Docyrus Data Source Design

Design a data source's schema with docyrus studio, then validate the schema and test it with real records before handing it off. A data source is a collection of records with a typed schema (fields). This skill is the schema-authoring counterpart to record querying (docyrus ds / dsql).

For the full CLI flag reference see the docyrus-cli-app skill; for platform concepts see docyrus-platform; for general schema-design principles see the database-architect skill. This skill is the data-source-specific workflow that ties them together.

Workflow

Follow these phases in order. Do not skip validation/testing — an unvalidated schema is not done.

1. Confirm the app and auth. Every data source belongs to an app. Resolve the app first:

   docyrus auth who --json            # confirm an active session + tenant
   docyrus apps list --json           # find the target appSlug / appId
   

   If there is no session, stop and ask the user to run docyrus auth login (interactive).

2. Model the entities. Turn the requirement into data sources and fields before issuing commands. Per entity decide: the singular/plural name, the slug, each attribute → field type, which fields are selections (need enums), and which are relations to other data sources. Sketch this for the user and confirm naming when the domain is ambiguous. See references/field-types.md to pick types.