adding new MF command

website/docs/docs/build/metricflow-commands.md

@@ -26,13 +26,13 @@ Using MetricFlow with dbt Cloud means you won't need to manage versioning &mdash
 
 - MetricFlow [commands](#metricflow-commands) are embedded in the dbt Cloud CLI. This means you can immediately run them once you install the dbt Cloud CLI and don't need to install MetricFlow separately.
 - You don't need to manage versioning — your dbt Cloud account will automatically manage the versioning for you.
-
+ 
 </TabItem>
 
 <TabItem value="cloud ide" label="dbt Cloud IDE">
 
 :::info
-You can create metrics using MetricFlow in the dbt Cloud IDE. However, support for running MetricFlow commands in the IDE will be available soon.
+You can create metrics using MetricFlow in the dbt Cloud IDE and [run `dbt sl validate`](/docs/build/validation#validations-command). Support for running more MetricFlow commands in the IDE will be available soon.
 :::
 
 </TabItem>
@@ -78,10 +78,9 @@ You can use the `dbt sl` prefix before the command name to execute them in the d
 - [`query`](#query) &mdash; Query metrics, saved queries, and dimensions you want to see in the command line interface. Refer to [query examples](#query-examples) to help you get started.
 - [`export`](#export) &mdash;  Runs exports for a singular saved query for testing and generating exports in your development environment. You can also use the `--select` flag to specify particular exports from a saved query.
 - [`export-all`](#export-all) &mdash; Runs exports for multiple saved queries at once, saving time and effort.
-
+- [`validate-configs`](#validate-configs) &mdash; Validates semantic model configurations.
 
 <!--below commands aren't supported in dbt cloud yet
-- [`validate-configs`](#validate-configs) &mdash; Validates semantic model configurations.
 - [`health-checks`](#health-checks) &mdash; Performs data platform health check.
 - [`tutorial`](#tutorial) &mdash; Dedicated MetricFlow tutorial to help get you started.
 -->
@@ -222,10 +221,8 @@ The list of available saved queries:
 
 The following command performs validations against the defined semantic model configurations.
 
-Note, in dbt Cloud you don't need to validate the Semantic Layer config separately. Running a dbt command (such as `dbt parse`, `dbt build`, `dbt compile`, `dbt run`) automatically checks it.
-
 ```bash
-
+dbt sl validate-configs # dbt Cloud users
 mf validate-configs # In dbt Core
 
 Options:

website/docs/docs/build/validation.md

@@ -14,13 +14,13 @@ The code that handles validation [can be found here](https://github.com/dbt-labs
 
 ## Validations command
 
-You can run validations against the defined semantic model configurations from the command line with the following [MetricFlow commands](/docs/build/metricflow-commands):
-
-Note, in dbt Cloud you don't need to validate the Semantic Layer config separately. Running a dbt command (such as `dbt parse`, `dbt build`, `dbt compile`, or `dbt run`) automatically checks it.
+You can run validations from dbt Cloud or the command line with the following [MetricFlow commands](/docs/build/metricflow-commands). In dbt Cloud, you need developer credentials to run `dbt sl validate-configs` in the IDE or CLI, and deployment credentials to run it in CI.
 
 ```bash
+dbt sl validate-configs # dbt Cloud users
 mf validate-configs # dbt Core users
 ```
+
 
 ## Parsing