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| Section | Weight | Objectives |
|---|---|---|
| Design agentic AI solutions | 25% | - Design agent architecture
|
| Test, deploy, and monitor agentic AI systems | 20% | - Deploy and monitor agents at scale
|
| Implement agents and multi-agent systems | 30% | - Orchestrate multi-agent collaboration
|
| Integrate tools, data, and services | 25% | - Connect data sources and knowledge bases
|
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NEW QUESTION # 103
Drag and Drop Question
You have a GitHub repository that uses a custom GitHub Copilot coding agent defined in the rollout-bot.agent.md file.
You need to update a workflow so that agent-profile changes can be rolled back by reverting a single commit and rerunning the workflow. The workflow must check out the exact commit being deployed and apply the agent profile from the repository at that commit.
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:
Box 1: inputs.ref
The specific commit being targeted.
Box 2: agents/rollout-bot.agent.md
The profile file to validate
Box 3: ${{ github.sha }}
The exact commit ref that the checkout action fetched
Reference:
https://octopus.com/devops/github-actions/github-actions-workflows/
NEW QUESTION # 104
You have a repository on github.com that uses the GitHub Copilot coding agent.
You also use the GitHub Copilot CLI locally to reproduce failures and continue the same work from your terminal.
You need to verify the current token usage.
Which Copilot CLI slash command should you run?
Answer: A
Explanation:
To verify your current token usage in the GitHub Copilot CLI, you should run the /context slash command.
When you execute /context during your interactive terminal session, it visualizes your context window breakdown. It helps you track token consumption by explicitly mapping out:
The active AI model being used.
The number of used tokens versus total capacity.
Token distribution among the System Prompt, System/MCP Tools, and active Message History.
Remaining Free Space and reserved response buffers.
Reference:
https://docs.github.com/en/copilot/how-tos/copilot-cli/use-copilot-cli/overview
NEW QUESTION # 105
You are running the GitHub Copilot CLI and want the agent to execute file edits and shell commands without prompting for confirmation on each individual action, during a trusted throwaway sandbox session. Which flag/command should you use?
Answer: B
Explanation:
The --allow-all (commonly nicknamed "YOLO mode") flag disables per-action confirmation prompts, letting the agent run autonomously. This should only be used in isolated, low-risk environments since it removes a key safety checkpoint.
NEW QUESTION # 106
You want to grant the Copilot coding agent access to only a narrowly scoped set of repository permissions (e.g., read code, write pull requests) rather than full admin access. What governs this scope?
Answer: A
Explanation:
The coding agent operates using a scoped GitHub token whose permissions are configured at the repository or organization level, following the principle of least privilege -- granting only what's needed (e.g., contents: write, pull-requests: write).
NEW QUESTION # 107
In Microsoft Visual Studio Code, you are using GitHub Copilot Chat to generate documentation for a new feature.
Earlier in the day, you used Copilot Chat extensively for an unrelated refactoring task.
You discover that the Copilot responses for the new documentation task are influenced by the earlier conversation.
You need Copilot to focus only on the current task and avoid using prior conversational context. The solution must NOT affect other conversations.
What should you do?
Answer: A
Explanation:
Starting a new Copilot Chat conversation establishes a separate conversational context for the documentation task. The unrelated refactoring exchanges remain in their original conversation instead of continuing to influence the new thread. This directly addresses the requirement to separate tasks while preserving other conversations.
Conversation history contributes information beyond the latest prompt. Earlier instructions, assumptions, terminology, and design decisions can continue to affect subsequent responses within the same session. A fresh conversation provides a clear task boundary, allowing the developer to supply the feature requirements and relevant documentation context explicitly.
Changing from sidebar chat to inline chat changes the interaction surface; it does not provide the same explicit separation of conversational history. Referencing a file supplies relevant context but does not reliably remove earlier instructions. The maximum requests setting governs agent execution limits rather than conversation isolation. Clearing history is also unnecessary when the previous work can remain available in its own session.
A new conversation can still receive applicable repository instructions and deliberately supplied context; it is the previous conversation that is separated.
Study-guide topics: conversational state, context isolation, and task boundaries. Reference: VS Code-Manage agent sessions.
NEW QUESTION # 108
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