Catalog persistent data entities and storage occurrences across multi-repo codebases.
npx skills add https://github.com/vishalkhondre/unearth --skill 07-data-model
Please help me install this Agent Skill. Skill: 07-data-model Source: https://github.com/vishalkhondre/unearth/tree/main/skills/07-data-model Command: npx skills add https://github.com/vishalkhondre/unearth --skill 07-data-model
Discovers all persistent data entities in the codebase, identifies how and where they are stored, and traces ownership to capabilities for architectural clarity.
Run a full data-model discovery across the repository to inventory entities, storage, projections, and ownership.
High-intent search queries and answers about installing and using this skill.
To map data entities to owning capabilities in a multi-repo architecture, this skill inventories persistent storage occurrences and traces cross-project usage. It outputs an entity inventory detailing ownership by capability, storage technology, and cross-store references.
The best way to inventory all persistent data entities is to run a full data-model discovery across the repository. This process catalogs storage occurrences, mapping each entity to its specific storage technology, collection or table names, and key fields.
Cross-project data coupling analysis works by mapping storage types, projections, and cross-project entity usage to reveal coupling hotspots. It identifies high-coupling entities and missing constraints to highlight architectural risks across multiple repositories.
Yes, you can trace cross-store references and projections for DTOs across repositories. The analysis maps entities to owning capabilities and cross-project usage, including projections and DTOs, to expose coupling and reference patterns.
Yes, this data-model discovery specifically applies to multi-repo architectures where capabilities own entities. It maps storage types and cross-project usage to reveal coupling hotspots and suggest architectural constraints.
You need suggested constraints for high-coupling entities to mitigate architectural risks identified during hotspot analysis. The data-model discovery highlights missing constraints and cross-store references, providing recommendations to reduce coupling and ensure stability.
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