Connect LinkML
Let the pipeline read the model that is already right.
How CoreModels works with LinkML
LinkML is designed as a source of truth for biomedical and scientific models. Generation exists — and teams still copy. Every copy starts drifting the day it is made.
CoreModels treats the LinkML file as an importable estate. Enumerations with meanings become taxonomies tied to URIs. Slots become elements with types and constraints. Conversion recipes (including LinkML to Synapse) carry a ledger of what the target format cannot hold.
Re-import after a curator change and the CI gate fails the pipeline artifacts that did not hear about the new permissible value.
Recipes
No recipes yet for LinkML. The articles below still describe the problem this connector is built to close.
Uses
Problems this connector fixes
Articles that explain the gap, then point at the recipe that closes it.
Your LinkML Model Is Right. Your Pipeline Never Read It.
The ticket that lands on a Monday morning rarely says "semantic drift." It says: *rows rejected, unexpected value in `sex` column.* Someone traces it back. Six weeks earlier a curator added a permissible value to an enum in the team's LinkML model, complete with a `meaning` URI pointing at a specific ontology term. The model was correct that day and has been correct every day since. The warehouse constraint, the JSON Schema the API validates against, and the Avro subject in the registry were each written by hand from an older reading of that file, and none of them heard about the change.
OutcomesOne Model, Every Downstream Format: What Governed LinkML Actually Buys You
The clearest sign that a team has adopted this is what has gone missing from their repository. The four hand-maintained schema files that used to shadow the LinkML model — a DDL script, a JSON Schema, an Avro subject definition, a catalog entry — are no longer there. Not stale, not deprecated, not marked "regenerate me." Gone, because they are outputs now.
GovernanceWho Approved That Meaning? Governing a LinkML Model You Can Defend
Sooner or later somebody senior asks a question that sounds simple and is not: *how do you know the column in the warehouse means what the model says it means, and who decided that?*
EcosystemLinkML Doesn't Need Us to Generate JSON Schema
Start with the awkward fact; it is the honest way in. LinkML already ships a generator toolchain. If your entire need is "turn this model into a validation artifact," the project's own tooling does that, maintained by the people who write the specification, and you should keep using it. A product that opens by claiming otherwise is selling something.
AgentsThe Expensive Kind of Wrong: Agents, LinkML, and Guessed Semantics
The costly failure of an AI agent working on schemas is not the one that errors out. It is the output that is perfectly well-formed and quietly invented — valid YAML, sensible field names, a plausible type for every slot, and three or four decisions nobody made. It passes review because it looks like the work, and fails in production.
QuickstartLinkML to Postgres in One Call: A CoreModels Quickstart
Ten minutes, one YAML file, one HTTP call. By the end of this you will have converted a LinkML schema into Postgres DDL through CoreModels, read the machine-readable ledger of everything the conversion could not carry exactly, and sent the same schema back out as LinkML unchanged.
APIThe LinkML HTTP Surface: Import, Export, Map, Replay
There are ten routes on the CoreModels transform API. Five of them matter if LinkML is your source or your target, and the first thing to settle is which one you actually want — because the difference between them is not the format, it is whether anything gets written and who decides what passes through.
MCPGive an Agent a LinkML Schema: `transform_schema` over MCP
> **Analyst:** Here's our product catalog in LinkML. The warehouse team needs a Postgres table for it. What do we lose?
AutomationPlans, Not Scripts: Repeatable LinkML Conversion Pipelines
A conversion you cannot reproduce is not a pipeline; it is a favor someone did once. The interesting question for automation is not "can this tool turn LinkML into Postgres DDL" — it is "will the run in six months, on a build agent, with a token nobody remembers issuing, produce the same bytes and tell me if it did not."
Deep diveInside the LinkML Coder: Every Construct, Every Loss
Start with one line of YAML: