validate-scaffold

To validate a data engineering project scaffold against LLD requirements, run automated compliance checks on the directory tree, utility modules, and infrastructure files. This verifies your local-first project setup meets design rules and produces per-check PASS/FAIL/INDETERMINATE verdicts for any compliance gaps.

You can check if your DuckDB and SQLMesh project setup is ready by running automated smoke tests. These execute uv sync, perform utility module import checks, and run pytest collection to catch missing dependencies or broken imports before you start building pipelines.

DMS StructType schema contract validation is the process of verifying that your data model specification schemas match the implemented project structure. It surfaces compliance gaps by checking your foundation-layer project setup against DMS rules before pipeline and model development begins.

Yes, scaffold validation works with Apache Superset and UV environments. It runs read-only checks and smoke tests specifically designed for local-first data engineering environments using UV, DuckDB, SQLMesh, and Apache Superset to confirm the foundation layer is fully compliant.

A project scaffold fails smoke testing when uv sync encounters missing dependencies, utility module imports break, or pytest collection surfaces configuration errors. Running scaffold validation identifies these exact setup issues early by providing specific PASS/FAIL/INDETERMINATE verdicts for each compliance check.

Yes, you can run scaffold compliance checks without write operations because the validation process applies read-only checks to your project directory. It analyzes the LLD directory structure, Make targets, and infrastructure rules without modifying your files, safely running smoke tests to confirm readiness.