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| Section | Objectives |
|---|---|
| Build and Configure AI Agents in Copilot Studio | - Using generative AI and prompt engineering in Copilot Studio - Creating and configuring copilots and topics - Configuring actions, plugins, and connectors |
| Plan and Design Copilot Studio AI Agents | - Designing conversation flows and agent behavior - Requirements analysis for AI agent solutions - Selecting Copilot Studio capabilities and architecture approach |
| Deploy, Monitor, and Optimize AI Agents | - Iterative improvement and lifecycle management - Publishing and deploying copilots - Monitoring performance and analytics |
| Governance, Security, and Compliance | - Environment management in Power Platform - Managing access control and authentication - Data protection and responsible AI practices |
| Integrate External Systems and Data Sources | - Integrating Dataverse and Power Platform components - Connecting Azure services and APIs - Using Power Automate for workflow orchestration |
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NEW QUESTION # 59
Drag and Drop Question
A company wants to extend an agent in Copilot Studio by calling an external REST API to retrieve and update data.
To meet the business needs, the REST API must be added following a correct dependency order.
You need to add a REST API to the agent so it can be invoked during conversations.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
You must configure authentication and the API tool before you can successfully configure the endpoint details and test it.
To add an external REST API to an agent in Copilot Studio, you must follow this exact dependency order:
Step 1: Configure authentication for the API
Setup security credentials first.
This includes API keys or OAuth.
Without this, the connection will fail.
Security First: Copilot Studio requires a valid connection object to save and route endpoint requests.
Step 2: Add the REST API tool.
Import or create the action connector.
This registers the tool in Copilot.
Tool Registration: The agent needs to recognize the tool wrapper before you can customize its internal endpoint paths.
Step 3: Configure the API endpoint details.
Define specific paths and methods.
Map input and output parameters.
Step 4: Test the API configuration
Run validation checks in real-time.
Ensure data flows correctly.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/agent-extend-action-rest-api
NEW QUESTION # 60
An agent in Copilot Studio must retrieve real-time data from an external system that exposes a REST API.
The API returns structured JSON data and requires authentication.
The agent must call the API during conversations to fulfill user requests.
The agent must retrieve real-time data from the external system by calling an authenticated REST API during a conversation.
The solution must use a supported mechanism that executes the REST API call and the call must be explicitly configured to run at runtime.
You need to determine which approaches add the REST API to the agent.
Which two solutions meet the goal? Each correct answer is a complete solution.
NOTE: Each correct selection is worth one point.
Answer: A,D
Explanation:
[A] Configure an HTTP action and invoke it from a topic during the conversation.
This is a correct and supported solution.
You can fulfill this requirement directly within Microsoft Copilot Studio by configuring an HTTP Request node (HTTP action) inside a topic.
Real-Time Execution: The HTTP action is explicitly executed at runtime during the live conversation when the specific topic is triggered.
Native Authentication Support: The HTTP Request node allows you to securely pass authentication tokens, API keys, or custom credentials directly within the request headers.
Handles Structured JSON: The node natively supports standard REST methods (GET, POST, PATCH, PUT, DELETE) and can ingest structured JSON data, allowing you to parse and store the returned values into agent variables for use later in the conversation.
[C] Add the REST API as a tool and call it either by using a topic or agent instruction.
Depending on how your agent architecture is managed, you could also fulfill this requirement using these alternative methods:
*-> REST API Tools (OpenAPI Plugins): You can upload an OpenAPI specification directly into Copilot Studio to register the REST API as a native REST API tool/action.
* Power Automate Flows: You can invoke a Power Automate cloud flow from a topic, using the HTTP connector inside the flow to retrieve and pass back the JSON data.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/agent-extend-action-rest-api
NEW QUESTION # 61
A company uses an agent flow that occasionally requires human input before continuing execution.
Some automated actions must pause until a human provides a decision or additional information. The flow must be configured to:
* Capture a human response for use in later steps.
* Continue processing within the same flow run after the response is submitted.
* Wait for a manual decision before proceeding.
You need to configure a human-in-the-loop agent flow.
Which setting should you configure for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 62
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear on the review screen.
A team is implementing ALM for agents in Copilot Studio across multiple environments.
The team requires a consistent way to manage and transport agent assets.
You need to recommend a solution that supports creation and use of ALM scenarios for agents in Copilot Studio.
Solution: To export, import, and manage agents between environments, you need to create and use a custom solution.
Does the solution meet the goal?
Answer: A
Explanation:
Correct:
* Builders can change environment variable values directly in Copilot Studio to complete ALM configuration without administrative tools.
builders can change environment variable values directly during the solution import process to complete Application Lifecycle Management (ALM) configurations.
Native ALM in Copilot StudioMicrosoft Copilot Studio embeds native solution management capabilities directly within the app authoring environment. This design minimizes the reliance on standalone administrative portals or complex external tools for standard deployment tasks.
The Import Process: When you transport your agent by importing its containing solution into a target downstream environment (such as Test or Production), Copilot Studio prompts you for environment-specific parameters.
Modifying Values: Builders can update the "current value" of environment variables right inside the import wizard panel. Alternatively, you can let them fall back to pre-defined default parameters.
Supported Scenarios: This inline editing mechanism is commonly used to dynamically update variables tied to external resources, such as changing SharePoint URLs or public website links used for generative AI knowledge grounding between sandbox and live states.
Incorrect:
* Publishing an agent to a channel is the required ALM container for transporting agents between environments.
* Publishing an agent to a channel is not the required or correct ALM container for transporting agents between environments.
* To export, import, and manage agents between environments, you need to create and use a custom solution.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/guidance/alm
NEW QUESTION # 63
A company is building a Copilot Studio solution that must answer policy questions, retrieve operational metrics from structured data, and execute authenticated updates in backend systems. The company decides to use multiple specialized agents rather than a single monolithic agent. Custom agents for each capability already exist.
To meet the business requirements, the solution must:
* Retrieve up-to-date metrics from structured data.
* Answer policy questions by using curated knowledge.
* Execute authenticated updates during conversations.
You need to select the appropriate agent design for each requirement.
Which configuration should you use for each requirement? To answer, move the appropriate configurations to the correct requirements. You may use each configuration once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Requirement
Configuration
The solution must retrieve up-to-date metrics from structured data.
Delegate the request to a data-access agent.
The solution must answer policy questions by using curated data sources.
Delegate the request to a knowledge-focused agent.
The solution must execute authenticated updates during conversations.
Delegate the request to a tools-first agent.
A data-access agent is appropriate for operational metrics because it specializes in retrieving current information from structured systems such as Microsoft Fabric, Dataverse, SQL databases, or real-time Power Platform connector sources. Its scope and instructions can be optimized for analytical queries and structured data retrieval.
A knowledge-focused agent is designed around authoritative, curated content such as policy documents, SharePoint libraries, approved websites, and enterprise knowledge bases. Its instructions and knowledge- source descriptions can constrain responses to approved material, making it the appropriate specialist for policy questions.
A tools-first agent is the correct design for authenticated updates. Tools-including connectors, agent flows, REST APIs, custom connectors, and MCP tools-allow an agent to interact with backend systems and perform transactional operations. Connections can use the appropriate user or service authentication strategy, while tool inputs and outputs control the requested update.
Delegating all three responsibilities to a single agent would recreate the monolithic design that the company explicitly wants to avoid. Separating the capabilities improves modularity, privilege isolation, independent maintenance, and orchestration accuracy. The primary agent should use clear connected-agent descriptions so it can select the appropriate specialist at runtime. Relevant study-guide topics are Design multi-agent solutions , Configure multi-agent collaboration , Connect to enterprise knowledge sources , and Add tools to agents . See Multi-agent orchestration patterns and Add tools to custom agents .
NEW QUESTION # 64
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