Glyph: A Multi-Strategy Agentic System for Column Description and Sensitivity-Ontology Tagging of Enterprise Data Catalogs

This post introduces Glyph, a production system that frames column description generation and data classification tagging as cooperating LLM agents. It utilizes a Descriptor agent with active RAG grounded in enterprise GitHub code via a reasoning-acting tool loop. The Tagger agent employs three parallel strategies (description, regex, metadata) and fuses their outputs with Reciprocal Rank Fusion (RRF). A fine-tuned MiniLM metadata encoder significantly improves retrieval accuracy. The system emphasizes value-free, code-grounded design, per-tag provenance, and graceful degradation for auditable and operable cataloging.