Data Build Tool

This tool analyzes GitHub repositories to reveal how data build projects are structured and where to begin building. It focuses on dbt-like workflows, identifying models, seeds, and macros, and outputs an actionable plan. It does not execute code but provides the scaffolding and validation guidance needed to start consistent, auditable projects.

Conceptually, a repository is treated as a data transformation pipeline with defined inputs, transformations, and outputs. The tool computes dependencies, enforces naming and lineage conventions, and generates scaffolding templates that can be wired into CI/CD pipelines. It also produces a validation report that highlights gaps and potential conflicts before work begins.

Beneficiaries include data engineers, analytics engineers, and platform teams who must align on project scope and quality gates. Unique value lies in reproducible scaffolds, rule templates for governance, and export formats suitable for integration with common CI systems. Use cases include project kickoff, repository onboarding, and pre-implementation planning for data modernization efforts.

Core features include repo analysis, plan generation, rule templating, and artifact export. The tool emphasizes a non-runtime, planning-oriented workflow, providing actionable guidance and structured outputs that accelerate delivery while reducing miscommunication.