ReusStdFlow: A Standardized Reusability Framework for Dynamic Workflow Construction in Agentic AI.

ReusStdFlow is a framework designed to tackle the "reusability dilemma" and structural hallucinations in enterprise Agentic AI. It proposes an "Extraction-Storage-Construction" paradigm that deconstructs heterogeneous, platform-specific Domain-Specific Languages (DSLs) into standardized, modular workflow segments. Utilizing a dual-knowledge architecture, it achieves over 90% accuracy in extraction and construction on 200 real-world workflows, offering a standardized solution for automated reorganization and efficient reuse of enterprise digital assets.