This project provides a custom rule set and configuration profiles for content processing tools. It consists of declarative rules and JSON-based configurations that define how a target application identifies and handles specific types of data.
The system enables dynamic tool configuration by injecting external logic at runtime, removing the need for core system recompilation. These configurations use schema-validated rule sets to ensure structural integrity and prevent errors during processing.
The project implements pattern-based data identification using regular expressions and a priority-based execution logic to determine which rules take precedence. This allows for automated content processing and the customization of tool behaviors through a declarative rule engine.
