clarify SL test/query language

website/docs/docs/build/sl-getting-started.md

@@ -14,38 +14,34 @@ import DefineMetrics from '/snippets/_sl-define-metrics.md';
 import ConfigMetric from '/snippets/_sl-configure-metricflow.md';
 import TestQuery from '/snippets/_sl-test-and-query-metrics.md';
 
-This getting started page presents a sample workflow to help you create your first metrics. It uses the [Jaffle shop example project](https://github.com/dbt-labs/jaffle-sl-template) as the project data source and is available for you to use. If you prefer, you can create semantic models and metrics for your own dbt project.
+This getting started page presents a sample workflow to help you create your first metrics in dbt Cloud or the command-line interface (CLI). It uses the [Jaffle shop example project](https://github.com/dbt-labs/jaffle-sl-template) as the project data source and is available for you to use. If you prefer, you can create semantic models and metrics for your own dbt project.
 
-To fully experience the power of a universal dbt Semantic Layer, take the following steps:
+This guide will walk you through how to:
 
-- [Create a semantic model](#create-a-semantic-model) with MetricFlow
-- [Define metrics](#define-metrics) with MetricFlow
-- [Test and query metrics locally](#test-and-query-metrics) with MetricFlow
+- [Create a semantic model](#create-a-semantic-model) using MetricFlow
+- [Define metrics](#define-metrics) using MetricFlow
+- [Test and query metrics locally](#test-and-query-metrics) using MetricFlow
 - [Run a production job](#run-a-production-job) in dbt Cloud
 - [Set up dbt Semantic Layer](#set-up-dbt-semantic-layer) in dbt Cloud
 - [Connect to and query the API](#connect-and-query-api) with dbt Cloud
 
+To fully experience the power of a universal [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl), you'll need a dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) account. 
+
 ## Prerequisites
 
 - Have an understanding of key concepts in [MetricFlow](/docs/build/about-metricflow), which powers the revamped dbt Semantic Layer.
 - Have both your production and development environments running dbt version 1.6 or higher. Refer to [upgrade in dbt Cloud](/docs/dbt-versions/upgrade-core-in-cloud) for more info.
-- Use MetricFlow with Snowflake, BigQuery, Databricks, Postgres (CLI only), or Redshift. (dbt Cloud Postgres support coming soon)
-- A successful run in the environment where your Semantic Layer is configured
-- To query with dbt Cloud:
-  * Have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America (Other regions coming soon)
-  * Set up the [dbt Semantic Layer](/docs/use-dbt-semantic-layer/dbt-sl) and the [Semantic Layer API](/docs/dbt-cloud-apis/sl-api-overview) in the integrated tool to import metric definitions.
-- To query locally:
-  * dbt Core or Developer accounts must manually install the [MetricFlow CLI](/docs/build/metricflow-cli) to test or query their metrics. After installing the package, make sure you run at least one model. <br />
-
+- Use Snowflake, BigQuery, Databricks, Postgres (CLI only), or Redshift. (dbt Cloud Postgres support coming soon)
+-  Create a successful run in the environment where you configure the Semantic Layer. 
+   - **Note:** Semantic Layer currently supports the Deployment environment for querying. (_development querying experience coming soon_)
+- Set up the [Semantic Layer API](/docs/dbt-cloud-apis/sl-api-overview) in the integrated tool to import metric definitions. 
+  - **Note:** dbt Core or Developer accounts can only query data manually using the [MetricFlow CLI](/docs/build/metricflow-cli) and SQL. To dynamically query metrics using external tools, you must have a dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) account with access to the Semantic Layer API.<br />
+- Understand [MetricFlow's](/docs/build/about-metricflow) key concepts, which powers the revamped dbt Semantic Layer.
 
 :::tip 
 New to dbt or metrics? Try our [Jaffle shop example project](https://github.com/dbt-labs/jaffle-sl-template) to help you get started!
 :::
 
-## Install MetricFlow
-
-<InstallMetricFlow />
-
 ## Create a semantic model
 
 <CreateModel />
@@ -64,7 +60,7 @@ New to dbt or metrics? Try our [Jaffle shop example project](https://github.com/
 
 ## Run a production job
 
-Before you begin, you must have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America.
+Before you begin, you must have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America (cloud.getdbt.com login).
 
 Once you’ve defined metrics in your dbt project, you can perform a job run in your dbt Cloud deployment environment to materialize your metrics. Only the deployment environment is supported for the dbt Semantic Layer at this moment. 
 
@@ -82,7 +78,9 @@ import SlSetUp from '/snippets/_new-sl-setup.md';
 
 ## Connect and query API
 
-You can query your metrics in a JDBC-enabled tool or use existing first-class integrations with the dbt Semantic Layer. In order to do so, you must have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America. 
+You can query your metrics in a JDBC-enabled tool or use existing first-class integrations with the dbt Semantic Layer. 
+
+Before you begin, you must have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America (cloud.getdbt.com login). 
 
 - <span>To learn how to use the JDBC API and what tools you can query it with, refer to the  <a href="https://docs.getdbt.com/docs/dbt-cloud-apis/sl-api-overview" target="_self">{frontMatter.meta.api_name}</a></span>.<br />
 

website/docs/docs/use-dbt-semantic-layer/quickstart-sl.md

@@ -27,9 +27,9 @@ MetricFlow is a powerful component within the dbt Semantic Layer that helps user
 
 Use this guide to fully experience the power of a universal dbt Semantic Layer. Here are the following steps you'll take:
 
-- [Create a semantic model](#create-a-semantic-model) with MetricFlow
-- [Define metrics](#define-metrics) with MetricFlow
-- [Test and query metrics locally](#test-and-query-metrics) with MetricFlow 
+- [Create a semantic model](#create-a-semantic-model) in dbt Cloud using MetricFlow
+- [Define metrics](#define-metrics) in dbt Cloud using MetricFlow
+- [Test and query metrics locally](#test-and-query-metrics) using MetricFlow 
 - [Run a production job](#run-a-production-job) in dbt Cloud
 - [Set up dbt Semantic Layer](#setup) in dbt Cloud 
 - [Connect and query API](#connect-and-query-api) with dbt Cloud
@@ -44,10 +44,6 @@ import SetUp from '/snippets/_v2-sl-prerequisites.md';
 New to dbt or metrics? Try our [Jaffle shop example project](https://github.com/dbt-labs/jaffle-sl-template) to help you get started!
 :::
 
-## Install MetricFlow
-
-<InstallMetricFlow />
-
 ## Create a semantic model
 
 <CreateModel />
@@ -62,7 +58,7 @@ New to dbt or metrics? Try our [Jaffle shop example project](https://github.com/
 
 ## Run a production job
 
-Once you’ve defined metrics in your dbt project, you can perform a job run in your deployment environment to materialize your metrics. The deployment environment is only supported for the dbt Semantic Layer at this moment. 
+Once you’ve defined metrics in your dbt project, you can perform a job run in your deployment environment in dbt Cloud to materialize your metrics. The deployment environment is only supported for the dbt Semantic Layer at this moment. 
 
 1. Go to **Deploy** in the navigation header
 2. Select **Jobs** to re-run the job with the most recent code in the deployment environment.
@@ -88,7 +84,9 @@ import SlSetUp from '/snippets/_new-sl-setup.md';
 
 ## Connect and query API
 
-You can query your metrics in a JDBC-enabled tool or use existing first-class integrations with the dbt Semantic Layer. In order to do so, you must have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America. 
+You can query your metrics in a JDBC-enabled tool or use existing first-class integrations with the dbt Semantic Layer. 
+
+Before you begin, you must have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America (cloud.getdbt.com login). 
 
 - <span>To learn how to use the JDBC API and what tools you can query it with, refer to the  <a href="https://docs.getdbt.com/docs/dbt-cloud-apis/sl-api-overview" target="_self">{frontMatter.meta.api_name}</a></span>.<br />
 

website/sidebars.js

@@ -251,6 +251,7 @@ const sidebarSettings = {
           link: { type: "doc", id: "docs/build/build-metrics-intro" },
           collapsed: true,
           items: [
+            "docs/build/sl-getting-started",
             {
               type: "category",
               label: "About MetricFlow",
@@ -262,7 +263,6 @@ const sidebarSettings = {
                 "docs/build/metricflow-cli",
               ]
             },
-            "docs/build/sl-getting-started",
             {
               type: "category",
               label: "Semantic models",

website/snippets/_sl-create-semanticmodel.md

@@ -1,4 +1,4 @@
-The following steps will walk you through setting up semantic models in your dbt project, which consist of [entities](/docs/build/entities), [dimensions](/docs/build/dimensions), and [measures](/docs/build/measures).  
+The following steps will walk you through setting up semantic models, which you can do with the dbt Cloud IDE or the CLI. Semantic models consist of [entities](/docs/build/entities), [dimensions](/docs/build/dimensions), and [measures](/docs/build/measures).  
 
 We highly recommend you read the overview of what a [semantic model](/docs/build/semantic-models) is before getting started. If you're working in the [Jaffle shop example](https://github.com/dbt-labs/jaffle-sl-template), delete the `orders.yml` config or delete the .yml extension so it's ignored during parsing. **We'll be rebuilding it step by step in this example.**
 

website/snippets/_sl-define-metrics.md

@@ -1,4 +1,6 @@
-Now that you've created your first semantic model, it's time to define your first metric! MetricFlow supports different metric types like [simple](/docs/build/simple), [ratio](/docs/build/ratio), [cumulative](/docs/build/cumulative), and [derived](/docs/build/derived). It's recommended that you read the [metrics overview docs](/docs/build/metrics-overview) before getting started.
+Now that you've created your first semantic model, it's time to define your first metric! You can define metrics with the dbt Cloud IDE or CLI.
+
+MetricFlow supports different metric types like [simple](/docs/build/simple), [ratio](/docs/build/ratio), [cumulative](/docs/build/cumulative), and [derived](/docs/build/derived). It's recommended that you read the [metrics overview docs](/docs/build/metrics-overview) before getting started.
 
 1. You can define metrics in the same YAML files as your semantic models or create a new file. If you want to create your metrics in a new file, create another directory called `/models/metrics`. The file structure for metrics can become more complex from here if you need to further organize your metrics, for example, by data source or business line.
 

website/snippets/_sl-install-metricflow.md

@@ -1,7 +1,8 @@
-Before you begin, install the [MetricFlow CLI](/docs/build/metricflow-cli) as an extension of a dbt adapter from PyPI. The MetricFlow CLI is compatible with Python versions 3.8, 3.9, 3.10 and 3.11
+Install the [MetricFlow CLI](/docs/build/metricflow-cli) as an extension of a dbt adapter from PyPI. The MetricFlow CLI is compatible with Python versions 3.8, 3.9, 3.10 and 3.11
 
 Use pip install `metricflow` and your [dbt adapter](/docs/supported-data-platforms):
 
 - Create or activate your virtual environment. `python -m venv venv` or `source your-venv/bin/activate`
 - Run `pip install "dbt-metricflow[your_adapter_name]"`
-  - You must specify `[your_adapter_name]`. For example, run `pip install "dbt-metricflow[snowflake]"` if you use a Snowflake adapter.
+  - You must specify `[your_adapter_name]`. 
+  - For example, run `pip install "dbt-metricflow[snowflake]"` if you use a Snowflake adapter.

website/snippets/_sl-test-and-query-metrics.md

@@ -1,13 +1,23 @@
-This section will explain how you can locally test and query metrics. Before you begin, refer to [MetricFlow CLI](/docs/build/metricflow-cli) for instructions on installing it and a reference for the CLI commands.
+:::important Testing and querying metrics in the dbt Cloud IDE not yet supported
 
-:::important
+For public beta, testing or querying metrics in the dbt Cloud IDE isn't supported yet, however support is coming soon. 
 
-- dbt Cloud Team or Enterprise — For public beta, querying metrics in the dbt Cloud IDE isn't yet supported (Coming soon). You'll still be able to run semantic validation on your metrics in the IDE to ensure they are defined correctly. You can also use the MetricFlow CLI to test and query metrics locally. Alternatively, you can test using SQL client tools like DataGrip, DBeaver, or RazorSQL.
+You can use the **Preview** or **Compile** buttons in the IDE to run semantic validations and make sure your metrics are defined. And you can [dynamically query metrics](#connect-and-query-api) with integrated tools on a dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) plan using the [Semantic Layer API](/docs/dbt-cloud-apis/sl-api-overview).
+
+You can currently only test metrics locally using the MetricFlow CLI. Alternatively, you can test using SQL client tools like DataGrip, DBeaver, or RazorSQL. 
 
-- dbt Core or Developer plan — Users can only test and query metrics manually using the CLI, but won't be able to use the dbt Semantic Layer to dynamically query metrics.
 :::
 
-**Query and commit your metrics using the CLI:**
+This section will explain how you can test and query metrics locally using the MetricFlow CLI (dbt Cloud IDE support coming soon).
+
+Before you begin, you'll need to install the [MetricFlow CLI](/docs/build/metricflow-cli) package and make sure you run at least one model.
+### Install MetricFlow
+
+import InstallMetricFlow from '/snippets/_sl-install-metricflow.md';
+
+<InstallMetricFlow />
+
+### Query and commit your metrics using the CLI
 
 MetricFlow needs a `semantic_manifest.json` in order to build a semantic graph. To generate a semantic_manifest.json artifact run `dbt parse`. This will create the file in your `/target` directory. If you're working from the Jaffle shop example, run `dbt seed && dbt run` before preceding to ensure the data exists in your warehouse.
 

website/snippets/_v2-sl-prerequisites.md

@@ -4,13 +4,12 @@
 To use the Semantic Layer, you must:
 
 - Have a dbt Cloud Team or Enterprise [multi-tenant](/docs/cloud/about-cloud/regions-ip-addresses) deployment, hosted in North America.
-- Have both your production and development environments running dbt version 1.6 or higher.
+- Have both your production and development environments running dbt version 1.6 or higher. Refer to [upgrade in dbt Cloud](/docs/dbt-versions/upgrade-core-in-cloud) for more info.
 - Use Snowflake, BigQuery, Databricks, or Redshift (dbt Cloud Postgres support coming soon).
--  Create a successful run in the environment where you configure the Semantic Layer. <br/>
-  **Note:** Semantic Layer currently supports the Deployment environment. (_development experience coming soon_)
-- Install the [MetricFlow CLI](/docs/build/metricflow-cli). After installing the package, make sure you run at least one model.
-- Set up the [Semantic Layer API](/docs/dbt-cloud-apis/sl-api-overview) in the integrated tool to import metric definitions. <br /> 
-**Note:** Developer accounts can only query data manually using the [MetricFlow CLI](/docs/build/metricflow-cli) and SQL. To dynamically query metrics using external tools, you must have a dbt Cloud Team or Enterprise account with access to the Semantic Layer API.<br />
+-  Create a successful run in the environment where you configure the Semantic Layer. 
+   - **Note:** Semantic Layer currently supports the Deployment environment for querying. (_development querying experience coming soon_) 
+- Set up the [Semantic Layer API](/docs/dbt-cloud-apis/sl-api-overview) in the integrated tool to import metric definitions. 
+  - **Note:** dbt Core or Developer accounts can only query data manually using the [MetricFlow CLI](/docs/build/metricflow-cli) and SQL. To dynamically query metrics using external tools, you must have a dbt Cloud [Team or Enterprise](https://www.getdbt.com/pricing/) account with access to the Semantic Layer API.<br />
 - Understand [MetricFlow's](/docs/build/about-metricflow) key concepts, which powers the revamped dbt Semantic Layer.