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| Section | Weight | Objectives |
|---|---|---|
| Test, deploy, and manage agents | 20–25% | - Deploy and manage agent lifecycle
|
| Build and extend agents in Copilot Studio | 40–45% | - Develop agent flows and logic
|
| Plan and configure agent solutions | 30–35% | - Plan an agent solution
|
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NEW QUESTION # 84
A company wants to use content from a non-Microsoft enterprise knowledge base to ground agent responses.
To meet the business needs, the knowledge source must meet the following requirements:
Support grounding from indexed data.
Use existing access controls from the source system.
Support read-only operations.
You need to determine the correct behavior to meet the requirements.
Which behavior meets each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 85
Drag and Drop Question
A company is preparing an agent flow so that it can be invoked by an agent during conversations.
The agent flow must meet the following requirements:
- The agent must be able to trigger the flow.
- The agent flow must be verified.
You need to prepare an agent flow so that it can be used by the agent.
In which order should you perform the actions to prepare the agent flow? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Step 1: Create a new agent flow artifact in the environment
You must first initialize the flow container within your Copilot Studio workspace before adding any logic.
Step 2: Configure the invocation trigger that allows the agent to call the agent flow You must set up the specialized trigger first (i.e., "When an agent calls the flow"), because this defines the required input variables that the downstream behavioral actions will rely on.
Step 3: Configure the actions that implement the required behavior
With the trigger and input variables established, you build the functional core of the flow (e.g., pulling data, sending approvals) and finalize it with the "Respond to the agent" action.
Step 4: Validate the agent flow behavior with representative test runs
The workflow needs to be tested and verified directly within the flow authoring interface using test data to check for errors before exposing it to the orchestrator.
Step 5: Make the agent flow available for agent usage
Once verified, you publish the flow and add it to your agent as an active tool so the conversational orchestrator can dynamically call it during live interactions.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/flow-agent
NEW QUESTION # 86
A company uses an agent in Copilot Studio to coordinate user interactions.
The company wants the agent to delegate requests to a Microsoft Fabric Data Agent that accesses governed business data.
The agent must retrieve structured analytical data while enforcing data security and scope controls.
You need to select the integration approach that meets the requirements.
What should you use?
Answer: A
Explanation:
To coordinate interactions while accessing governed data, you should create a Microsoft Fabric Data Agent and integrate it into Microsoft Copilot Studio using the Add Agent / Generative Orchestration feature.
Agent-to-Agent Collaboration: Instead of writing custom APIs, you can publish a specialized Fabric Data Agent in Microsoft Fabric, and then simply bind it as an external agent within Copilot Studio.
Built-in Security & Scope: Fabric enforces existing data constraints. Data access runs under the authenticated user's identity, automatically respecting Power BI model-level read permissions, Row-Level Security (RLS), and Object-Level Security (OLS).
Seamless Context: This enables multi-step agent orchestration where Copilot Studio routes queries to the Fabric agent for complex analytical insights (translating natural language to SQL/DAX/KQL) without exposing raw data.
Reference:
https://learn.microsoft.com/en-us/fabric/data-science/data-agent-microsoft-copilot-studio
NEW QUESTION # 87
A company uses a primary agent in Copilot Studio to handle user intake.
For some requests, the company wants the primary agent to delegate work to another Copilot Studio agent that already exists.
To meet the business requirements, the solution must support the following capabilities for the connected agent:
* Allow calls from other agents.
* Allow agents to use the connected agent for collaboration.
* Allow agents to invoke the connected agent during conversations.
You need to integrate the existing Copilot Studio agent with the primary agent.
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:
An existing Copilot Studio agent must satisfy several prerequisites before another agent can invoke it. First, the connected agent must permit incoming agent-to-agent connections. In the connected agent's settings, Let other agents connect to and use this one must be enabled. This corresponds to configuring connections and allows the agent to receive calls from other agents.
Next, the existing agent must be added to the primary agent. From the primary agent's Agents page, the builder selects Add an agent , chooses Copilot Studio , and selects the required published agent. Adding it establishes the collaboration relationship and makes the connected agent available to the primary agent's orchestration process. Its description should accurately identify its capabilities so the primary agent can determine when delegation is appropriate.
Finally, the connected agent must be published. The primary agent can invoke only the published version during runtime conversations. If the connected agent is subsequently changed, it must be published again before the primary agent can use the updated behavior.
Adding the agent as an indexed knowledge source is incorrect because connected agents perform delegated work; they are not document repositories used for retrieval grounding. Relevant study-guide topics are Configure multi-agent collaboration , Integrate an existing Copilot Studio agent , and Design multi- agent solutions . See Connect to an existing Copilot Studio agent .
NEW QUESTION # 88
Case Study 2 - Fabrikam Inc.
Background
Fabrikam Inc. is a Canada-based manufacturer with a growing service organization that supports field technicians and internal operations teams. Fabrikam Inc. plans to launch a new internal agent solution named Operations Concierge to reduce time spent searching policy content, retrieving operational metrics, and executing routine transactions.
The agent will be used by three groups:
- Service coordinators who triage incoming service requests
- Field technicians who need guided procedures and parts availability
- Operations managers who monitor KPIs and exceptions
The agent solution must work in real-world operational conditions. Users often ask questions mid- call with a customer or while coordinating parts shipments. The agents require quick, reliable outcomes. As a result, Fabrikam Inc. requires the solution to:
- Provide grounded answers with traceability when it provides guidance.
- Retrieve real-time metrics when users ask for operational status.
- Execute authenticated updates when users initiate a flow (such as creating a parts request).
Fabrikam Inc. also expects the solution to be maintained by multiple makers and developers across the year. The company has experienced duplicated logic and inconsistent behavior across different agents. This project emphasizes reuse, governance, and maintainability across teams.
Current environment
Fabrikam Inc. runs three Microsoft Power Platform environments for agent development and release: Dev, Test, and Prod.
The team plans to build the agent and validate it in Dev and Test, then promote to Prod by using a controlled release process that supports repeatable deployments.
Fabrikam Inc. already has two assets the team wants to reuse:
- A partially completed Copilot Studio agent named Service Desk Agent, used by IT to create internal tickets and route requests
- A Microsoft Foundry agent created by a central AI team that performs specialized summarization and classification for long-form text (for example, summarizing call transcripts into an incident narrative) Fabrikam Inc. also has operational and knowledge data sources:
- A curated policy library (internal SOPs, service warranty rules, escalation criteria, and standard operating procedures)
- A set of indexed documents and procedures in an Azure AI Search service that supports vector search for the policy library
- A Microsoft Fabric workspace that includes a semantic model used by operations leadership for reporting Business requirements Fabrikam Inc. requires Operations Concierge to meet the following business requirements:
- Traceability requirement: When the agent provides policy guidance or procedural recommendations, users must be able to see where the answer came from.
- Metrics requirement: When users ask about service performance (backlog, SLA risk, parts shortages, dispatch delays), the solution must return up-to-date metrics in a structured format that operations managers can use in weekly reviews.
- Transaction requirement: The solution must support authenticated updates initiated during conversations, including creating a parts request and updating a service case status.
In addition, Fabrikam Inc. wants to avoid duplicating common assets across agents:
- The team must reuse the same set of escalation topics, MCP tool definitions, and a standard safety disclaimer across three different agents.
- Only the platform engineering group as allowed to edit shared assets. However, all agent authors must be able to use them.
Technical requirements
The Fabrikam Inc. solution architecture uses a multi-agent approach so that specialist responsibilities are isolated and can evolve independently.
The Operations Concierge (primary agent) must coordinate the following specialist capabilities:
- Policy and procedure Q&A: Use an enterprise knowledge source that supports indexed retrieval across the curated policy library and service procedures.
- Operational metrics: Delegate metric queries to a Fabric Data Agent that reads governed business data through the Fabric semantic model.
- Authenticated updates: Use tools exposed by an existing internal Model Context Protocol (MCP) server that provides transactional operations for the service organization.
- Specialized processing: Delegate summarization and classification requests to an existing Microsoft Foundry agent.
Fabrikam Inc. will onboard two MCP servers as tools:
- PartsOps MCP server: exposes tools for parts availability checks and parts request creation.
The server requires per-user authentication because actions must be traceable to the requesting user.
- WarrantyRules MCP server: exposes a read-only tool for validating warranty coverage. The server uses an API key shared by the agent team.
Fabrikam Inc. has also defined a collaboration requirement with the existing Service Desk Agent:
- The primary agent must delegate IT-specific requests to the existing Service Desk Agent rather than reimplement ticket creation logic.
Finally, Fabrikarn Inc. plans to support a partner integration:
- For shipment tracking inquiries, Fabrikam Inc. will delegate to a partner-provided agent that is only available through a standardized agent-to-agent endpoint.
Issues and constraints
During early testing, Fabrikam Inc. found three recurring problems:
- Makers are copying and modifying the same components across agents, resulting in inconsistent disclaimers and duplicated tools.
- Users can obtain a correct answer, but the response is not consistently traceable to a source when the agent uses knowledge.
- The primary agent can route some requests, but specialist capabilities are not consistently delegated (for example, some metric questions are answered generatively instead of being routed to the Fabric Data Agent).
You are part of the engineering team responsible for correcting the design and configuration to meet the preceding requirements and constraints.
Drag and Drop Question
You need to design a solution that provides Fabrikam Inc. with a multi-agent design approach with existing agents.
Which approach should you use for each requirement? To answer, move the appropriate approaches to the correct requirements. You may use each approach once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Delegate the request to a knowledge-focused agent
Scenario: Traceability requirement: When the agent provides policy guidance or procedural recommendations, users must be able to see where the answer came from.
The best action to take is to delegate the request to a knowledge-focused agent.
Pure Grounding and Citation Support: In Microsoft Copilot Studio and the Power Platform ecosystem, a knowledge-focused agent is explicitly engineered to retrieve information from designated repositories (such as SharePoint sites, Dataverse tables, or uploaded company policy manuals).
Built-in Transparency: When an agent relies on custom knowledge sources via Retrieval- Augmented Generation (RAG) or generative answers, it inherently provides inline citations and source links. This allows users to immediately verify exactly where the policy guidance or procedural recommendations originated.
Box 2: Delegate the request to a data-access agent.
Scenario: Metrics requirement: When users ask about service performance (backlog, SLA risk, parts shortages, dispatch delays), the solution must return up-to-date metrics in a structured format that operations managers can use in weekly reviews.
The best action to take is to delegate the request to a data-access agent.
Governed and Current Business Data: Tracking active metrics like backlog, SLA risk, and shortages demands direct, real-time query access to structured enterprise data stores (such as Microsoft Fabric or Microsoft Dataverse).
Optimized for Structured Reporting: Data-access specialists focus specifically on retrieving, grouping, and structuring current operational facts into accurate, review-ready formats for management.
Role Distinction: In contrast, a tools-first agent is designed primarily to trigger transactional processes or workflows across external systems (e.g., executing a parts request or updating a service case ticket) rather than retrieving and aggregating high-level analytics.
Box 3: Delegate the request to a tools-first agent.
Scenario: Transaction requirement: The solution must support authenticated updates initiated during conversations, including creating a parts request and updating a service case status.
The best action to take is to delegate the request to a tools-first agent.
Action-Oriented Design: A tools-first agent is specifically optimized to perform tasks, run workflows, and execute transactional actions-such as creating parts requests and updating status fields.
API Integration: It excels at leveraging connectors and Power Automate cloud flows to securely push updates back into your Microsoft Power Platform environment.
Separation of Concerns: Delegating to a specialized tools-first agent keeps your orchestration layer lightweight and prevents a single agent from becoming too complex to maintain.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-copilot-studio
NEW QUESTION # 89
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