CoreModelsGuides
SQL
Give the column nobody can explain a definition your team governs and your agents act on.
- Your First DDL Transform Should Write Nothing: a SQL QuickstartQuickstart · The most accurate description of your data is almost certainly a CREATE TABLE statement sitting in a migrations folder. It is reviewed, versioned, and executable — and it is legible to exactly one kind of consumer. Getting it out of that folder and into a data contract, a JSON Schema, or another vendor's dialect is usually where the accuracy stops.
- Four Routes, One Envelope: SQL DDL on the CoreModels Transform APIAPI · | Route | Role | What it touches | |---|---|---| | POST /graph/transform/schema/import/{projectId} | Admin | writes the DDL's model into the project | | POST /graph/transform/schema/export/{projectId} | Viewer | reads the project, returns CREATE TABLE text | | POST /graph/transform/schema/map/{projectId} | Viewer (ai: Editor) | nothing — stateless, source in, target out | | POST /graph/transform/plan/execute/{projectId} | Viewer | nothing — replays a stored plan |
- Teaching an Agent to Read DDL: the transform_schema MCP ToolMCP · A partner attaches subscriber_dump.sql to a ticket. Backticks, an ENUM, a DATETIME, and one column named by a DBA who shouts. Your canonical model is a JSON Schema in a repo. Somebody has to reconcile the two, and historically that somebody spent an afternoon in a diff viewer.
- Commit the Plan, Not the Guess: SQL Conversion Pipelines That RepeatAutomation · Database teams solved schema-as-code years ago. DDL lives in git, migrations get reviewed, nobody types ALTER TABLE into production by hand. Then the schema has to leave the database — become a JSON Schema for the API team, a contract for the platform team, DDL for a second warehouse — and the discipline evaporates into a conversion script that one person ran once on a laptop.
- No Annotation Slot: How the SQL DDL Coder Carries Meaning, and Where It StopsDeep dive · Every other format on the CoreModels transform surface has somewhere to put meaning. JSON Schema has x- keywords. Avro has custom attributes. LinkML has slot_uri and meaning. OWL *is* meaning. SQL DDL has a name, a type, and a handful of constraints — and no annotation slot at all.
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