Refresh and refactor to improve flow

Author: GraemeMalcolm

learn-pr/wwl-data-ai/build-agent-with-custom-tools/1-introduction.yml

@@ -4,7 +4,7 @@ title: Introduction
 metadata:
   title: Introduction
   description: "Introduction to building an agent with custom tools."
-  ms.date: 3/11/2025
+  ms.date: 04/03/2025
   author: ivorb
   ms.author: berryivor
   ms.topic: unit

learn-pr/wwl-data-ai/build-agent-with-custom-tools/2-why-use-custom-tools.yml

@@ -4,7 +4,7 @@ title: Why use custom tools
 metadata:
   title: Why use custom tools
   description: "Understand the benefits of using custom tools with your agent."
-  ms.date: 3/11/2025
+  ms.date: 04/03/2025
   author: ivorb
   ms.author: berryivor
   ms.topic: unit

learn-pr/wwl-data-ai/build-agent-with-custom-tools/3-custom-tool-options.yml

@@ -4,7 +4,7 @@ title: Options for implementing custom tools
 metadata:
   title: Options for implementing custom tools
   description: "Explore the options for implementing custom tools in your agent."
-  ms.date: 3/11/2025
+  ms.date: 04/03/2025
   author: ivorb
   ms.author: berryivor
   ms.topic: unit

learn-pr/wwl-data-ai/build-agent-with-custom-tools/4-how-use-custom-tools.yml

@@ -4,7 +4,7 @@ title: How to integrate custom tools
 metadata:
   title: How to integrate custom tools
   description: "Learn how to integrate custom tools into your agent. This unit covers function calling, Azure Function integration, and OpenAPI specification integration."
-  ms.date: 3/11/2025
+  ms.date: 04/03/2025
   author: ivorb
   ms.author: berryivor
   ms.topic: unit

learn-pr/wwl-data-ai/build-agent-with-custom-tools/5-exercise.yml

@@ -4,7 +4,7 @@ title: Exercise - Build an agent with custom tools
 metadata:
   title: Exercise - Build an agent with custom tools
   description: "Get interactive experience with building an agent with custom tools."
-  ms.date: 3/11/2025
+  ms.date: 04/03/2025
   author: ivorb
   ms.author: berryivor
   ms.topic: unit

learn-pr/wwl-data-ai/build-agent-with-custom-tools/6-knowledge-check.yml

@@ -4,45 +4,45 @@ title: Module assessment
 metadata:
   title: Module assessment
   description: "Check your knowledge of building an agent with custom tools."
-  ms.date: 3/11/2025
+  ms.date: 04/03/2025
   author: ivorb
   ms.author: berryivor
   ms.topic: unit
 durationInMinutes: 3
 content: |
 quiz:
   questions:
-  - content: "What is one of the primary benefits of using custom tools in Azure AI Agent Service?"  
+  - content: "What are custom tools, and how can they help you develop effective agents with Azure AI Agent Service?"  
     choices:  
-    - content: "They eliminate the need for any coding knowledge."  
-      isCorrect: false  
-      explanation: "Incorrect. While custom tools simplify many processes, some level of coding knowledge may still be required for advanced configurations."  
-    - content: "They enhance productivity by automating repetitive tasks."  
+    - content: "Callable functions that an agent to use to extend its capabilities."  
       isCorrect: true  
-      explanation: "Correct. Custom tools in Azure AI services can automate repetitive tasks, saving time and resources, which enhance productivity."  
-    - content: "They provide free access to all Azure AI services."  
+      explanation: "Correct. Custom tools extend the capabilities of your agents by enabling them to call external functions."  
+    - content: "Extensions for Visual Studio Code that make it easier to create and deploy agents."  
+      isCorrect: false  
+      explanation: "Incorrect. Custom tools aren't extensions for Visual Studio Code."  
+    - content: "Fine-tuned models that the agent can use to generate custom output."  
       isCorrect: false  
-      explanation: "Incorrect. While some Azure AI services offer a free tier, not all services are free, and custom tools don't inherently provide free access."
-  - content: "A company wants to integrate its AI agents with existing patient management systems securely that they have a standard specification for already. Which tool should they use?"  
+      explanation: "Incorrect. Custom tools aren't fine-tuned models."
+  - content: "You need to integrate functionality from an OpenAPI 3.0-based web service into an agent solution. What should you do?"  
     choices:  
-    - content: "Custom question answering"  
+    - content: "Add the JSON schema of the web service to the agent's instructions."  
       isCorrect: false  
-      explanation: "Incorrect. Custom question answering is designed for creating FAQ bots, not for integrating AI agents with existing systems."  
-    - content: "Azure AI Search tool"  
+      explanation: "Incorrect. Adding the schema of the web service to the instructions wouldn't result in the desired integration."  
+    - content: "Rewrite the web service as a Python function and hard-code it in your agent app."  
       isCorrect: false  
-      explanation: "Incorrect. The Azure AI Search tool is used for performing searches on large datasets, not for system integration."  
-    - content: "OpenAPI specified tools"  
+      explanation: "Incorrect. Rewriting the web service as a Python function and hard-coding it isn't an effective solution."  
+    - content: "Add the web service as an OpenAPI specification tool to the agent definition"  
       isCorrect: true  
-      explanation: "Correct. OpenAPI specified tools enable scalable interoperability with various applications, making them suitable for integrating AI agents with existing systems securely."  
-  - content: "What is a key advantage of using custom tools in Azure AI Agent Service?"  
+      explanation: "Correct. OpenAPI specification tools enable scalable interoperability with external services."  
+  - content: "Your agent application code includes a local function that you want the agent to call. What kind of tool should you add to the agent's definition?"  
     choices:  
-    - content: "They provide standardized, automated, and scalable integrations."  
+    - content: "Function calling"  
       isCorrect: true  
-      explanation: "Correct. Custom tools in Azure AI services offer standardized, automated, and scalable integrations, improving the function calling experience and overall efficiency."  
-    - content: "They eliminate the need for any human intervention."  
+      explanation: "Correct. Use a Function calling tool to access functions in your application code."  
+    - content: "Code interpreter"  
       isCorrect: false  
-      explanation: "Incorrect. While custom tools automate many processes, some level of human intervention may still be required for configuration and maintenance."  
-    - content: "They guarantee 100% accuracy in all predictions."  
+      explanation: "Incorrect. The code interpreter tool is used to enable the agent to generate its own code in a sandbox environment."  
+    - content: "Azure Functions"  
       isCorrect: false  
-      explanation: "Incorrect. No AI tool can guarantee 100% accuracy in all predictions; however, custom tools can significantly improve accuracy by fine-tuning models with specific data."  
+      explanation: "Incorrect. Azure Functions tools are used to enable the agent to call an Azure Function, not a function in your application code."  
 

learn-pr/wwl-data-ai/build-agent-with-custom-tools/7-summary.yml

@@ -4,7 +4,7 @@ title: Summary
 metadata:
   title: Summary
   description: "Review the key points of using custom tools with your agent."
-  ms.date: 3/11/2025
+  ms.date: 04/03/2025
   author: ivorb
   ms.author: berryivor
   ms.topic: unit

learn-pr/wwl-data-ai/build-agent-with-custom-tools/includes/1-introduction.md

@@ -1,13 +1,8 @@
-Azure AI Agent Service offers a seamless way to build an agent without needing extensive AI or machine learning expertise. Through the use of tools, you can provide your agent additional functionality to execute actions on your behalf.
+Azure AI Agent Service offers a seamless way to build an agent without needing extensive AI or machine learning expertise. By using tools, you can provide your agent with functionality to execute actions on your behalf.
 
-The AI Agent Service provides built-in tools for gathering knowledge and interpreting code, which provide your agent with some powerful functionality. However, sometimes your agent needs to be able to complete specific tasks or actions that an AI model would struggle to handle on its own. To accomplish these actions, you can provide your agent a **custom tool**.
+The AI Agent Service provides built-in tools for gathering knowledge and generating code, which provide your agent with some powerful functionality. However, sometimes your agent needs to be able to complete specific tasks or actions that an AI model would struggle to handle on its own. To accomplish these actions, you can provide your agent a *custom tool* based on your own code or a third-party service or API.
 
-Imagine you're working in the retail industry, and your company is struggling with managing customer inquiries efficiently. The customer support team is overwhelmed with repetitive questions, leading to delays in response times and decreased customer satisfaction. By leveraging Azure AI Agent Service with custom tools, you can create a custom FAQ agent that handles common inquiries. This agent can be provided a set of custom tools to look up customer orders, freeing up your support team to focus on more complex issues.
+Imagine you're working in the retail industry, and your company is struggling with managing customer inquiries efficiently. The customer support team is overwhelmed with repetitive questions, leading to delays in response times and decreased customer satisfaction. By using Azure AI Agent Service with custom tools, you can create a custom FAQ agent that handles common inquiries. This agent can be provided with a set of custom tools to look up customer orders, freeing up your support team to focus on more complex issues.
 
 In this module, you'll learn how to utilize custom tools in Azure AI Agent Service to enhance productivity, improve accuracy, and create tailored solutions for specific needs.
 
-After completing this module, you’ll be able to:
-
-- Describe the benefits of using custom tools in your agent.
-- Explore the different options for custom tools.
-- Build an agent with custom tools using the Azure AI Agent Service.

learn-pr/wwl-data-ai/build-agent-with-custom-tools/includes/2-why-use-custom-tools.md

@@ -1,20 +1,55 @@
-Azure AI Agent Service offers a powerful platform for integrating custom tools to enhance productivity and provide tailored solutions for specific business needs. By leveraging these custom tools, businesses can achieve greater efficiency and effectiveness in their operations.
+Azure AI Agent Service offers a powerful platform for integrating custom tools to enhance productivity and provide tailored solutions for specific business needs. By using these custom tools, businesses can achieve greater efficiency and effectiveness in their operations.
 
-## Benefits of using custom tools in Azure AI Agent Service
+## Why use custom tools?
 
 Custom tools in Azure AI services can significantly enhance productivity by automating repetitive tasks and streamlining workflows that are specific to your use case. These tools improve accuracy by providing precise and consistent outputs, reducing the likelihood of human error. Additionally, custom tools offer tailored solutions that address specific business needs, enabling organizations to optimize their processes and achieve better outcomes.
 
 - **Enhanced productivity**: Automate repetitive tasks and streamline workflows.
 - **Improved accuracy**: Provide precise and consistent outputs, reducing human error.
 - **Tailored solutions**: Address specific business needs and optimize processes.
 
-Adding tools to achieve custom functionality are available for the agent to decide to use, depending on how it decides to respond to the user prompt.
+Adding tools makes custom functionality available for the agent to use, depending on how it decides to respond to the user prompt. For example, consider how a custom tool to retrieve weather data from an external meteorological service could be used by an agent.
 
-![Diagram showing the flow of logic through an agent using a custom tool.](../media/agent-tool-diagram.png)
+![Diagram showing an agent using a custom tool t call an external meteorological service.](../media/agent-tool-diagram.png)
 
-The diagram shows the process of an agent choosing to use the provided tool:
+The diagram shows the process of an agent choosing to use the custom tool:
 
-1. A user asks an agent for a report, such as about recent snowfall in their local mountains.
-1. The agent determines the provided tool to retrieve snowfall for a specific location will be useful, and calls that tool.
-1. The agent may choose to use other tools to best accomplish the user's task, such as retrieve knowledge using a built-in tool.
-1. The agent then outputs the report and responds to the user.
+1. A user asks an agent about the weather conditions in a ski resort.
+2. The agent determines that it has access to a tool that can use an API to get meteorological information, and calls it.
+3. The tool returns the weather report, and the agent informs the user.
+
+## Common scenarios for custom tools in agents
+
+Custom tools within the Azure AI Agent Service enable users to extend the capabilities of AI agents, tailoring them to meet specific business needs. Some example use cases that illustrate the versatility and impact of custom tools include:
+
+### Customer support automation
+
+- **Scenario**: A retail company integrates a custom tool that connects the Azure AI Agent to their customer relationship management (CRM) system.
+- **Functionality**: The AI agent can retrieve customer order histories, process refunds, and provide real-time updates on shipping statuses.
+- **Outcome**: Faster resolution of customer queries, reduced workload for support teams, and improved customer satisfaction.
+
+### Inventory management
+
+- **Scenario**: A manufacturing company develops a custom tool to link the AI agent with their inventory management system.
+- **Functionality**: The AI agent can check stock levels, predict restocking needs using historical data, and place orders with suppliers automatically.
+- **Outcome**: Streamlined inventory processes and optimized supply chain operations.
+
+### Healthcare appointment scheduling
+
+- **Scenario**: A healthcare provider integrates a custom scheduling tool with the AI agent.
+- **Functionality**: The AI agent can access patient records, suggest available appointment slots, and send reminders to patients.
+- **Outcome**: Reduced administrative burden, improved patient experience, and better resource utilization.
+
+### IT Helpdesk support
+
+- **Scenario**: An IT department develops a custom tool to integrate the AI agent with their ticketing and knowledge base systems.
+- **Functionality**: The AI agent can troubleshoot common technical issues, escalate complex problems, and track ticket statuses.
+- **Outcome**: Faster issue resolution, reduced downtime, and improved employee productivity.
+
+### E-learning and training
+
+- **Scenario**: An educational institution creates a custom tool to connect the AI agent with their learning management system (LMS).
+- **Functionality**: The AI agent can recommend courses, track student progress, and answer questions about course content.
+- **Outcome**: Enhanced learning experiences, increased student engagement, and streamlined administrative tasks.
+
+These examples demonstrate how custom tools within the Azure AI Agent Service can be used across industries to address unique challenges, drive efficiency, and deliver value.