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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Test, deploy, and manage agents | 20โ25% | - Test and validate agent performance
|
| Topic 2: Plan and configure agent solutions | 30โ35% | - Plan an agent solution
|
| Topic 3: Build and extend agents in Copilot Studio | 40โ45% | - Implement advanced capabilities
|
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NEW QUESTION # 17
Hotspot Question
A company uses an agent that invokes an agent flow to exchange information during a conversation.
The company requires that the agent send data into the flow and receive structured results back from the same flow run. To support this business need, the flow must be configured to do the following:
- Capture the data provided by the agent.
- Return data results to the agent.
You need to configure the flow so that it can exchange data with the agent.
What 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:
Explanation:
Box 1: Add a text input parameter
To allow a Copilot Studio agent to pass data into a flow and receive structured results back, you must configure a Power Automate flow triggered by the "Run a flow from Copilot" trigger with custom input variables, and concluding with the "Respond to Copilot" action containing structured output parameters.
Box 2: Add a text output parameter
To return structured results from an agent flow to your agent in Microsoft Copilot Studio, you should configure the "Respond to the agent" action in your flow with an output parameter.
In Microsoft Copilot Studio, when a topic or bot calls a Power Automate flow, data is sent into the flow via input parameters. To pass data, objects, or structured results back to the copilot during the exact same flow run, you must explicitly define one or more output parameters (such as a text, number, or boolean output) in the "Return value(s) to Power Virtual Agents/Copilot Studio" final step of the flow.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/advanced-use-flow
NEW QUESTION # 18
You need to enable Operations Concierge to delegate shipment tracking inquiries according to Fabrikam Inc. ' s defined architecture and technical requirements.
Which integration approach should you use?
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: The partner capability is described as an agent available only through a standardized agent-to-agent endpoint. That is the defining use case for an Agent2Agent connection. In Copilot Studio, the primary agent is configured with the external agent ' s A2A message endpoint and the applicable authentication details, after which orchestration can delegate shipment-tracking requests to it. An MCP server exposes tools or resources rather than an independently orchestrated partner agent, so option C changes the integration contract. An indexed knowledge source is also unsuitable because shipment status is dynamic and the requirement is delegation, not retrieval from a copied corpus. Generative responses in the primary agent would have no authoritative live shipment source and would violate the defined architecture. The A2A description should identify shipment tracking precisely so that it does not compete with unrelated agents or tools. Because external-agent support can be preview functionality, Fabrikam should also validate regional availability, authentication, error behavior, latency, and governance before production use. Study Guide alignment: Integrate and extend agents in Copilot Studio > Configure multi-agent collaboration from Copilot Studio > Create a multi-agent solution by using A2A protocol.
Topic 1, Fabrikam inc.
Background Current Environment:
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.
Business Requirements:
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 is allowed to edit shared assets. However, all agent authors must be able to use them.
Technical Requirements:
The Fabrikam Inc. ' s 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, Fabrikam 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.
NEW QUESTION # 19
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 # 20
A company wants an agent to retrieve real-time answers from a large, frequently updated document repository stored outside Dataverse, with strong relevance ranking. Which knowledge source should you configure?
Answer: A
Explanation:
Azure AI Search provides indexed, relevance-ranked retrieval over large and frequently updated content, making it the preferred grounding source for enterprise-scale RAG scenarios compared to static file uploads.
NEW QUESTION # 21
A development team is reusing agents in Copilot Studio across development, test, and production environments.
You need to ensure the agents meet the following requirements:
Reusable components must support governed promotion across environments.
Environment-specific configuration must not be hard-coded.
Deployments must support automated, multi-stage approvals.
You need to configure the agents based on the business requirements.
Answer:
Explanation:
NEW QUESTION # 22
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