DBML Validator

Purpose & User Intent: The DBML Validator provides precise feedback on DBML definitions used to model databases. It targets developers, data architects, and deployment teams seeking early error detection. Conceptually, it parses DBML text, builds an internal schema model, and reports syntactic and semantic issues with exact locations. It supports standard DBML constructs such as tables, columns, primary keys, foreign keys, and indexes, and flags unknown tokens or structural gaps. Core features include a robust parser, line/column exactness, error categorization, and a structured JSON output suitable for automation. Optional features include dialect-aware hints and lint suggestions to improve DBML quality. Use cases include pre-commit validation, CI pipeline checks, and schema reviews where quick feedback accelerates development.
What makes it valuable is the combination of accurate parsing, actionable errors, and automation-friendly outputs. The tool helps teams avoid migration failures caused by subtle DBML mistakes, and it provides a consistent standard for schema definitions across projects. It is designed to scale to large schemas without blocking development, and it can be integrated into existing tooling via its structured results. The validator emphasizes deterministic behavior and clear messaging, which reduces back-and-forth during code reviews and lowers the risk of schema drift in production environments.
Core features and use cases include syntax validation, foreign key consistency checks, duplicate table detection, and a summarized report suitable for CI dashboards. Use cases span early development, PR reviews, and automated quality gates, ensuring DBML models are robust before code becomes part of a release.