add saved queries to various pages

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

@@ -25,7 +25,7 @@ Using MetricFlow with dbt Cloud means you won't need to manage versioning &mdash
 
 <TabItem value="cloudcli" label="dbt Cloud CLI">
 
-- 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.
+- 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 &mdash; your dbt Cloud account will automatically manage the versioning for you.
 
 </TabItem>
@@ -36,21 +36,17 @@ Using MetricFlow with dbt Cloud means you won't need to manage versioning &mdash
 You can create metrics using MetricFlow in the dbt Cloud IDE. However, support for running MetricFlow commands in the IDE will be available soon.
 :::
 
-
-
 </TabItem>
 
 <TabItem value="core" label="dbt Core">
 
+:::tip Use dbt Cloud CLI for semantic layer development
 
-:::info Use dbt Cloud CLI for semantic layer development
-
-Use the dbt Cloud CLI for the experience in defining and querying metrics in your dbt project on dbt Cloud or dbt Core with MetricFlow. 
+You can use the dbt Cloud CLI for the experience in defining and querying metrics in your dbt project.
 
 A benefit to using the dbt Cloud is that you won't need to manage versioning &mdash; your dbt Cloud account will automatically manage the versioning.
 :::
 
-
 You can install [MetricFlow](https://github.com/dbt-labs/metricflow#getting-started) from [PyPI](https://pypi.org/project/dbt-metricflow/). You need to use `pip` to install MetricFlow on Windows or Linux operating systems:
 
 1. Create or activate your virtual environment `python -m venv venv`
@@ -70,16 +66,16 @@ Something to note, MetricFlow `mf` commands return an error if you have a Metafo
 MetricFlow provides the following commands to retrieve metadata and query metrics. 
 
 <Tabs>
-<TabItem value="cloud" label="Commands for dbt Cloud">
+<TabItem value="cloud" label="Commands for dbt Cloud CLI">
 
-Use the `dbt sl` prefix before the command name to execute them in dbt Cloud. For example, to list all metrics, run `dbt sl list metrics`. 
+You can use the `dbt sl` prefix before the command name to execute them in the dbt Cloud CLI. For example, to list all metrics, run `dbt sl list metrics`.
 
 - [`list`](#list) &mdash; Retrieves metadata values.
 - [`list metrics`](#list-metrics) &mdash; Lists metrics with dimensions.
 - [`list dimensions`](#list) &mdash; Lists unique dimensions for metrics.
 - [`list dimension-values`](#list-dimension-values) &mdash; List dimensions with metrics.
 - [`list entities`](#list-entities) &mdash; Lists all unique entities.
-- [`query`](#query) &mdash; Query metrics and dimensions you want to see in the command line interface. Refer to [query examples](#query-examples) to help you get started.
+- [`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.
 
 <!--below commands aren't supported in dbt cloud yet
 - [`validate-configs`](#validate-configs) &mdash; Validates semantic model configurations.
@@ -226,10 +222,11 @@ mf tutorial # In dbt Core
 
 ### Query
 
-Create a new query with MetricFlow, execute that query against the user's data platform, and return the result:
+Create a new query with MetricFlow and execute it against your data platform. The query returns the following result:
 
 ```bash
 dbt sl query --metrics <metric_name> --group-by <dimension_name> # In dbt Cloud 
+dbt sl query --saved-query <name> # In dbt Cloud CLI
 
 mf query --metrics <metric_name> --group-by <dimension_name> # In dbt Core
 
@@ -372,7 +369,6 @@ mf query --metrics order_total --group-by metric_time,is_food_order --limit 10 -
 You can further filter the data set by adding a `where` clause to your query.
 
 **Query**
-
 ```bash
 # In dbt Cloud 
 dbt sl query --metrics order_total --group-by metric_time --where "{{ Dimension('order_id__is_food_order') }} = True" 
@@ -406,7 +402,6 @@ To filter by time, there are dedicated start and end time options. Using these o
 
 **Query**
 ```bash
-
 # In dbt Cloud
 dbt sl query --metrics order_total --group-by metric_time,is_food_order --limit 10 --order -metric_time --where "is_food_order = True" --start-time '2017-08-22' --end-time '2017-08-27' 
 
@@ -429,9 +424,25 @@ mf query --metrics order_total --group-by metric_time,is_food_order --limit 10 -
 
 </TabItem>
 
+<TabItem value="eg6" label=" Saved queries">
 
-</Tabs>
+You can use this for frequently used queries. Replace `<name>` with the name of your [saved query](/docs/build/saved-queries). 
+
+**Query**
+```bash
+dbt sl query --saved-query <name> # In dbt Cloud
+
+mf query --saved-query <name> # In dbt Core
+```
+
+For example, if you use dbt Cloud and have a saved query named `new_customer_orders`, you would run `dbt sl query --saved-query new_customer_orders`.
 
+:::info A note on querying saved queries
+When querying [saved queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for saved queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
+:::
+
+</TabItem>
+</Tabs>
 
 ### Additional query examples
 

website/docs/docs/dbt-cloud-apis/sl-graphql.md

@@ -217,6 +217,31 @@ Dimension {
 DimensionType = [CATEGORICAL, TIME]
 ```
 
+**List saved queries**
+
+  ```graphql
+  {
+  savedQueries(environmentId: 200532) {
+    name
+    description
+    label
+    queryParams {
+      metrics {
+        name
+      }
+      groupBy {
+        name
+        grain
+        datePart
+      }
+      where {
+        whereSqlTemplate
+      }
+    }
+  }
+}
+```
+
 ### Querying
 
 When querying for data, _either_ a `groupBy` _or_ a `metrics` selection is required. 
@@ -576,3 +601,38 @@ mutation {
   }
 }
 ```
+
+**Querying compile SQL with saved queries** 
+
+This query includes the field `savedQuery` and generates the SQL based on a predefined [saved query](/docs/build/saved-queries),rather than dynamically building it from a list of metrics and groupings. You can use this for frequently used queries.
+
+```graphql
+mutation {
+  compileSql(
+    environmentId: 200532
+    savedQuery: "new_customer_orders" # new field
+  ) {
+    queryId
+    sql
+  }
+}
+```
+
+:::info A note on querying saved queries
+When querying [saved queries](/docs/build/saved-queries),you can use parameters such as `where`, `limit`, `order`, `compile`, and so on. However, keep in mind that you can't access `metric` or `group_by` parameters in this context. This is because they are predetermined and fixed parameters for saved queries, and you can't change them at query time. If you would like to query more metrics or dimensions, you can build the query using the standard format.
+:::
+
+**Create query with saved queries** 
+
+This takes the same inputs as the `createQuery` mutation, but includes the field `savedQuery`. You can use this for frequently used queries.
+
+```graphql
+mutation {
+  createQuery(
+    environmentId: 200532
+    savedQuery: "new_customer_orders"  # new field
+  ) {
+    queryId
+  }
+}
+```