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| Section | Weight | Objectives |
|---|---|---|
| Orchestrate multi-agent coordination | 15–20% | - Configure observability for multi-agent behavior by using logs, artifacts, and operational signals
|
| Prepare agent architecture and SDLC processes | 15–20% | - Integrate agents into the software development lifecycle (SDLC)
|
| Manage memory, state, and execution | 10–15% | - Ensure continuity of agent memory and state across tools and environments
|
| Implement tool use and environment interaction | 20–25% | - Integrate agents within development environments
|
| Perform evaluation, error analysis, and tuning | 15–20% | - Analyze agent failures and identify root causes
|
| Implement guardrails and accountability | 10–15% | - Define autonomy levels
|
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NEW QUESTION # 68
Hotspot Question
Your company uses Microsoft Visual Studio Code and GitHub Copilot Chat.
You have a GitHub repository that uses main as the default branch. The repository contains a workspace custom agent stored at .github/agents/release-notes.agent.md.
A developer switches to a branch named branch1 where the agent file does NOT exist. In the same session, the developer switches to a user profile named profile1.profile1 contains a custom agent file named release-notes.agent.md that has user-invokable set to false.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: No
The agent will not appear in the agents dropdown with a display name of release-notes because the developer is currently on branch1 and profile1, which effectively hides it.
Box 2: No
The workspace version of the release-notes agent will not be available in the agents dropdown when the developer is on branch2.
Box 3: No
The user profile agent will not appear in the agents dropdown, nor will it override a workspace agent in this scenario.
Reference:
https://code.visualstudio.com/docs/agent-customization/custom-agents
NEW QUESTION # 69
Case Study 1 - Contoso, Ltd
Overview
Contoso Ltd. is a software development company located in the United States.
Existing Environment
GitHub Environment
Contoso uses GitHub Enterprise and assigns GitHub Copilot Pro+ licenses to its developers. The developers use Microsoft Visual Studio Code as their IDE.
Contoso has a customer portal. The code for the portal is stored in a GitHub repository named repo1that contains the following:
- A custom agent named agent1 that includes instructions to review specs related to best practices
- A custom instruction file named validate-instructions.md that is used to validate tone of voice and applies to all .md and .txt files
- A custom instruction file named codereview.instructions.md that is used by the Copilot coding agent but is excluded for use by the Copilot code review repo1 has the following structure:
- The front-end is stored in the /frontend folder.
- The API logic is stored in the /api folder.
Contoso has a second repository named repo2 that contains a legacy .NET application named App1 built by using .NET 6. repo2 has a multi-agent workflow for modernization tasks.
Contoso enables the Model Context Protocol (MCP) registry and allows the Microsoft Learn MCP Server. Every developer must configure their own connection to the Learn MCP Server.
Problem Statements
The developers working in repo1 report that the Microsoft Learn documentation is NOT being retrieved when they attempt to validate a design by using agent1.
The testing team at Contoso identifies that the customer portal uses inconsistent UI styles, which leads to customer confusion and branding issues. The UI inconsistencies stem from variations in the folder structure.
Agent Logs
You have the following logs for the multi-agent workflow used in repo2.
Requirements
Planned Changes
Contoso plans to have all agents and developers in repo1use the Microsoft Learn MCP to ensure that reviews are validated by using the appropriate documentation. This must be implemented centrally.
Contoso plans to leverage AI-powered coding agents to implement new portal features and pages.
Technical Requirements
App1 must be upgraded to .NET 10. A previous upgrade attempt was started by using the Copilot modernization agent, but the attempt was never finalized.
You plan to retry the upgrade. You must first analyze App1 by using AI, and then generate a report that contains breaking changes and deprecated patterns before retrying the upgrade.
All AI-generated code for UI styling must adhere to a predefined folder structure.
The architects at Contoso need help building implementation plans for repo1. The company wants to implement a new agent named agent2 to analyze the code base and the code requirements, and then respond with a detailed plan. The agent must NOT be able to edit files or run local commands.
The developers must be able to delegate work to the Copilot coding agent by assigning issues to the agent.
Hotspot Question
You need to implement agent2 to meet the technical requirements.
How should you complete the YAML configuration? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: 'search',
Search allows the agent to look for specific keywords, classes, or patterns across your repository to understand the current structure and code requirements.
Box 2: 'read'
Read grants the agent read-only permission to examine the full contents of the codebase files without having the capability to alter them.
Reference:
https://github.com/github/copilot-cli/issues/1663
NEW QUESTION # 70
An agentic coding session in the terminal has grown too long, and you want to discard all prior conversation history and start clean, without summarization. Which slash command should you run?
Answer: A
Explanation:
/clear wipes the entire conversation history and starts a fresh session. This differs from /compact, which summarizes history to save tokens while retaining prior progress.
NEW QUESTION # 71
You have a GitHub Enterprise repository that uses the GitHub Copilot coding agent and opens draft pull requests for assigned issues.
Evaluation results show that the agent repeatedly opens pull requests that modify .github/workflows/*.yml to bypass failing checks instead of fixing the underlying code.
You need to ensure that the agent fixes the underlying code instead of bypassing the failing checks.
What should you do?
Answer: C
Explanation:
A properly configured branch ruleset establishes enforcement outside the agent's editable task instructions. It can require pull requests, successful checks, and appropriate reviews before changes enter protected branches. In an enterprise setup, required workflows can also be governed centrally so that changing a repository-local workflow does not remove the organization's validation requirement.
The ruleset must be configured to preserve the intended checks. Merely creating an empty ruleset does not solve the problem, and requiring a check whose implementation the agent can freely weaken is insufficient. Protecting workflow changes through required ownership review or centrally managed validation addresses that remaining gap. The agent should not receive bypass permission for these controls.
Option A increases authority rather than constraining the unwanted behavior. Option C removes the checks that are supposed to detect defective code. Option D affects treatment of untracked files and does not prevent changes to already tracked workflow definitions.
The control cannot guarantee successful reasoning, but it can prevent acceptance of a shortcut that defeats validation.
Relevant curriculum topics are blocking prohibited actions, enforcing independent controls, and correcting undesirable behavior identified through evaluation.
Reference:
NEW QUESTION # 72
Drag and Drop Question
You have a GitHub repository that has a GitHub Actions workflow. The workflow runs an AI agent.
You need to ensure that the default GITHUB_TOKEN permissions are read-only, and write access is granted to only the job that performs repository write operations. The workflow must be able to create and approve pull requests only when explicitly enabled.
How should you complete the workflow? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
How should you complete the workflow?
Box 1: contents: read
Set Global Read-Only Permissions
To enforce the principle of least privilege, the top-level permissions block must strip all default write capabilities from the GITHUB_TOKEN. Setting contents: read allows the workflow to fetch the code but prevents any accidental repository modifications.
Box 2: contents: write
Grant Job-Level Write Access
Only the specific job responsible for modifying the repository should receive write access. The update_artifacts job requires permission to push code modifications back to the repository.
Box 3: pull-requests: write
To successfully create and approve pull requests, you must explicitly enable this capability in your GitHub repository settings:
Reference:
https://docs.github.com/en/organizations/managing-organization-settings/disabling-or-limiting-github-actions-for-your-organization
NEW QUESTION # 73
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