diff --git a/output/openapi/elasticsearch-openapi.json b/output/openapi/elasticsearch-openapi.json
index 0eaead9c08..57f459d8b6 100644
--- a/output/openapi/elasticsearch-openapi.json
+++ b/output/openapi/elasticsearch-openapi.json
@@ -17812,7 +17812,7 @@
           "ml data frame"
         ],
         "summary": "Create a data frame analytics job",
-        "description": "This API creates a data frame analytics job that performs an analysis on the\nsource indices and stores the outcome in a destination index.",
+        "description": "This API creates a data frame analytics job that performs an analysis on the\nsource indices and stores the outcome in a destination index.\nBy default, the query used in the source configuration is `{\"match_all\": {}}`.\n\nIf the destination index does not exist, it is created automatically when you start the job.\n\nIf you supply only a subset of the regression or classification parameters, hyperparameter optimization occurs. It determines a value for each of the undefined parameters.",
         "operationId": "ml-put-data-frame-analytics",
         "parameters": [
           {
@@ -18032,7 +18032,7 @@
           "ml anomaly"
         ],
         "summary": "Create a datafeed",
-        "description": "Datafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job.\nYou can associate only one datafeed with each anomaly detection job.\nThe datafeed contains a query that runs at a defined interval (`frequency`).\nIf you are concerned about delayed data, you can add a delay (`query_delay') at each interval.\nWhen Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had\nat the time of creation and runs the query using those same roles. If you provide secondary authorization headers,\nthose credentials are used instead.\nYou must use Kibana, this API, or the create anomaly detection jobs API to create a datafeed. Do not add a datafeed\ndirectly to the `.ml-config` index. Do not give users `write` privileges on the `.ml-config` index.",
+        "description": "Datafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job.\nYou can associate only one datafeed with each anomaly detection job.\nThe datafeed contains a query that runs at a defined interval (`frequency`).\nIf you are concerned about delayed data, you can add a delay (`query_delay') at each interval.\nBy default, the datafeed uses the following query: `{\"match_all\": {\"boost\": 1}}`.\n\nWhen Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had\nat the time of creation and runs the query using those same roles. If you provide secondary authorization headers,\nthose credentials are used instead.\nYou must use Kibana, this API, or the create anomaly detection jobs API to create a datafeed. Do not add a datafeed\ndirectly to the `.ml-config` index. Do not give users `write` privileges on the `.ml-config` index.",
         "operationId": "ml-put-datafeed",
         "parameters": [
           {
@@ -18653,7 +18653,7 @@
           "ml anomaly"
         ],
         "summary": "Create an anomaly detection job",
-        "description": "If you include a `datafeed_config`, you must have read index privileges on the source index.",
+        "description": "If you include a `datafeed_config`, you must have read index privileges on the source index.\nIf you include a `datafeed_config` but do not provide a query, the datafeed uses `{\"match_all\": {\"boost\": 1}}`.",
         "operationId": "ml-put-job",
         "parameters": [
           {
@@ -43755,6 +43755,7 @@
         "externalDocs": {
           "url": "https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl.html"
         },
+        "description": "An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.",
         "type": "object",
         "properties": {
           "bool": {
diff --git a/output/openapi/elasticsearch-serverless-openapi.json b/output/openapi/elasticsearch-serverless-openapi.json
index 1551b2e1a4..521381ee5c 100644
--- a/output/openapi/elasticsearch-serverless-openapi.json
+++ b/output/openapi/elasticsearch-serverless-openapi.json
@@ -10292,7 +10292,7 @@
           "ml data frame"
         ],
         "summary": "Create a data frame analytics job",
-        "description": "This API creates a data frame analytics job that performs an analysis on the\nsource indices and stores the outcome in a destination index.",
+        "description": "This API creates a data frame analytics job that performs an analysis on the\nsource indices and stores the outcome in a destination index.\nBy default, the query used in the source configuration is `{\"match_all\": {}}`.\n\nIf the destination index does not exist, it is created automatically when you start the job.\n\nIf you supply only a subset of the regression or classification parameters, hyperparameter optimization occurs. It determines a value for each of the undefined parameters.",
         "operationId": "ml-put-data-frame-analytics",
         "parameters": [
           {
@@ -10512,7 +10512,7 @@
           "ml anomaly"
         ],
         "summary": "Create a datafeed",
-        "description": "Datafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job.\nYou can associate only one datafeed with each anomaly detection job.\nThe datafeed contains a query that runs at a defined interval (`frequency`).\nIf you are concerned about delayed data, you can add a delay (`query_delay') at each interval.\nWhen Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had\nat the time of creation and runs the query using those same roles. If you provide secondary authorization headers,\nthose credentials are used instead.\nYou must use Kibana, this API, or the create anomaly detection jobs API to create a datafeed. Do not add a datafeed\ndirectly to the `.ml-config` index. Do not give users `write` privileges on the `.ml-config` index.",
+        "description": "Datafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job.\nYou can associate only one datafeed with each anomaly detection job.\nThe datafeed contains a query that runs at a defined interval (`frequency`).\nIf you are concerned about delayed data, you can add a delay (`query_delay') at each interval.\nBy default, the datafeed uses the following query: `{\"match_all\": {\"boost\": 1}}`.\n\nWhen Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had\nat the time of creation and runs the query using those same roles. If you provide secondary authorization headers,\nthose credentials are used instead.\nYou must use Kibana, this API, or the create anomaly detection jobs API to create a datafeed. Do not add a datafeed\ndirectly to the `.ml-config` index. Do not give users `write` privileges on the `.ml-config` index.",
         "operationId": "ml-put-datafeed",
         "parameters": [
           {
@@ -10922,7 +10922,7 @@
           "ml anomaly"
         ],
         "summary": "Create an anomaly detection job",
-        "description": "If you include a `datafeed_config`, you must have read index privileges on the source index.",
+        "description": "If you include a `datafeed_config`, you must have read index privileges on the source index.\nIf you include a `datafeed_config` but do not provide a query, the datafeed uses `{\"match_all\": {\"boost\": 1}}`.",
         "operationId": "ml-put-job",
         "parameters": [
           {
@@ -25703,6 +25703,7 @@
         "externalDocs": {
           "url": "https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl.html"
         },
+        "description": "An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.",
         "type": "object",
         "properties": {
           "bool": {
diff --git a/output/schema/schema.json b/output/schema/schema.json
index ae3e1981dc..013cdac4c8 100644
--- a/output/schema/schema.json
+++ b/output/schema/schema.json
@@ -12076,7 +12076,7 @@
           "stability": "stable"
         }
       },
-      "description": "Create a data frame analytics job.\nThis API creates a data frame analytics job that performs an analysis on the\nsource indices and stores the outcome in a destination index.",
+      "description": "Create a data frame analytics job.\nThis API creates a data frame analytics job that performs an analysis on the\nsource indices and stores the outcome in a destination index.\nBy default, the query used in the source configuration is `{\"match_all\": {}}`.\n\nIf the destination index does not exist, it is created automatically when you start the job.\n\nIf you supply only a subset of the regression or classification parameters, hyperparameter optimization occurs. It determines a value for each of the undefined parameters.",
       "docId": "put-dfanalytics",
       "docTag": "ml data frame",
       "docUrl": "https://www.elastic.co/guide/en/elasticsearch/reference/{branch}/put-dfanalytics.html",
@@ -12128,7 +12128,7 @@
           "stability": "stable"
         }
       },
-      "description": "Create a datafeed.\nDatafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job.\nYou can associate only one datafeed with each anomaly detection job.\nThe datafeed contains a query that runs at a defined interval (`frequency`).\nIf you are concerned about delayed data, you can add a delay (`query_delay') at each interval.\nWhen Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had\nat the time of creation and runs the query using those same roles. If you provide secondary authorization headers,\nthose credentials are used instead.\nYou must use Kibana, this API, or the create anomaly detection jobs API to create a datafeed. Do not add a datafeed\ndirectly to the `.ml-config` index. Do not give users `write` privileges on the `.ml-config` index.",
+      "description": "Create a datafeed.\nDatafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job.\nYou can associate only one datafeed with each anomaly detection job.\nThe datafeed contains a query that runs at a defined interval (`frequency`).\nIf you are concerned about delayed data, you can add a delay (`query_delay') at each interval.\nBy default, the datafeed uses the following query: `{\"match_all\": {\"boost\": 1}}`.\n\nWhen Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had\nat the time of creation and runs the query using those same roles. If you provide secondary authorization headers,\nthose credentials are used instead.\nYou must use Kibana, this API, or the create anomaly detection jobs API to create a datafeed. Do not add a datafeed\ndirectly to the `.ml-config` index. Do not give users `write` privileges on the `.ml-config` index.",
       "docTag": "ml anomaly",
       "docUrl": "https://www.elastic.co/guide/en/elasticsearch/reference/current/ml-put-datafeed.html",
       "name": "ml.put_datafeed",
@@ -12219,7 +12219,7 @@
           "stability": "stable"
         }
       },
-      "description": "Create an anomaly detection job.\nIf you include a `datafeed_config`, you must have read index privileges on the source index.",
+      "description": "Create an anomaly detection job.\nIf you include a `datafeed_config`, you must have read index privileges on the source index.\nIf you include a `datafeed_config` but do not provide a query, the datafeed uses `{\"match_all\": {\"boost\": 1}}`.",
       "docTag": "ml anomaly",
       "docUrl": "https://www.elastic.co/guide/en/elasticsearch/reference/current/ml-put-job.html",
       "name": "ml.put_job",
@@ -79292,7 +79292,7 @@
         "name": "CombinedFieldsOperator",
         "namespace": "_types.query_dsl"
       },
-      "specLocation": "_types/query_dsl/abstractions.ts#L512-L515"
+      "specLocation": "_types/query_dsl/abstractions.ts#L513-L516"
     },
     {
       "kind": "interface",
@@ -79388,7 +79388,7 @@
           }
         }
       ],
-      "specLocation": "_types/query_dsl/abstractions.ts#L465-L499"
+      "specLocation": "_types/query_dsl/abstractions.ts#L466-L500"
     },
     {
       "kind": "enum",
@@ -79406,7 +79406,7 @@
         "name": "CombinedFieldsZeroTerms",
         "namespace": "_types.query_dsl"
       },
-      "specLocation": "_types/query_dsl/abstractions.ts#L517-L526"
+      "specLocation": "_types/query_dsl/abstractions.ts#L518-L527"
     },
     {
       "kind": "interface",
@@ -80070,7 +80070,7 @@
         }
       ],
       "shortcutProperty": "field",
-      "specLocation": "_types/query_dsl/abstractions.ts#L528-L542"
+      "specLocation": "_types/query_dsl/abstractions.ts#L529-L543"
     },
     {
       "kind": "interface",
@@ -80128,7 +80128,7 @@
           }
         }
       ],
-      "specLocation": "_types/query_dsl/abstractions.ts#L429-L446"
+      "specLocation": "_types/query_dsl/abstractions.ts#L430-L447"
     },
     {
       "kind": "enum",
@@ -83785,10 +83785,11 @@
           }
         }
       ],
-      "specLocation": "_types/query_dsl/abstractions.ts#L452-L463"
+      "specLocation": "_types/query_dsl/abstractions.ts#L453-L464"
     },
     {
       "kind": "interface",
+      "description": "An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.",
       "extDocId": "query-dsl",
       "extDocUrl": "https://www.elastic.co/guide/en/elasticsearch/reference/{branch}/query-dsl.html",
       "name": {
@@ -84849,7 +84850,7 @@
           }
         }
       ],
-      "specLocation": "_types/query_dsl/abstractions.ts#L102-L427",
+      "specLocation": "_types/query_dsl/abstractions.ts#L102-L428",
       "variants": {
         "kind": "container",
         "nonExhaustive": true
@@ -87731,7 +87732,7 @@
           }
         }
       ],
-      "specLocation": "_types/query_dsl/abstractions.ts#L501-L510"
+      "specLocation": "_types/query_dsl/abstractions.ts#L502-L511"
     },
     {
       "kind": "enum",
@@ -171516,7 +171517,7 @@
           }
         ]
       },
-      "description": "Create a data frame analytics job.\nThis API creates a data frame analytics job that performs an analysis on the\nsource indices and stores the outcome in a destination index.",
+      "description": "Create a data frame analytics job.\nThis API creates a data frame analytics job that performs an analysis on the\nsource indices and stores the outcome in a destination index.\nBy default, the query used in the source configuration is `{\"match_all\": {}}`.\n\nIf the destination index does not exist, it is created automatically when you start the job.\n\nIf you supply only a subset of the regression or classification parameters, hyperparameter optimization occurs. It determines a value for each of the undefined parameters.",
       "inherits": {
         "type": {
           "name": "RequestBase",
@@ -171542,7 +171543,7 @@
         }
       ],
       "query": [],
-      "specLocation": "ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts#L30-L144"
+      "specLocation": "ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts#L30-L149"
     },
     {
       "kind": "response",
@@ -171922,7 +171923,7 @@
           }
         ]
       },
-      "description": "Create a datafeed.\nDatafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job.\nYou can associate only one datafeed with each anomaly detection job.\nThe datafeed contains a query that runs at a defined interval (`frequency`).\nIf you are concerned about delayed data, you can add a delay (`query_delay') at each interval.\nWhen Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had\nat the time of creation and runs the query using those same roles. If you provide secondary authorization headers,\nthose credentials are used instead.\nYou must use Kibana, this API, or the create anomaly detection jobs API to create a datafeed. Do not add a datafeed\ndirectly to the `.ml-config` index. Do not give users `write` privileges on the `.ml-config` index.",
+      "description": "Create a datafeed.\nDatafeeds retrieve data from Elasticsearch for analysis by an anomaly detection job.\nYou can associate only one datafeed with each anomaly detection job.\nThe datafeed contains a query that runs at a defined interval (`frequency`).\nIf you are concerned about delayed data, you can add a delay (`query_delay') at each interval.\nBy default, the datafeed uses the following query: `{\"match_all\": {\"boost\": 1}}`.\n\nWhen Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had\nat the time of creation and runs the query using those same roles. If you provide secondary authorization headers,\nthose credentials are used instead.\nYou must use Kibana, this API, or the create anomaly detection jobs API to create a datafeed. Do not add a datafeed\ndirectly to the `.ml-config` index. Do not give users `write` privileges on the `.ml-config` index.",
       "inherits": {
         "type": {
           "name": "RequestBase",
@@ -172005,7 +172006,7 @@
           }
         }
       ],
-      "specLocation": "ml/put_datafeed/MlPutDatafeedRequest.ts#L37-L175"
+      "specLocation": "ml/put_datafeed/MlPutDatafeedRequest.ts#L37-L177"
     },
     {
       "kind": "response",
@@ -172533,7 +172534,7 @@
           }
         ]
       },
-      "description": "Create an anomaly detection job.\nIf you include a `datafeed_config`, you must have read index privileges on the source index.",
+      "description": "Create an anomaly detection job.\nIf you include a `datafeed_config`, you must have read index privileges on the source index.\nIf you include a `datafeed_config` but do not provide a query, the datafeed uses `{\"match_all\": {\"boost\": 1}}`.",
       "inherits": {
         "type": {
           "name": "RequestBase",
@@ -172616,7 +172617,7 @@
           }
         }
       ],
-      "specLocation": "ml/put_job/MlPutJobRequest.ts#L30-L148"
+      "specLocation": "ml/put_job/MlPutJobRequest.ts#L30-L149"
     },
     {
       "kind": "response",
diff --git a/specification/_types/query_dsl/abstractions.ts b/specification/_types/query_dsl/abstractions.ts
index f9eafdac74..6ecdb11e9c 100644
--- a/specification/_types/query_dsl/abstractions.ts
+++ b/specification/_types/query_dsl/abstractions.ts
@@ -100,6 +100,7 @@ import { TextExpansionQuery } from './TextExpansionQuery'
 import { WeightedTokensQuery } from './WeightedTokensQuery'
 
 /**
+ * An Elasticsearch Query DSL (Domain Specific Language) object that defines a query.
  * @variants container
  * @non_exhaustive
  * @ext_doc_id query-dsl
diff --git a/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts b/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts
index cd36199e18..ea7446a30b 100644
--- a/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts
+++ b/specification/ml/put_data_frame_analytics/MlPutDataFrameAnalyticsRequest.ts
@@ -31,6 +31,11 @@ import { integer } from '@_types/Numeric'
  * Create a data frame analytics job.
  * This API creates a data frame analytics job that performs an analysis on the
  * source indices and stores the outcome in a destination index.
+ * By default, the query used in the source configuration is `{"match_all": {}}`.
+ *
+ * If the destination index does not exist, it is created automatically when you start the job.
+ *
+ * If you supply only a subset of the regression or classification parameters, hyperparameter optimization occurs. It determines a value for each of the undefined parameters.
  * @rest_spec_name ml.put_data_frame_analytics
  * @availability stack since=7.3.0 stability=stable
  * @availability serverless stability=stable visibility=public
diff --git a/specification/ml/put_datafeed/MlPutDatafeedRequest.ts b/specification/ml/put_datafeed/MlPutDatafeedRequest.ts
index 6a317c9640..d109b14fb9 100644
--- a/specification/ml/put_datafeed/MlPutDatafeedRequest.ts
+++ b/specification/ml/put_datafeed/MlPutDatafeedRequest.ts
@@ -40,6 +40,8 @@ import { Duration } from '@_types/Time'
  * You can associate only one datafeed with each anomaly detection job.
  * The datafeed contains a query that runs at a defined interval (`frequency`).
  * If you are concerned about delayed data, you can add a delay (`query_delay') at each interval.
+ * By default, the datafeed uses the following query: `{"match_all": {"boost": 1}}`.
+ *
  * When Elasticsearch security features are enabled, your datafeed remembers which roles the user who created it had
  * at the time of creation and runs the query using those same roles. If you provide secondary authorization headers,
  * those credentials are used instead.
diff --git a/specification/ml/put_job/MlPutJobRequest.ts b/specification/ml/put_job/MlPutJobRequest.ts
index c15eb15c9c..854cc2d5f6 100644
--- a/specification/ml/put_job/MlPutJobRequest.ts
+++ b/specification/ml/put_job/MlPutJobRequest.ts
@@ -30,6 +30,7 @@ import { Duration } from '@_types/Time'
 /**
  * Create an anomaly detection job.
  * If you include a `datafeed_config`, you must have read index privileges on the source index.
+ * If you include a `datafeed_config` but do not provide a query, the datafeed uses `{"match_all": {"boost": 1}}`.
  * @rest_spec_name ml.put_job
  * @availability stack since=5.4.0 stability=stable
  * @availability serverless stability=stable visibility=public