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The Document to MXCP skill provides a sophisticated, code-first pipeline for transforming static files into actionable data within an MXCP project. It intelligently analyzes file content to determine the optimal storage strategy—classifying data for either DuckDB (structured SQL queries) or RAG (narrative semantic search), or both. By handling complex document features like merged cells, hierarchical headers, and embedded images via vision analysis, it ensures that critical context is preserved. The skill prioritizes reproducibility by generating dbt models and automated scripts, allowing teams to maintain a version-controlled, idempotent data environment.
