Japancertを手に入れるのは、MicrosoftのAB-620認定試験に合格する鍵を手に入れるのに等しいです。Japancertの MicrosoftのAB-620試験トレーニング資料は高度に認証されたIT領域の専門家の経験と創造を含めているものです。その権威性は言うまでもありません。あなたはうちのMicrosoftのAB-620問題集を購入する前に、Japancertは無料でサンプルを提供することができます。
| Section | Weight | Objectives |
|---|---|---|
| Test and Manage Agents | 20-25% | - Monitor and manage agent solutions
|
| Plan and Configure Agent Solutions | 30-35% | - Plan agent solutions
|
| Integrate and Extend Agents in Copilot Studio | 40-45% | - Integrate agents with enterprise systems
|
市場で最高のAB-620テストトレントを提供する世界的なリーダーとして、Japancertは、専門家によって何度もチェックされているAB-620試験問題の更新情報を提供することを約束し、消費者の大半が、統合サービスの構築に努めています。さらに、認定トレーニングアプリケーションだけでなく、インタラクティブな共有とアフターサービスでも画期的な成果を達成しました。 AB-620トレーニングブレインダンプを購入する価値があります。
質問 # 52
Drag and Drop Question
A company has an Azure AI Search vector index that contains enterprise content and wants to use it as a knowledge source for an agent in Copilot Studio.
To meet business needs, the knowledge source must meet the following requirements:
- The agent must connect to the Azure AI Search service.
- The agent must use a supported authentication method for the
connection.
- The agent must ensure answers are grounded using the specified Azure
AI Search index.
You need to connect to Azure AI Search as a knowledge source for the agent.
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.
正解：
解説：
Explanation:
Step 1: Initiate the process to add a knowledge source to the agent
You start inside Copilot Studio by navigating to your agent's settings and choosing to add a new knowledge source.
Step 2: Create a new Azure AI Search connection
From the available knowledge source options, you select Azure AI Search, which prompts the creation of a new connection.
Step 3: Configure the authentication method and provide the required connection details You input the necessary credentials (such as your Azure AI Search endpoint and API key or OAuth details) to authenticate the connection securely.
Step 4: Specify the Azure AI Search index to use for grounding
Once connected, you select the specific vector index that contains your enterprise content so the model knows where to look.
Step 5: Associate the configured knowledge source with the agent
Finally, you save and link this configured search source to the agent, enabling it to ground its responses using your enterprise data.
Reference:
https://learn.microsoft.com/en-us/microsoft-copilot-studio/knowledge-azure-ai-search
質問 # 53
Hotspot Question
You run multiple evaluation tests for an agent in Copilot Studio before expanding user access.
The tests provide the following results:
- Each evaluation case is reported as meeting or missing the expected
response.
- Some evaluation cases fail repeatedly across several runs.
- Each run displays the expected response and the response generated by the agent.
You need to provide a conclusion based on the evaluation results.
Which conclusions should you make? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
正解：
解説：
Explanation:
Box 1: Pass or fail status
Based on the testing criteria in Microsoft Copilot Studio, the outcome described directly measures the Pass or fail status of your tests.
Pass or fail status: This is the primary conclusion. Microsoft Copilot Studio Agent Evaluation uses structured methods (such as Exact Match, Similarity, or Compare Meaning) to objectively check if your agent met or missed the expected responses in your test set.
Box 2: Consistent outcomes
The conclusion to make from this is Consistent outcomes.
When evaluation test cases fail repeatedly across several runs, it indicates a stable, reproducible issue with the agent's behavior rather than random variability. Because the agent produces the same failure under the same test conditions, you have consistent outcomes.
Box 3: Expected and generated response
From the multiple evaluation tests in Microsoft Copilot Studio, the primary conclusion you can make is regarding the expected and generated responses.
This specific test output allows you to directly assess the alignment between what the AI was anticipated to say (the expected response) and what it actually produced (the generated response). By contrasting these, you can analyze semantic similarity, intent, and overall quality.
Reference:
https://www.microsoft.com/en-us/microsoft-copilot/blog/copilot-studio/how-to-evaluate-ai-agents/
質問 # 54
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.
正解：
解説：
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 .
質問 # 55
A company must enable an agent in Copilot Studio to execute operations exposed by an external MCP server.
The MCP server publishes callable tools and requires authentication.
The agent must be able to invoke MCP tools during conversations.
You need to configure MCP tools so the agent can execute MCP tool calls.
What should you do?
正解：A
質問 # 56
An agent calls a flow that intermittently produces unexpected results during execution. The agent behaves inconsistently.
You need to investigate agent flow executions to diagnose the issue.
Which two actions should you use? Each correct answer presents a complete solution. Choose two. NOTE:
Each correct selection is worth one point.
正解：D、E
解説：
Comprehensive and Detailed Explanation From Microsoft AB-620 Study Guide: Flow run history provides the chronological record needed to identify which executions succeeded, failed, timed out, or behaved differently. Opening the failed run details then exposes the action-level inputs, outputs, status, duration, connection errors, and failure message that explain the inconsistent result. These two views support evidence-based diagnosis without changing the flow before the cause is known. Updating the trigger, increasing a timeout, or changing connection behavior are potential remediations only after the failure pattern has been established. The Analytics summary is useful for aggregate trends but lacks the full payload and step sequence of an individual run. The Activity tab ' s Error column can help locate failures, but the question asks for the two complete diagnostic actions and the detailed run inspection is the more direct evidence. Reviewers should compare a failed run with a successful run using the same input, check transient versus deterministic errors, and redact or restrict access to sensitive data captured in run history. Study Guide alignment: Plan and configure agent solutions > Create and monitor agent flows in Copilot Studio > Monitor agent flows.
質問 # 57
......
あなたのキャリアでいくつかの輝かしい業績を行うことを望まないのですか。きっとそれを望んでいるでしょう。では、常に自分自身をアップグレードする必要があります。では、IT業種で仕事しているあなたはどうやって自分のレベルを高めるべきですか。実は、AB-620認定試験を受験して認証資格を取るのは一つの良い方法です。Microsoftの認定試験のAB-620資格は非常に大切なものですから、Microsoftの試験を受ける人もますます多くなっています。
AB-620科目対策: https://www.japancert.com/AB-620.html