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| Section | Weight | Objectives |
|---|---|---|
| Test, deploy, and manage agents | 20–25% | - Test and validate agent performance
|
| Plan and configure agent solutions | 30–35% | - Configure agent foundations
|
| Build and extend agents in Copilot Studio | 40–45% | - Develop agent flows and logic
|
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NEW QUESTION # 25
An agent calls a flow to a database. The agent requires structured output values to be returned. The agent receives unexpected or empty values.
You need to configure the agent so that data is exchanged correctly between the agent and the flow. What should you do?
Answer: C
Explanation:
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: The first configuration check is the contract between the agent and the flow. Input and output parameter definitions must agree on name, data type, required status, and mapping. A flow can complete successfully yet return an empty value to the agent if the response field is not mapped to the declared output or if the agent expects a different type.
Validating the parameter definitions therefore addresses the actual data-exchange requirement. Reviewing run history is useful for diagnosis, but it does not correct a mismatched contract by itself. Changing the trigger schema or adding Parse JSON might be necessary in a specific implementation, yet neither should be done before confirming what the caller sends and what the flow returns. Republishing cannot repair an incorrect mapping. The builder should test the flow directly with known values, inspect each action output, verify the final response action, and then test from the agent. Optional and null fields should be handled explicitly, and sensitive outputs should be minimized and protected in logs. Study Guide alignment: Plan and configure agent solutions > Create and monitor agent flows in Copilot Studio > Add input and output parameters.
NEW QUESTION # 26
Drag and Drop Question
A team is preparing a test set to evaluate an agent in Copilot Studio before expanding access to additional users.
The test set must support consistent evaluation across repeated runs and focus on the agent's most important behaviors.
You need to create a test set that enables repeatable and meaningful evaluation.
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:
To establish a repeatable and meaningful evaluation in Microsoft Copilot Studio, you should perform the actions in the following logical order:
Step 1: Identify the high-value conversational intents the agent must handle Focus first on the core business values and critical user goals.
Pinpoint exactly what your agent needs to achieve.
Define the core capabilities (e.g., knowledge base lookups, specific topic flows) the agent must master before expanding access.
Step 2: Author representative user prompts that trigger the identified intents Write various realistic phrases that users will likely use to trigger those core intents.
Step 3: Define the expected outcomes and success criteria for each interaction.
Establish what a correct agent response looks like for each authored prompt.
Step 4: Baseline the test set to ensure deterministic evaluation across repeatable runs.
Lock in your test cases and expected outputs to measure future changes accurately.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/analytics-agent-evaluation-create
NEW QUESTION # 27
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:
NEW QUESTION # 28
Which two actions should you perform before making the agent available on both channels? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.
Answer: B,E
Explanation:
* A. Configure prompt modifications at the system level. Centralized instructions enforce the required tone, disclaimers, response boundaries, and refusal behavior consistently across generative responses.
Microsoft documents that prompt modification can define an agent's personality, response format, permitted subjects, and behavior when an answer is unavailable. This avoids inconsistent manual changes across individual topics. Microsoft: Prompt modification
* D. Configure Power Platform DLP policies. DLP policies govern which connectors, knowledge sources, HTTP endpoints, and channels the agent may use. They should be configured and validated before publication because a policy violation can prevent the agent from being published. DLP also protects against unauthorized data movement between business and non-business connectors.
Microsoft: Data policies for agents
Why the others are incorrect: B creates duplicated, inconsistent disclaimers. C incorrectly treats moderation as a web-channel setting; moderation is configured for generative behavior rather than enforced only by embedding settings. E applies safeguards after publication and assumes filters must be configured separately for every channel, which would not provide the required centralized governance.
NEW QUESTION # 29
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 the creation and use of ALM scenarios for agents in Copilot Studio.
Solution: Builders can change environment-variable values directly in Copilot Studio to complete ALM configuration without administrative tools.
Does the solution meet the goal?
Answer: B
Explanation:
The proposed solution does not meet the goal because environment variables are read-only within Copilot Studio. Agent builders can reference environment variables in topics, tools, formulas, and other agent components, but they cannot directly modify the variables' current values from the Copilot Studio authoring interface.
Environment variables are created and managed through the appropriate Power Platform or Power Apps solution-authoring experience. During an ALM deployment, they separate environment-specific configuration-such as service endpoints, resource identifiers, or other external references-from the agent definition. This separation allows the same solution package to move through development, testing, and production without changing its internal components. Administrators can supply appropriate values during solution import or update the current values in the target environment afterward.
For non-secret environment variables, an agent normally must be republished after an administrator changes a value so that the published runtime uses the updated configuration. Secret environment-variable values are retrieved differently and do not require republishing when changed.
Therefore, the claim that builders can complete this configuration by editing values directly in Copilot Studio is technically incorrect. Relevant AB-620 study-guide topics are Create and use environment variables , Create solutions , and Implement ALM for agents in Copilot Studio . See Variables overview in Copilot Studio
NEW QUESTION # 30
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