diff --git a/docs/workflow/submit.rst b/docs/workflow/submit.rst
index fe097c3..2d82936 100644
--- a/docs/workflow/submit.rst
+++ b/docs/workflow/submit.rst
@@ -80,10 +80,10 @@ the following code snippet offers guidance on how to construct and store the RKM
 
 .. code-block:: python
     
-    import learnware.specification as specification
+    from learnware.specification import generate_rkme_spec
     
     # generate rkme specification for digits dataset
-    spec = specification.utils.generate_rkme_spec(X=data_X)
+    spec = generate_rkme_spec(X=data_X)
     spec.save("stat.json")
 
 Significantly, the RKME generation process is entirely conducted on your local machine, without any involvement of cloud services, 
diff --git a/examples/dataset_m5_workflow/main.py b/examples/dataset_m5_workflow/main.py
index 009b557..bfdbe71 100644
--- a/examples/dataset_m5_workflow/main.py
+++ b/examples/dataset_m5_workflow/main.py
@@ -9,9 +9,8 @@ from shutil import copyfile, rmtree
 import learnware
 from learnware.market import EasyMarket, BaseUserInfo
 from learnware.market import database_ops
-from learnware.learnware import Learnware
 from learnware.reuse import JobSelectorReuser, AveragingReuser
-import learnware.specification as specification
+from learnware.specification import generate_rkme_spec
 from m5 import DataLoader
 from learnware.logger import get_module_logger
 
@@ -88,7 +87,7 @@ class M5DatasetWorkflow:
         for idx in tqdm(idx_list):
             train_x, train_y, test_x, test_y = m5.get_idx_data(idx)
             st = time.time()
-            spec = specification.utils.generate_rkme_spec(X=train_x, gamma=0.1, cuda_idx=0)
+            spec = generate_rkme_spec(X=train_x, gamma=0.1, cuda_idx=0)
             ed = time.time()
             logger.info("Stat spec generated in %.3f s" % (ed - st))
 
@@ -140,7 +139,7 @@ class M5DatasetWorkflow:
 
         for idx in idx_list:
             train_x, train_y, test_x, test_y = m5.get_idx_data(idx)
-            user_spec = specification.utils.generate_rkme_spec(X=test_x, gamma=0.1, cuda_idx=0)
+            user_spec = generate_rkme_spec(X=test_x, gamma=0.1, cuda_idx=0)
             user_spec_path = f"./user_spec/user_{idx}.json"
             user_spec.save(user_spec_path)
 
diff --git a/examples/dataset_pfs_workflow/main.py b/examples/dataset_pfs_workflow/main.py
index b5cbdd8..abe80cd 100644
--- a/examples/dataset_pfs_workflow/main.py
+++ b/examples/dataset_pfs_workflow/main.py
@@ -8,10 +8,8 @@ from shutil import copyfile, rmtree
 
 import learnware
 from learnware.market import EasyMarket, BaseUserInfo
-from learnware.market import database_ops
-from learnware.learnware import Learnware
 from learnware.reuse import JobSelectorReuser, AveragingReuser
-import learnware.specification as specification
+from learnware.specification import generate_rkme_spec
 from pfs import Dataloader
 from learnware.logger import get_module_logger
 
@@ -86,7 +84,7 @@ class PFSDatasetWorkflow:
         for idx in tqdm(idx_list):
             train_x, train_y, test_x, test_y = pfs.get_idx_data(idx)
             st = time.time()
-            spec = specification.utils.generate_rkme_spec(X=train_x, gamma=0.1, cuda_idx=0)
+            spec = generate_rkme_spec(X=train_x, gamma=0.1, cuda_idx=0)
             ed = time.time()
             logger.info("Stat spec generated in %.3f s" % (ed - st))
 
@@ -138,7 +136,7 @@ class PFSDatasetWorkflow:
 
         for idx in idx_list:
             train_x, train_y, test_x, test_y = pfs.get_idx_data(idx)
-            user_spec = specification.utils.generate_rkme_spec(X=test_x, gamma=0.1, cuda_idx=0)
+            user_spec = generate_rkme_spec(X=test_x, gamma=0.1, cuda_idx=0)
             user_spec_path = f"./user_spec/user_{idx}.json"
             user_spec.save(user_spec_path)
 
diff --git a/examples/dataset_text_workflow/main.py b/examples/dataset_text_workflow/main.py
index e7e1c38..406aad9 100644
--- a/examples/dataset_text_workflow/main.py
+++ b/examples/dataset_text_workflow/main.py
@@ -10,9 +10,7 @@ import time
 import pickle
 
 from learnware.market import instantiate_learnware_market, BaseUserInfo
-from learnware.market import database_ops
-from learnware.learnware import Learnware
-import learnware.specification as specification
+from learnware.specification import RKMETextSpecification
 from learnware.logger import get_module_logger
 
 from shutil import copyfile, rmtree
@@ -99,8 +97,7 @@ def prepare_learnware(data_path, model_path, init_file_path, yaml_path, save_roo
     semantic_spec = semantic_specs[0]
 
     st = time.time()
-    # user_spec = specification.utils.generate_rkme_spec(X=X, gamma=0.1, cuda_idx=0)
-    user_spec = specification.RKMETextSpecification()
+    user_spec = RKMETextSpecification()
     user_spec.generate_stat_spec_from_data(X=X)
     ed = time.time()
     logger.info("Stat spec generated in %.3f s" % (ed - st))
@@ -163,10 +160,8 @@ def test_search(gamma=0.1, load_market=True):
             user_data = pickle.load(f)
         with open(user_label_path, "rb") as f:
             user_label = pickle.load(f)
-        # user_data = np.load(user_data_path)
-        # user_label = np.load(user_label_path)
-        # user_stat_spec = specification.utils.generate_rkme_spec(X=user_data, gamma=gamma, cuda_idx=0)
-        user_stat_spec = specification.RKMETextSpecification()
+
+        user_stat_spec = RKMETextSpecification()
         user_stat_spec.generate_stat_spec_from_data(X=user_data)
         user_info = BaseUserInfo(semantic_spec=user_semantic, stat_info={"RKMETextSpecification": user_stat_spec})
         logger.info("Searching Market for user: %d" % (i))
diff --git a/examples/workflow_by_code/main.py b/examples/workflow_by_code/main.py
index 2f62db0..afedc41 100644
--- a/examples/workflow_by_code/main.py
+++ b/examples/workflow_by_code/main.py
@@ -12,8 +12,7 @@ from shutil import copyfile, rmtree
 import learnware
 from learnware.market import EasyMarket, BaseUserInfo
 from learnware.reuse import JobSelectorReuser, AveragingReuser
-import learnware.specification as specification
-from learnware.utils import get_module_by_module_path
+from learnware.specification import generate_rkme_spec
 
 curr_root = os.path.dirname(os.path.abspath(__file__))
 
@@ -54,7 +53,7 @@ class LearnwareMarketWorkflow:
 
             joblib.dump(clf, os.path.join(dir_path, "svm.pkl"))
 
-            spec = specification.utils.generate_rkme_spec(X=data_X, gamma=0.1, cuda_idx=0)
+            spec = generate_rkme_spec(X=data_X, gamma=0.1, cuda_idx=0)
             spec.save(os.path.join(dir_path, "svm.json"))
 
             init_file = os.path.join(dir_path, "__init__.py")
@@ -174,7 +173,7 @@ class LearnwareMarketWorkflow:
         X, y = load_digits(return_X_y=True)
         _, data_X, _, data_y = train_test_split(X, y, test_size=0.3, shuffle=True)
 
-        stat_spec = specification.utils.generate_rkme_spec(X=data_X, gamma=0.1, cuda_idx=0)
+        stat_spec = generate_rkme_spec(X=data_X, gamma=0.1, cuda_idx=0)
         user_info = BaseUserInfo(semantic_spec=user_semantic, stat_info={"RKMETableSpecification": stat_spec})
 
         _, _, _, mixture_learnware_list = easy_market.search_learnware(user_info)
diff --git a/learnware/reuse/job_selector.py b/learnware/reuse/job_selector.py
index a131fd5..5e3a71f 100644
--- a/learnware/reuse/job_selector.py
+++ b/learnware/reuse/job_selector.py
@@ -11,7 +11,7 @@ from .base import BaseReuser
 from ..market.utils import parse_specification_type
 from ..learnware import Learnware
 from ..specification import RKMETableSpecification, RKMETextSpecification
-from ..specification.utils import generate_rkme_spec
+from ..specification import generate_rkme_spec
 from ..logger import get_module_logger
 
 logger = get_module_logger("job_selector_reuse")
diff --git a/tests/test_market/test_easy.py b/tests/test_market/test_easy.py
index bb03839..0ca779f 100644
--- a/tests/test_market/test_easy.py
+++ b/tests/test_market/test_easy.py
@@ -12,7 +12,7 @@ from shutil import copyfile, rmtree
 
 import learnware
 from learnware.market import instantiate_learnware_market, BaseUserInfo
-import learnware.specification as specification
+from learnware.specification import RKMETableSpecification, generate_rkme_spec
 
 curr_root = os.path.dirname(os.path.abspath(__file__))
 
@@ -62,7 +62,7 @@ class TestMarket(unittest.TestCase):
 
             joblib.dump(clf, os.path.join(dir_path, "svm.pkl"))
 
-            spec = specification.utils.generate_rkme_spec(X=data_X, gamma=0.1, cuda_idx=0)
+            spec = generate_rkme_spec(X=data_X, gamma=0.1, cuda_idx=0)
             spec.save(os.path.join(dir_path, "svm.json"))
 
             init_file = os.path.join(dir_path, "__init__.py")
@@ -170,7 +170,7 @@ class TestMarket(unittest.TestCase):
             with zipfile.ZipFile(zip_path, "r") as zip_obj:
                 zip_obj.extractall(path=unzip_dir)
 
-            user_spec = specification.rkme.RKMETableSpecification()
+            user_spec = RKMETableSpecification()
             user_spec.load(os.path.join(unzip_dir, "svm.json"))
             user_info = BaseUserInfo(semantic_spec=user_semantic, stat_info={"RKMETableSpecification": user_spec})
             (
diff --git a/tests/test_specification/test_rkme.py b/tests/test_specification/test_rkme.py
index 143bf22..ba280b2 100644
--- a/tests/test_specification/test_rkme.py
+++ b/tests/test_specification/test_rkme.py
@@ -7,9 +7,8 @@ import unittest
 import tempfile
 import numpy as np
 
-import learnware.specification as specification
 from learnware.specification import RKMETableSpecification, RKMEImageSpecification, RKMETextSpecification
-from learnware.specification import generate_rkme_image_spec, generate_rkme_spec
+from learnware.specification import generate_rkme_image_spec, generate_rkme_spec, generate_rkme_text_spec
 
 
 class TestRKME(unittest.TestCase):
@@ -71,7 +70,7 @@ class TestRKME(unittest.TestCase):
             return text_list
 
         def _test_text_rkme(X):
-            rkme = specification.utils.generate_rkme_text_spec(X)
+            rkme = generate_rkme_text_spec(X)
 
             with tempfile.TemporaryDirectory(prefix="learnware_") as tempdir:
                 rkme_path = os.path.join(tempdir, "rkme.json")
diff --git a/tests/test_workflow/test_workflow.py b/tests/test_workflow/test_workflow.py
index fea00d9..3b3579c 100644
--- a/tests/test_workflow/test_workflow.py
+++ b/tests/test_workflow/test_workflow.py
@@ -13,7 +13,7 @@ from shutil import copyfile, rmtree
 import learnware
 from learnware.market import EasyMarket, BaseUserInfo
 from learnware.reuse import JobSelectorReuser, AveragingReuser, EnsemblePruningReuser
-import learnware.specification as specification
+from learnware.specification import generate_rkme_spec, RKMETableSpecification
 
 curr_root = os.path.dirname(os.path.abspath(__file__))
 
@@ -57,7 +57,7 @@ class TestAllWorkflow(unittest.TestCase):
 
             joblib.dump(clf, os.path.join(dir_path, "svm.pkl"))
 
-            spec = specification.utils.generate_rkme_spec(X=data_X, gamma=0.1, cuda_idx=0)
+            spec = generate_rkme_spec(X=data_X, gamma=0.1, cuda_idx=0)
             spec.save(os.path.join(dir_path, "svm.json"))
 
             init_file = os.path.join(dir_path, "__init__.py")
@@ -159,7 +159,7 @@ class TestAllWorkflow(unittest.TestCase):
             with zipfile.ZipFile(zip_path, "r") as zip_obj:
                 zip_obj.extractall(path=unzip_dir)
 
-            user_spec = specification.RKMETableSpecification()
+            user_spec = RKMETableSpecification()
             user_spec.load(os.path.join(unzip_dir, "svm.json"))
             user_info = BaseUserInfo(semantic_spec=user_semantic, stat_info={"RKMETableSpecification": user_spec})
             (
@@ -185,7 +185,7 @@ class TestAllWorkflow(unittest.TestCase):
         X, y = load_digits(return_X_y=True)
         train_X, data_X, train_y, data_y = train_test_split(X, y, test_size=0.3, shuffle=True)
 
-        stat_spec = specification.utils.generate_rkme_spec(X=data_X, gamma=0.1, cuda_idx=0)
+        stat_spec = generate_rkme_spec(X=data_X, gamma=0.1, cuda_idx=0)
         user_info = BaseUserInfo(semantic_spec=user_semantic, stat_info={"RKMETableSpecification": stat_spec})
 
         _, _, _, mixture_learnware_list = easy_market.search_learnware(user_info)