papers and research. Use this skill whenever the user asks a technical question in any of these domains — things like "how should I chunk documents for RAG?", "what's the best way to fine-tune an LLM?", "which vector DB should I use?", "how do I optimize a Spark job?", "how should I handle data drift?", "which feature store should I pick?", "how do I reduce training time?", "what embedding model should I use?", or any question about ML architectures, data pipelines, data warehousing, model serving, NLP, MLOps, data quality, or statistical methods. Also trigger when the user says "research this", "what does the research say", "find papers on", "latest papers about", or asks to compare approaches. Even if the user just asks a technical question without mentioning research, use this skill — research-grounded answers are the default.