add release note to singular test enhancment (#6227)

website/docs/docs/dbt-versions/release-notes.md

@@ -20,6 +20,7 @@ Release notes are grouped by month for both multi-tenant and virtual private clo
 
 ## October 2024
 
+- **Enhancement**: You can now add a description to a singular data test in dbt Cloud Versionless. Use the [`description` property](/reference/resource-properties/description) to document [singular data tests](/docs/build/data-tests#singular-data-tests). You can also use [docs block](/docs/build/documentation#using-docs-blocks) to capture your test description. The enhancement will be included in upcoming dbt Core 1.9 release.
 - **New**: Introducing the [microbatch incremental model strategy](/docs/build/incremental-microbatch) (beta), available in dbt Cloud Versionless and will soon be supported in dbt Core 1.9. The microbatch strategy allows for efficient, batch-based processing of large time-series datasets for improved performance and resiliency, especially when you're working with data that changes over time (like new records being added daily). To enable this feature in dbt Cloud, set the `DBT_EXPERIMENTAL_MICROBATCH` environment variable to `true` in your project.
 - **New**: The dbt Semantic Layer supports custom calendar configurations in MetricFlow, available in [Preview](/docs/dbt-versions/product-lifecycles#dbt-cloud). Custom calendar configurations allow you to query data using non-standard time periods like `fiscal_year` or `retail_month`. Refer to [custom calendar](/docs/build/metricflow-time-spine#custom-calendar) to learn how to define these custom granularities in your MetricFlow timespine YAML configuration.
 - **New**: In dbt Cloud Versionless, [Snapshots](/docs/build/snapshots) have been updated to use YAML configuration files instead of SQL snapshot blocks. This new feature simplifies snapshot management and improves performance, and will soon be released in dbt Core 1.9.
@@ -29,8 +30,7 @@ Release notes are grouped by month for both multi-tenant and virtual private clo
 - **Behavior change:** Set the [`skip_nodes_if_on_run_start_fails`](/reference/global-configs/behavior-changes#failures-in-on-run-start-hooks) flag to `True` to skip all selected resources from running if there is a failure on an `on-run-start` hook.
 - **Enhancement**: In dbt Cloud Versionless, snapshots defined in SQL files can now use `config` defined in `schema.yml` YAML files. This update resolves the previous limitation that required snapshot properties to be defined exclusively in `dbt_project.yml` and/or a `config()` block within the SQL file. This will also be released in dbt Core 1.9.
 - **New**: In dbt Cloud Versionless, the `snapshot_meta_column_names` config allows for customizing the snapshot metadata columns. This feature allows an organization to align these automatically-generated column names with their conventions, and will be included in the upcoming dbt Core 1.9 release.
-- **Enhancement**: dbt Cloud versionless began inferring a model's `primary_key` based on configured data tests and/or constraints within `manifest.json`. The inferred `primary_key` is visible in dbt Explorer and utilized by the dbt Cloud [compare changes](/docs/deploy/run-visibility#compare-tab) feature. This will also be released in dbt Core 1.9.
-Read about the [order dbt infers columns can be used as primary key of a model](https://github.com/dbt-labs/dbt-core/blob/7940ad5c7858ff11ef100260a372f2f06a86e71f/core/dbt/contracts/graph/nodes.py#L534-L541). 
+- **Enhancement**: dbt Cloud versionless began inferring a model's `primary_key` based on configured data tests and/or constraints within `manifest.json`. The inferred `primary_key` is visible in dbt Explorer and utilized by the dbt Cloud [compare changes](/docs/deploy/run-visibility#compare-tab) feature. This will also be released in dbt Core 1.9. Read about the [order dbt infers columns can be used as primary key of a model](https://github.com/dbt-labs/dbt-core/blob/7940ad5c7858ff11ef100260a372f2f06a86e71f/core/dbt/contracts/graph/nodes.py#L534-L541). 
 - **New:** dbt Explorer now includes trust signal icons, which is currently available as a [Preview](/docs/dbt-versions/product-lifecycles#dbt-cloud). Trust signals offer a quick, at-a-glance view of data health when browsing your dbt models in Explorer. These icons indicate whether a model is **Healthy**, **Caution**, **Degraded**, or **Unknown**. For accurate health data, ensure the resource is up-to-date and has had a recent job run. Refer to [Trust signals](/docs/collaborate/explore-projects#trust-signals-for-resources) for more information. 
 - **New:** Auto exposures are now available in Preview in dbt Cloud. Auto-exposures helps users understand how their models are used in downstream analytics tools to inform investments and reduce incidents. It imports and auto-generates exposures based on Tableau dashboards, with user-defined curation. To learn more, refer to [Auto exposures](/docs/collaborate/auto-exposures).