ai-data-engineering

The skill's footprint is coherent with its stated purpose of building data engineering infrastructure for AI/ML and RAG pipelines. It centers on well-known tooling (LangChain, Qdrant, Feast, Dagster, LakeFS, dbt) and recommended embedding strategies, with normal packaging practices and credential usage guidance. No evident malicious behavior, credential harvesting, or insecure data flows are present in the provided materials. Overall risk is low to moderate, primarily driven by best-practice credential management and ensuring secure orchestration in production.