Adding to contracts ref

website/docs/reference/resource-configs/contract.md

@@ -14,6 +14,13 @@ When the `contract` configuration is enforced, dbt will ensure that your model's
 
 This is to ensure that the people querying your model downstream—both inside and outside dbt—have a predictable and consistent set of columns to use in their analyses. Even a subtle change in data type, such as from `boolean` (`true`/`false`) to `integer` (`0`/`1`), could cause queries to fail in surprising ways.
 
+## Support
+
+At present, model contracts are supported for:
+- SQL models (not yet Python)
+- Models materialized as `table`, `view`, and `incremental` (with `on_schema_change: append_new_columns` or `on_schema_change: fail`)
+- The most popular data platforms — though support and enforcement of different [constraint types](/reference/resource-properties/constraints) vary by platform
+
 ## Data type aliasing
 
 dbt uses built-in type aliasing for the `data_type` defined in your YAML. For example, you can specify `string` in your contract, and on Postgres/Redshift, dbt will convert it to `text`. If dbt doesn't recognize the `data_type` name among its known aliases, it will pass it through as-is. This is enabled by default, but you can opt-out by setting `alias_types` to `false`.
@@ -91,12 +98,6 @@ When you `dbt run` your model, _before_ dbt has materialized it as a table in th
 20:53:45    > in macro assert_columns_equivalent (macros/materializations/models/table/columns_spec_ddl.sql)
 ```
 
-## Support
-
-At present, model contracts are supported for:
-- SQL models (not yet Python)
-- Models materialized as `table`, `view`, and `incremental` (with `on_schema_change: append_new_columns`)
-- The most popular data platforms — though support and enforcement of different [constraint types](/reference/resource-properties/constraints) vary by platform
 
 ### Incremental models and `on_schema_change`