diff --git a/output/openapi/elasticsearch-openapi.json b/output/openapi/elasticsearch-openapi.json
index d69e0d4ac1..aca653bbc4 100644
--- a/output/openapi/elasticsearch-openapi.json
+++ b/output/openapi/elasticsearch-openapi.json
@@ -22157,7 +22157,7 @@
                 "MlEvaluateDataFrameRequestExample4": {
                   "summary": "Regression example 1",
                   "description": "Run `POST _ml/data_frame/_evaluate` to evaluate the testing error of a regression job for an annotated index. The term query in the body limits evaluation to be performed on the test split only. The `actual_field` contains the ground truth for house prices. The `predicted_field` contains the house price calculated by the regression analysis.\n",
-                  "value": "{\n  \"index\": \"house_price_predictions\",\n  \"query\": {\n    \"bool\": {\n      \"filter\": [\n        {\n          \"term\": {\n            \"ml.is_training\": false\n          }\n        }\n      ]\n    },\n    \"evaluation\": {\n      \"regression\": {\n        \"actual_field\": \"price\",\n        \"predicted_field\": \"ml.price_prediction\",\n        \"metrics\": {\n          \"r_squared\": {},\n          \"mse\": {},\n          \"msle\": {\n            \"offset\": 10\n          },\n          \"huber\": {\n            \"delta\": 1.5\n          }\n        }\n      }\n    }\n  }\n}"
+                  "value": "{\n  \"index\": \"house_price_predictions\",\n  \"query\": {\n    \"bool\": {\n      \"filter\": [\n        {\n          \"term\": {\n            \"ml.is_training\": false\n          }\n        }\n      ]\n    }\n  },\n  \"evaluation\": {\n    \"regression\": {\n      \"actual_field\": \"price\",\n      \"predicted_field\": \"ml.price_prediction\",\n      \"metrics\": {\n        \"r_squared\": {},\n        \"mse\": {},\n        \"msle\": {\n          \"offset\": 10\n        },\n        \"huber\": {\n          \"delta\": 1.5\n        }\n      }\n    }\n  }\n}"
                 },
                 "MlEvaluateDataFrameRequestExample5": {
                   "summary": "Regression example 2",
@@ -113741,7 +113741,7 @@
               "MultiTermVectorsRequestExample2": {
                 "summary": "Simplified syntax",
                 "description": "Run `POST /my-index-000001/_mtermvectors`. If all requested documents are in same index and the parameters are the same, you can use a simplified syntax.\n",
-                "value": "{\n  \"ids\": [ \"1\", \"2\" ],\n  \"parameters\": {\n    \"fields\": [\n      \"message\"\n    ],\n    \"term_statistics\": true\n  }\n}"
+                "value": "{\n  \"ids\": [ \"1\", \"2\" ],\n  \"fields\": [\n    \"message\"\n  ],\n  \"term_statistics\": true\n}"
               },
               "MultiTermVectorsRequestExample3": {
                 "summary": "Artificial documents",
diff --git a/output/openapi/elasticsearch-serverless-openapi.json b/output/openapi/elasticsearch-serverless-openapi.json
index 3d39b3ba55..3c5a4915ca 100644
--- a/output/openapi/elasticsearch-serverless-openapi.json
+++ b/output/openapi/elasticsearch-serverless-openapi.json
@@ -12561,7 +12561,7 @@
                 "MlEvaluateDataFrameRequestExample4": {
                   "summary": "Regression example 1",
                   "description": "Run `POST _ml/data_frame/_evaluate` to evaluate the testing error of a regression job for an annotated index. The term query in the body limits evaluation to be performed on the test split only. The `actual_field` contains the ground truth for house prices. The `predicted_field` contains the house price calculated by the regression analysis.\n",
-                  "value": "{\n  \"index\": \"house_price_predictions\",\n  \"query\": {\n    \"bool\": {\n      \"filter\": [\n        {\n          \"term\": {\n            \"ml.is_training\": false\n          }\n        }\n      ]\n    },\n    \"evaluation\": {\n      \"regression\": {\n        \"actual_field\": \"price\",\n        \"predicted_field\": \"ml.price_prediction\",\n        \"metrics\": {\n          \"r_squared\": {},\n          \"mse\": {},\n          \"msle\": {\n            \"offset\": 10\n          },\n          \"huber\": {\n            \"delta\": 1.5\n          }\n        }\n      }\n    }\n  }\n}"
+                  "value": "{\n  \"index\": \"house_price_predictions\",\n  \"query\": {\n    \"bool\": {\n      \"filter\": [\n        {\n          \"term\": {\n            \"ml.is_training\": false\n          }\n        }\n      ]\n    }\n  },\n  \"evaluation\": {\n    \"regression\": {\n      \"actual_field\": \"price\",\n      \"predicted_field\": \"ml.price_prediction\",\n      \"metrics\": {\n        \"r_squared\": {},\n        \"mse\": {},\n        \"msle\": {\n          \"offset\": 10\n        },\n        \"huber\": {\n          \"delta\": 1.5\n        }\n      }\n    }\n  }\n}"
                 },
                 "MlEvaluateDataFrameRequestExample5": {
                   "summary": "Regression example 2",
@@ -66523,7 +66523,7 @@
               "MultiTermVectorsRequestExample2": {
                 "summary": "Simplified syntax",
                 "description": "Run `POST /my-index-000001/_mtermvectors`. If all requested documents are in same index and the parameters are the same, you can use a simplified syntax.\n",
-                "value": "{\n  \"ids\": [ \"1\", \"2\" ],\n  \"parameters\": {\n    \"fields\": [\n      \"message\"\n    ],\n    \"term_statistics\": true\n  }\n}"
+                "value": "{\n  \"ids\": [ \"1\", \"2\" ],\n  \"fields\": [\n    \"message\"\n  ],\n  \"term_statistics\": true\n}"
               },
               "MultiTermVectorsRequestExample3": {
                 "summary": "Artificial documents",
diff --git a/output/schema/schema-serverless.json b/output/schema/schema-serverless.json
index b9e6fe4fa8..9befc31083 100644
--- a/output/schema/schema-serverless.json
+++ b/output/schema/schema-serverless.json
@@ -29558,7 +29558,7 @@
         "MlEvaluateDataFrameRequestExample4": {
           "description": "Run `POST _ml/data_frame/_evaluate` to evaluate the testing error of a regression job for an annotated index. The term query in the body limits evaluation to be performed on the test split only. The `actual_field` contains the ground truth for house prices. The `predicted_field` contains the house price calculated by the regression analysis.\n",
           "summary": "Regression example 1",
-          "value": "{\n  \"index\": \"house_price_predictions\",\n  \"query\": {\n    \"bool\": {\n      \"filter\": [\n        {\n          \"term\": {\n            \"ml.is_training\": false\n          }\n        }\n      ]\n    },\n    \"evaluation\": {\n      \"regression\": {\n        \"actual_field\": \"price\",\n        \"predicted_field\": \"ml.price_prediction\",\n        \"metrics\": {\n          \"r_squared\": {},\n          \"mse\": {},\n          \"msle\": {\n            \"offset\": 10\n          },\n          \"huber\": {\n            \"delta\": 1.5\n          }\n        }\n      }\n    }\n  }\n}"
+          "value": "{\n  \"index\": \"house_price_predictions\",\n  \"query\": {\n    \"bool\": {\n      \"filter\": [\n        {\n          \"term\": {\n            \"ml.is_training\": false\n          }\n        }\n      ]\n    }\n  },\n  \"evaluation\": {\n    \"regression\": {\n      \"actual_field\": \"price\",\n      \"predicted_field\": \"ml.price_prediction\",\n      \"metrics\": {\n        \"r_squared\": {},\n        \"mse\": {},\n        \"msle\": {\n          \"offset\": 10\n        },\n        \"huber\": {\n          \"delta\": 1.5\n        }\n      }\n    }\n  }\n}"
         },
         "MlEvaluateDataFrameRequestExample5": {
           "description": "Run `POST _ml/data_frame/_evaluate` to evaluate the training error of a regression job for an annotated index. The term query in the body limits evaluation to be performed on the training split only. The `actual_field` contains the ground truth for house prices. The `predicted_field` contains the house price calculated by the regression analysis.\n",
@@ -36876,7 +36876,7 @@
         "MultiTermVectorsRequestExample2": {
           "description": "Run `POST /my-index-000001/_mtermvectors`. If all requested documents are in same index and the parameters are the same, you can use a simplified syntax.\n",
           "summary": "Simplified syntax",
-          "value": "{\n  \"ids\": [ \"1\", \"2\" ],\n  \"parameters\": {\n    \"fields\": [\n      \"message\"\n    ],\n    \"term_statistics\": true\n  }\n}"
+          "value": "{\n  \"ids\": [ \"1\", \"2\" ],\n  \"fields\": [\n    \"message\"\n  ],\n  \"term_statistics\": true\n}"
         },
         "MultiTermVectorsRequestExample3": {
           "description": "Run `POST /_mtermvectors` to generate term vectors for artificial documents provided in the body of the request. The mapping used is determined by the specified `_index`.\n",
@@ -45854,6 +45854,119 @@
                 }
               }
             }
+          },
+          {
+            "description": "A list of fields to include in the statistics.\nIt is used as the default list unless a specific field list is provided in the `completion_fields` or `fielddata_fields` parameters.",
+            "name": "fields",
+            "required": false,
+            "type": {
+              "kind": "instance_of",
+              "type": {
+                "name": "Fields",
+                "namespace": "_types"
+              }
+            }
+          },
+          {
+            "description": "If `true`, the response includes:\n\n* The document count (how many documents contain this field).\n* The sum of document frequencies (the sum of document frequencies for all terms in this field).\n* The sum of total term frequencies (the sum of total term frequencies of each term in this field).",
+            "name": "field_statistics",
+            "required": false,
+            "serverDefault": true,
+            "type": {
+              "kind": "instance_of",
+              "type": {
+                "name": "boolean",
+                "namespace": "_builtins"
+              }
+            }
+          },
+          {
+            "description": "If `true`, the response includes term offsets.",
+            "name": "offsets",
+            "required": false,
+            "serverDefault": true,
+            "type": {
+              "kind": "instance_of",
+              "type": {
+                "name": "boolean",
+                "namespace": "_builtins"
+              }
+            }
+          },
+          {
+            "description": "If `true`, the response includes term payloads.",
+            "name": "payloads",
+            "required": false,
+            "serverDefault": true,
+            "type": {
+              "kind": "instance_of",
+              "type": {
+                "name": "boolean",
+                "namespace": "_builtins"
+              }
+            }
+          },
+          {
+            "description": "If `true`, the response includes term positions.",
+            "name": "positions",
+            "required": false,
+            "serverDefault": true,
+            "type": {
+              "kind": "instance_of",
+              "type": {
+                "name": "boolean",
+                "namespace": "_builtins"
+              }
+            }
+          },
+          {
+            "description": "If `true`, the response includes:\n\n* The total term frequency (how often a term occurs in all documents).\n* The document frequency (the number of documents containing the current term).\n\nBy default these values are not returned since term statistics can have a serious performance impact.",
+            "name": "term_statistics",
+            "required": false,
+            "serverDefault": false,
+            "type": {
+              "kind": "instance_of",
+              "type": {
+                "name": "boolean",
+                "namespace": "_builtins"
+              }
+            }
+          },
+          {
+            "description": "A custom value that is used to route operations to a specific shard.",
+            "name": "routing",
+            "required": false,
+            "type": {
+              "kind": "instance_of",
+              "type": {
+                "name": "Routing",
+                "namespace": "_types"
+              }
+            }
+          },
+          {
+            "description": "If `true`, returns the document version as part of a hit.",
+            "name": "version",
+            "required": false,
+            "type": {
+              "kind": "instance_of",
+              "type": {
+                "name": "VersionNumber",
+                "namespace": "_types"
+              }
+            }
+          },
+          {
+            "description": "The version type.",
+            "name": "version_type",
+            "required": false,
+            "type": {
+              "kind": "instance_of",
+              "type": {
+                "name": "VersionType",
+                "namespace": "_types"
+              }
+            }
           }
         ]
       },
@@ -46070,7 +46183,7 @@
           }
         }
       ],
-      "specLocation": "_global/termvectors/TermVectorsRequest.ts#L33-L187"
+      "specLocation": "_global/termvectors/TermVectorsRequest.ts#L33-L239"
     },
     {
       "body": {
diff --git a/output/schema/schema.json b/output/schema/schema.json
index 7edba55f2e..898087a1b3 100644
--- a/output/schema/schema.json
+++ b/output/schema/schema.json
@@ -31895,7 +31895,7 @@
         "MultiTermVectorsRequestExample2": {
           "description": "Run `POST /my-index-000001/_mtermvectors`. If all requested documents are in same index and the parameters are the same, you can use a simplified syntax.\n",
           "summary": "Simplified syntax",
-          "value": "{\n  \"ids\": [ \"1\", \"2\" ],\n  \"parameters\": {\n    \"fields\": [\n      \"message\"\n    ],\n    \"term_statistics\": true\n  }\n}"
+          "value": "{\n  \"ids\": [ \"1\", \"2\" ],\n  \"fields\": [\n    \"message\"\n  ],\n  \"term_statistics\": true\n}"
         },
         "MultiTermVectorsRequestExample3": {
           "description": "Run `POST /_mtermvectors` to generate term vectors for artificial documents provided in the body of the request. The mapping used is determined by the specified `_index`.\n",
@@ -174320,7 +174320,7 @@
         "MlEvaluateDataFrameRequestExample4": {
           "description": "Run `POST _ml/data_frame/_evaluate` to evaluate the testing error of a regression job for an annotated index. The term query in the body limits evaluation to be performed on the test split only. The `actual_field` contains the ground truth for house prices. The `predicted_field` contains the house price calculated by the regression analysis.\n",
           "summary": "Regression example 1",
-          "value": "{\n  \"index\": \"house_price_predictions\",\n  \"query\": {\n    \"bool\": {\n      \"filter\": [\n        {\n          \"term\": {\n            \"ml.is_training\": false\n          }\n        }\n      ]\n    },\n    \"evaluation\": {\n      \"regression\": {\n        \"actual_field\": \"price\",\n        \"predicted_field\": \"ml.price_prediction\",\n        \"metrics\": {\n          \"r_squared\": {},\n          \"mse\": {},\n          \"msle\": {\n            \"offset\": 10\n          },\n          \"huber\": {\n            \"delta\": 1.5\n          }\n        }\n      }\n    }\n  }\n}"
+          "value": "{\n  \"index\": \"house_price_predictions\",\n  \"query\": {\n    \"bool\": {\n      \"filter\": [\n        {\n          \"term\": {\n            \"ml.is_training\": false\n          }\n        }\n      ]\n    }\n  },\n  \"evaluation\": {\n    \"regression\": {\n      \"actual_field\": \"price\",\n      \"predicted_field\": \"ml.price_prediction\",\n      \"metrics\": {\n        \"r_squared\": {},\n        \"mse\": {},\n        \"msle\": {\n          \"offset\": 10\n        },\n        \"huber\": {\n          \"delta\": 1.5\n        }\n      }\n    }\n  }\n}"
         },
         "MlEvaluateDataFrameRequestExample5": {
           "description": "Run `POST _ml/data_frame/_evaluate` to evaluate the training error of a regression job for an annotated index. The term query in the body limits evaluation to be performed on the training split only. The `actual_field` contains the ground truth for house prices. The `predicted_field` contains the house price calculated by the regression analysis.\n",
@@ -238334,4 +238334,4 @@
       "specLocation": "_spec_utils/behaviors.ts#L102-L108"
     }
   ]
-}
+}
\ No newline at end of file