diff --git a/dev_gpt/options/generate/pm/pm.py b/dev_gpt/options/generate/pm/pm.py
index 7425f08..3dd2122 100644
--- a/dev_gpt/options/generate/pm/pm.py
+++ b/dev_gpt/options/generate/pm/pm.py
@@ -64,7 +64,9 @@ Description of the microservice:
             question_gen='Generate a question that requests for an example file url.',
             extension_name='Input Example',
         )
-        used_apis_beside_tools = [x for x in self.get_used_apis(microservice_description) if x not in ['google_custom_search', 'gpt_3_5_turbo']]
+        used_apis_beside_tools = [
+            x for x in self.get_used_apis(microservice_description) if any(t in x.lower() for t in ['gpt', 'search', 'google'])
+        ]
         for api in used_apis_beside_tools:
             microservice_description += self.user_input_extension_if_needed(
                 {
diff --git a/dev_gpt/options/generate/templates_user.py b/dev_gpt/options/generate/templates_user.py
index 8c65120..b6bb0f7 100644
--- a/dev_gpt/options/generate/templates_user.py
+++ b/dev_gpt/options/generate/templates_user.py
@@ -554,6 +554,7 @@ Microservice description:
 
 Question:
 Respond with a list as JSON indicating which web APIs (e.g. google_custom_search, gpt_3_5_turbo) are mentioned in the description.
+Note that local libraries are not web APIs and must not be mentioned. 
 Positive Example 1:
 {{
   "mentioned_apis": ["google_custom_search", "gpt_3_5_turbo"]
diff --git a/test/unit/test_tools.py b/test/unit/test_tools.py
index e559605..f29aea6 100644
--- a/test/unit/test_tools.py
+++ b/test/unit/test_tools.py
@@ -14,17 +14,17 @@ def test_no_search():
     tool_lines = get_available_tools().split('\n')
     assert len(tool_lines) == 1
 
-def test_get_used_tools(tmpdir):
+def test_get_used_apis(tmpdir):
     os.environ['VERBOSE'] = 'true'
     GPTSession(os.path.join(str(tmpdir), 'log.json'), model='gpt-3.5-turbo')
-    used_tools = PM.get_used_apis('''\
+    used_apis = PM.get_used_apis('''\
 This microservice listens for incoming requests and generates a fixed output of "test" upon receiving a request. \
 The response sent back to the requester includes the output as a string parameter. \
 No specific request parameters are required, and the response always follows a fixed schema with a single "output" parameter.'''
                                   )
-    assert used_tools == []
+    assert used_apis == []
 
-def test_get_used_tools_2(tmpdir):
+def test_get_used_apis_2(tmpdir):
     os.environ['VERBOSE'] = 'true'
     GPTSession(os.path.join(str(tmpdir), 'log.json'), model='gpt-3.5-turbo')
     description = '''\
@@ -36,5 +36,31 @@ This microservice accepts a 1-minute WAV audio file of speech, encoded as a base
 4. Encodes the resulting audio file as a base64 binary string.
 
 The microservice returns the summarized text converted to audio and encoded as a base64 binary string.'''
-    used_tools = PM.get_used_apis(description)
-    assert used_tools == ['Whisper API', 'gpt_3_5_turbo', 'text-to-speech (TTS) library']
+    used_apis = PM.get_used_apis(description)
+    assert used_apis == ['Whisper API', 'gpt_3_5_turbo', 'text-to-speech (TTS) library']
+
+def test_get_used_apis_3(tmpdir):
+    os.environ['VERBOSE'] = 'true'
+    GPTSession(os.path.join(str(tmpdir), 'log.json'), model='gpt-3.5-turbo')
+    description = '''\
+This microservice takes a PDF file as input and returns a summarized text output. \
+It uses PDF parsing and natural language processing tools to generate the summary, \
+and applies post-processing techniques to improve its quality. \
+The input parameter is the PDF file, \
+and the output parameter is the summarized text.'''
+    used_apis = PM.get_used_apis(description)
+    assert used_apis == []
+
+def test_get_used_apis_4(tmpdir):
+    os.environ['VERBOSE'] = 'true'
+    GPTSession(os.path.join(str(tmpdir), 'log.json'), model='gpt-3.5-turbo')
+    description = '''\
+This microservice receives a tweet as input \
+and identifies passive aggressive language using natural language processing techniques. \
+It then generates a positive version of the tweet using a text processing tool such as GPT-3. \
+The positive version of the tweet is returned as output. \
+The input tweet should be provided as a base64 encoded string \
+and the output positive tweet will also be returned as a base64 encoded string.'''
+    used_apis = PM.get_used_apis(description)
+    assert used_apis == ['GPT-3']
+