diff --git a/recipes/use_cases/gmail_agent/README.md b/recipes/use_cases/gmail_agent/README.md
index a243234d2e065ccd17a8dca195267f1497a8e160..38a70d6dc417563e55e5b4b4df7c3055fb403be9 100644
--- a/recipes/use_cases/gmail_agent/README.md
+++ b/recipes/use_cases/gmail_agent/README.md
@@ -301,7 +301,7 @@ Tool calling returned: [{'message_id': '1936ef72ad3f30e8', 'sender': 'gmagent_te
 # TODOs
 
 1. Port the app to using [Llama Stack](https://github.com/meta-llama/llama-stack) Agents API.
-2. Improve the search, reply, forward, create email draft, and query about attachments to cover all listed and other examples in `functions_prompt.py`.
+2. Improve the search, reply, forward, create email draft, and query about types of attachments.
 3. Improve the fallback and error handling mechanism when the user asks don't lead to a correct function calling spec or the function calling fails. 
 4. Improve the user experience by showing progress when some Gmail search API calls take long (minutes) to complete.
 5. Implement the async behavior of Gmagent - schedule an email to be sent later.
@@ -311,17 +311,17 @@ Tool calling returned: [{'message_id': '1936ef72ad3f30e8', 'sender': 'gmagent_te
 9. Introduce multiple-agent collaboration.
 10. Implement the agent observability. 
 11. Compare different agent frameworks using Gmagent as the case study.
-12. Productionize Gmagent.
+12. Add and implement a test plan and productionize Gmagent.
 
 
 # Resources
 1. Lilian Weng's blog [LLM Powered Autonomous Agents](https://lilianweng.github.io/posts/2023-06-23-agent/) 
-2. Andrew Ng's posts [Agentic Design Patterns](https://www.deeplearning.ai/the-batch/how-agents-can-improve-llm-performance/)
+2. Andrew Ng's posts [Agentic Design Patterns](https://www.deeplearning.ai/the-batch/how-agents-can-improve-llm-performance/) with basic [implementations from scratch](https://github.com/neural-maze/agentic_patterns).
 3. LangChain's survey [State of AI Agents](https://www.langchain.com/stateofaiagents)
 4. Deloitte's report [AI agents and multiagent systems](https://www2.deloitte.com/content/dam/Deloitte/us/Documents/consulting/us-ai-institute-generative-ai-agents-multiagent-systems.pdf)
 5. Letta's blog [The AI agents stack](https://www.letta.com/blog/ai-agents-stack)
 6. Microsoft's multi-agent system [Magentic-One](https://www.microsoft.com/en-us/research/articles/magentic-one-a-generalist-multi-agent-system-for-solving-complex-tasks)
 7. Amazon's [Multi-Agent Orchestrator framework](https://awslabs.github.io/multi-agent-orchestrator/)
-8. Deeplearning.ai's [agent related courses](https://www.deeplearning.ai/courses/?courses_date_desc%5Bquery%5D=agents) (Meta, AWS, Microsoft, LangChain, LlamaIndex, crewAI, AutoGen) and some [lessons ported to using Llama](https://github.com/meta-llama/llama-recipes/tree/main/recipes/quickstart/agents/DeepLearningai_Course_Notebooks). 
+8. Deeplearning.ai's [agent related courses](https://www.deeplearning.ai/courses/?courses_date_desc%5Bquery%5D=agents) (Meta, AWS, Microsoft, LangChain, LlamaIndex, crewAI, AutoGen, Letta) and some [lessons ported to using Llama](https://github.com/meta-llama/llama-recipes/tree/main/recipes/quickstart/agents/DeepLearningai_Course_Notebooks). 
 9. Felicis's [The Agentic Web](https://www.felicis.com/insight/the-agentic-web)
 10. A pretty complete [list of AI agents](https://github.com/e2b-dev/awesome-ai-agents), not including [/dev/agents](https://sdsa.ai/), a very new startup building the next-gen OS for AI agents, though.
diff --git a/recipes/use_cases/gmail_agent/gmagent.py b/recipes/use_cases/gmail_agent/gmagent.py
index 44bd8b3ee5b21145d85a0fc957c59453cd708b18..69603a8c7e2f64c80e036f2f5a9c22bf22c38b8e 100644
--- a/recipes/use_cases/gmail_agent/gmagent.py
+++ b/recipes/use_cases/gmail_agent/gmagent.py
@@ -491,11 +491,11 @@ user_email = None
 service = None
 user_id = 'me'
 
-def set_email_service(email):
+def set_email_service(gmail):
     global user_email
     global service
 
-    user_email = email
+    user_email = gmail
     service = authenticate_gmail(user_email)
 
 class Agent:
diff --git a/recipes/use_cases/gmail_agent/main.py b/recipes/use_cases/gmail_agent/main.py
index 9a1e0aedab0c047486f93bfc71f6abd801b197d7..781937de6665c7c4a08ef040607de6712163130b 100644
--- a/recipes/use_cases/gmail_agent/main.py
+++ b/recipes/use_cases/gmail_agent/main.py
@@ -6,10 +6,12 @@ from functions_prompt import system_prompt
 
 def main():
     parser = argparse.ArgumentParser(description="Set email address")
-    parser.add_argument("--user_email", type=str, required=True, help="Your Gmail address")
+    parser.add_argument("--gmail", type=str, required=True, help="Your Gmail address")
     args = parser.parse_args()
 
-    gmagent.set_email_service(args.user_email)
+    print(f"{args.gmail=}")
+
+    gmagent.set_email_service(args.gmail)
 
     greeting = llama31("hello", "Your name is Gmagent, an assistant that can perform all Gmail related tasks for your user.")
     agent_response = f"{greeting}\n\nYour ask: "