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| Section | Weight | Objectives |
|---|---|---|
| Plan and Configure Agent Solutions | 30-35% | - Plan agent solutions
|
| Test and Manage Agents | 20-25% | - Monitor and manage agent solutions
|
| Integrate and Extend Agents in Copilot Studio | 40-45% | - Integrate agents with enterprise systems
|
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NEW QUESTION # 43
A company has an approved custom connector that uses a REST API for an internal system.
An agent in Copilot Studio must call this connector during conversations to retrieve or update data.
To meet the business needs, the solution must meet the following requirements:
Make the connector actions available for the agent to invoke.
Ensure authentication is handled at the service level, not per user.
Pass conversation context into the connector when it is called.
Surface the returned data of the connector to the user in the conversation.
You need to configure the agent and the connector action to meet the requirements.
What should you configure 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. 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:
Requirement
Correct configuration
Make connector actions available for the agent to invoke.
Add the connector as a tool in the agent.
Handle authentication at the service level, not per user.
Create or reuse a connection for the connector.
Pass conversation context into the connector when called.
Map topic variables to the tool inputs.
Surface the connector's returned data to the user.
Parse the JSON response and assign it to a topic variable.
Adding the approved connector as an agent tool exposes its defined REST operations to Copilot Studio. The tool can then be called explicitly from a topic or selected dynamically by generative orchestration, depending on its configuration.
A connector connection stores the authentication configuration required to call the underlying service. Among the provided choices, creating or reusing that connection is the correct service-authentication action. For strict service-level authentication, the tool must additionally be configured under Credentials to use with Maker- provided credentials . Creating a connection alone does not guarantee this behavior if the tool remains configured to use end-user credentials.
Topic variables containing conversation context-such as a customer identifier, ticket number, or requested operation-are mapped to the connector tool's input parameters. This ensures the REST request receives values collected earlier in the conversation.
When the connector returns structured JSON, the relevant values must be parsed and stored in a topic variable. That variable can then be referenced in a message, adaptive card, or subsequent topic node to present the returned information to the user.
Relevant study-guide area: Integrate and extend agents in Copilot Studio # Add tools to agents # Add a tool by using an existing custom connector . See Use connectors in Copilot Studio agents and Add tools to custom agents .
NEW QUESTION # 44
Case Study 1 - Blue Yonder Airlines
Background
Blue Yonder Airlines is a global carrier headquartered in Los Angeles, California, operating domestic and international flights. The company serves millions of passengers annually through its website, mobile app, and call centers. To improve customer service efficiency and reduce call center volume, Blue Yonder is deploying an AI agent in Microsoft Copilot Studio.
The agent will handle customer inquiries across multiple channels - web chat, mobile app, and Microsoft Teams (for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human agents when needed.
The project is led by a cross-function team:
- Product manager: Defines requirements and success metrics.
- Lead agent author: Designs topics, intents, and generative behavior.
- Flow designers: Build agent flows and integrations.
- IT/security and compliance: Oversees identity, data protection, and Responsible AI (RAI) compliance.
Current environment
Channels
Public website: Embedded web chat
Mobile app: In-app chatbot
Microsoft Teams: Internal support agent access
Identity and access
Customers: Anonymous access for general inquiries (e.g., flight status, baggage policy).
Authentication is required for personal data access (e.g., bookings, loyalty points).
Internal staff: Authenticate via Microsoft Entra ID.
Data sources
Reservation and Ticketing System (internal): REST API, no prebuilt connector with custom enterprise database.
Flight Status and Weather APIs (external): REST APIs with API keys.
Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Loyalty Program Data: Stored in Dynamics 365 and Dataverse.
Travel Advisory Content: Uses REST API with partner services.
Integration mechanisms
Custom connectors must be used for internal APIs that lack prebuilt connectors.
HTTP request nodes may be used for lightweight external APIs.
Knowledge sources must be used for unstructured content.
Agent flows must be used to encapsulate reusable logic (e.g., rebooking).
Business requirements
Omnichannel support
Deploy the agent across web, mobile, and Teams with a consistent user experience. The Teams deployment must also support internal staff.
Self-service capabilities
The agent must handle common inquiries such as:
- Flight status
- Booking and rebooking
- Loyalty program questions
- Travel policies and baggage rules
Human escalation
If the agent cannot resolve an issue or the user requests help, it must:
- Escalate to a human agent.
- Transfer the conversation transcript and relevant context.
- Redact any sensitive personal data before escalation.
Knowledge integration
The agent must use scalable methods for knowledge integration and must not rely on manually authored Q&A topics for each document.
Performance metrics
First-contact resolution: +25%
Tier-1 call deflection: ≥20%
Response time: 90% of queries answered within 30 seconds
Accuracy: ≥95% for known FAQs
CSAT: ≥85% for AI-handled interactions
Technical requirements
Platform constraints
No custom code is permitted; only Copilot Studio's built-in tools may be used.
All backend logic must be implemented using agent flows.
Markdown must be used for formatting (e.g., bold, bullet points); HTML is not supported.
Authentication
Sign-in is required for personal data access.
Anonymous access is allowed for general inquiries.
User identity must be used for data access; shared or builder credentials must not be used.
Compliance and security
Power Platform DLP policies must be enforced to block unauthorized data flows.
Responsible AI content moderation filters must be enabled.
Prompt modifications must be added to enforce tone, disclaimers, and refusal behavior.
Disclaimers must be applied consistently across all generative responses. Manual edits to individual topics must be avoided.
Monitoring and maintenance
All conversations and actions must be logged for auditing.
Weekly reviews of transcripts and metrics must be conducted.
Topics, flows, and knowledge sources must be updated as policies or systems evolve.
Issues and constraints
API rate limits: External APIs (e.g., flight status) have usage limits. Agent flows must handle retries and caching to avoid exceeding quotas.
Knowledge base limits: Copilot Studio has limits on the number and size of indexed documents.
Large files must be split or summarized.
Generative answer risks: Generative responses must be constrained to avoid policy violations.
Prompt modifications and filters must be used to enforce tone, safety, and compliance.
User input variability: Users phrase questions in diverse ways. Topics must include varied trigger phrases and fallback handling.
Authentication UX: The agent must clearly explain when sign-in is required and handle transitions smoothly across channels.
Problem statement
Blue Yonder Airlines must deploy a secure, scalable, and policy-compliant AI agent using Microsoft Copilot Studio. The agent must deliver accurate, helpful, and safe responses across multiple channels, integrate with enterprise systems, and support both anonymous and authenticated users. It must adhere to strict data protection and Responsible AI standards while improving customer service efficiency and satisfaction.
You need to configure the agent in Copilot Studio to use internal and external partner knowledge sources to answer user questions about the airline services.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: A,D
Explanation:
[A] External
Scenario:
Data sources include:
Travel Advisory Content: Uses REST API with partner services.
Configuring a Microsoft Graph connector to index your external data and utilizing REST APIs are highly effective and distinct strategies for supplying knowledge and actions in Microsoft Copilot Studio.
[D] Internal
Scenario:
The agent will handle customer inquiries across multiple channels - web chat, mobile app, and Microsoft Teams (for internal support staff). It will answer questions, retrieve data from enterprise systems, and escalate to human agents when needed.
Data sources include: Customer Support Knowledge Base: SharePoint library with PDFs and policy documents.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-copilot-connectors
NEW QUESTION # 45
A solution containing an agent in Copilot Studio is moved across environments. The agent relies on configuration values that are different between environments and are managed as environment variables.
You must ensure the following:
- Configuration values are managed through environment variables that
supports ALM.
- Runtime behavior reflects updates to environment variable values.
You need to implement environment-variable usage that supports ALM and ensures correct runtime behavior.
Which three actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
Answer: B,C,F
Explanation:
[C]
Environment variables are read-only within Copilot Studio. Agent authors and builders cannot modify their values directly during topic authoring; changes must be done by administrators inside Power Apps to safeguard Application Lifecycle Management (ALM) integrity.
[D]
ALM Separation: Environment variables separate configuration settings from the application logic.
This means your agent's structure and topics stay exactly the same, while environment-specific parameters (such as API endpoints, URLs, or IDs) automatically adapt based on whether the solution is sitting in Dev, Test, or Production.
[F]
Copilot Studio caches environment variable values to optimize performance during conversation runtime. When an administrator updates a value in a target environment, the copilot will continue using the old cached value until a builder opens the agent and clicks Publish. This manual republication flushes the cache and pushes the new variable configuration into the live runtime environment.
Incorrect:
[Not A]
Hard-coding configuration values completely defeats the purpose of Application Lifecycle Management (ALM). It forces manual edits in every environment, introduces human error, and violates the core requirement of using environment variables.
[Not B]
Allowing builders to edit environment variable values directly within Copilot Studio during topic authoring can inadvertently bake "current values" into the solution package. This disrupts ALM pipelines, causes unintended configuration overwrites when moving solutions between Development, Test, and Production environments, and bypasses proper administrative controls.
[Not E]
Environment variable updates do not take effect immediately for all variable types at runtime. In Copilot Studio, the published version of an agent bakes in the current values. Whenever an administrator updates an environment variable, you must republish the agent for those changes to reflect in the live runtime experience.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/authoring-variables-about
NEW QUESTION # 46
You need to configure generative answers so the agent meets Fabrikam Inc.'s business requirements Which solutions should you use? To answer, move the appropriate solutions to the correct requirements. You may use each solution 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:
NEW QUESTION # 47
A company uses multiple Copilot Studio agents that perform specialized tasks.
The company needs to enable one agent to directly delegate and invoke another agent within Copilot Studio by using a standard Copilot Studio interface.
You need to configure collaboration among agents by using Copilot Studio.
What should you do?
Answer: A
Explanation:
The correct step to take is to provide A2A (Agent-to-Agent) endpoint information for the target agent.
Standard Multi-Agent Protocol: The Agent-to-Agent (A2A) protocol is the open, standard framework specifically designed to allow independent agents to directly communicate, discover capabilities via agent cards, and delegate workflows across standard interfaces. Providing the A2A endpoint information allows the orchestrating agent to securely hand off specialized tasks to the target agent.
Incorrect:
[Not A]
Adding the target agent as a Microsoft Fabric Data Agent is a separate, specialized pattern reserved strictly for reasoning over heavy data science pipelines and querying enterprise data lakes (like Lakehouses or Semantic Models). It is not used for standard cross-framework agent collaboration or general delegation within the native Copilot Studio interface.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/agents-experience/add-agent-connected
NEW QUESTION # 48
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