diff --git a/tests/models/test_agent_llmfx_process.py b/tests/models/test_agent_llmfx_process.py
index 6d43c4e2..bf719962 100644
--- a/tests/models/test_agent_llmfx_process.py
+++ b/tests/models/test_agent_llmfx_process.py
@@ -1,74 +1,66 @@
-
-""" Tests the execution of a multi-step Agent process using multiple SLIM models. """
+"""Tests the execution of a multi-step Agent process using multiple SLIM models."""
 
 from llmware.agents import LLMfx
 
-
 def test_multistep_agent_process():
+    # Sample customer transcript
+    customer_transcript = "My name is Michael Jones, and I am a long-time customer. The Mixco product is not working currently, and it is having a negative impact on my business, as we can not deliver our products while it is down. This is the fourth time that I have called. My account number is 93203, and my user name is mjones. Our company is based in Tampa, Florida."
 
-    # sample customer transcript
-
-    customer_transcript = "My name is Michael Jones, and I am a long-time customer.  " \
-                          "The Mixco product is not working currently, and it is having a negative impact " \
-                          "on my business, as we can not deliver our products while it is down. " \
-                          "This is the fourth time that I have called.  My account number is 93203, and " \
-                          "my user name is mjones. Our company is based in Tampa, Florida."
-
-    #   create an agent using LLMfx class
+    # Create an agent using LLMfx class
     agent = LLMfx()
 
+    # Load the work
     agent.load_work(customer_transcript)
 
-    #   load tools individually
+    # Load tools individually
     agent.load_tool("sentiment")
     agent.load_tool("ner")
 
-    #   load multiple tools
+    # Load multiple tools
     agent.load_tool_list(["emotions", "topics", "intent", "tags", "ratings", "answer"])
 
-    #   start deploying tools and running various analytics
-
-    #   first conduct three 'soft skills' initial assessment using 3 different models
+    # Start deploying tools and running various analytics
+    # First, conduct three 'soft skills' initial assessment using 3 different models
     agent.sentiment()
     agent.emotions()
     agent.intent()
 
-    #   alternative way to execute a tool, passing the tool name as a string
+    # Alternative way to execute a tool, passing the tool name as a string
     agent.exec_function_call("ratings")
 
-    #   call multiple tools concurrently
-    agent.exec_multitool_function_call(["ner","topics","tags"])
+    # Call multiple tools concurrently
+    agent.exec_multitool_function_call(["ner", "topics", "tags"])
 
-    #   the 'answer' tool is a quantized question-answering model - ask an 'inline' question
-    #   the optional 'key' assigns the output to a dictionary key for easy consolidation
-    agent.answer("What is a short summary?",key="summary")
+    # The 'answer' tool is a quantized question-answering model - ask an 'inline' question
+    # The optional 'key' assigns the output to a dictionary key for easy consolidation
+    agent.answer("What is a short summary?", key="summary")
 
-    #   prompting tool to ask a quick question as part of the analytics
+    # Prompting tool to ask a quick question as part of the analytics
     response = agent.answer("What is the customer's account number and user name?", key="customer_info")
 
-    #   you can 'unload_tool' to release it from memory
+    # You can 'unload_tool' to release it from memory
     agent.unload_tool("ner")
     agent.unload_tool("topics")
 
-    #   at end of processing, show the report that was automatically aggregated by key
+    # At the end of processing, show the report that was automatically aggregated by key
     report = agent.show_report()
 
-    #   displays a summary of the activity in the process
+    # Display a summary of the activity in the process
     activity_summary = agent.activity_summary()
 
-    #   list of the responses gathered
+    # List of the responses gathered
     for i, entries in enumerate(agent.response_list):
-        print("update: response analysis: ", i, entries)
-
+        print(f"Update: response analysis {i}: {entries}")
         assert entries is not None
 
     assert activity_summary is not None
     assert agent.journal is not None
     assert report is not None
 
-    output = {"report": report, "activity_summary": activity_summary, "journal": agent.journal}
+    output = {
+        "report": report,
+        "activity_summary": activity_summary,
+        "journal": agent.journal
+    }
 
     return output
-
-
-