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| Section | Weight | Objectives |
|---|---|---|
| Implement agents and multi-agent systems | 30% | - Build agents with Azure AI tools and frameworks
|
| Test, deploy, and monitor agentic AI systems | 20% | - Validate agent performance and safety
|
| Design agentic AI solutions | 25% | - Design agent architecture
|
| Integrate tools, data, and services | 25% | - Incorporate external tools and APIs
|
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NEW QUESTION # 51
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 correct selection is --allow-all. GitHub Copilot CLI uses a permission model for potentially consequential operations such as invoking tools, modifying files, accessing filesystem paths, running shell commands, and reaching external URLs. Normally, these operations can require explicit approval. The --allow-all startup option grants all available permissions for the session, allowing Copilot to execute those operations without prompting for approval on each individual action. GitHub also provides --yolo as an alias for the same permission configuration.
This option is appropriate only when the execution environment is sufficiently isolated and trusted. GitHub specifically recommends using broad permissions in a sandbox or similarly disposable environment because the agent can modify or delete files and execute commands autonomously once approval barriers are removed.
/compact manages conversation context rather than permissions. --agent=Task selects an agent profile and does not globally pre-authorize tool execution. The GH-600 study guide explicitly assesses configuring agent tools, tool permissions, execution contexts, and safe autonomous actions, making permission scoping a core operational skill.
Study Guide Reference Topics: Implement Tool Use and Environment Interaction; configure agent tool permissions; evaluate execution context; safe autonomous execution.
NEW QUESTION # 52
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:
The correct command is /clear. In GitHub Copilot CLI, /clear starts a fresh conversational state by removing the current chat history from the active session. This is the appropriate action when the requirement is to discard prior conversation context completely rather than compress or summarize it.
/compact is specifically designed for context management during long-running sessions. It summarizes older conversation history so that useful information can be retained while freeing context-window capacity. Because the question explicitly says "without summarization," /compact does not satisfy the requirement.
/usage displays session consumption and usage information rather than modifying conversation state. /reset-context is not the standard slash command used for clearing Copilot CLI conversation history in this scenario.
The operational distinction is important in agentic workflows. Compaction preserves semantic continuity, while clearing abandons the prior conversational state and gives the agent a clean starting point. Clearing is therefore appropriate when accumulated context has become irrelevant, misleading, or overly large and you deliberately do not want previous reasoning, instructions, or task history carried forward.
Study Guide Reference Topics: Manage Memory, State, and Execution; conversation-state management; context-window control; session reset versus context compaction.
NEW QUESTION # 53
You have a GitHub Enterprise repository that runs an autonomous agent by using a GitHub Actions workflow. The workflow has the following jobs:
- agent-run that generates trace.json and plan.md
- review that waits for human approval before continuing
- deploy that uses the outputs from agent-run
You need to make the files inspectable in the GitHub Actions UI and ensure that the files are available to the review and deploy jobs.
What should you do in the workflow?
Answer: D
NEW QUESTION # 54
You have a GitHub Copilot coding agent named Orchestrator that runs a multi-phase workflow by using the following subagents:
Explorer gathers context by using read-only tools.
Modifier applies focused edits.
You are adding a new agent named Summarizer that generates a concise summary after modifications are complete. Summarizer includes the following YAML frontmatter:
---
name: Summarizer
description: Produce a concise summary of recent changes
tools: ['fetch']
user-invocable: false
disable-model-invocation: true
---
The Orchestrator agent lists all three agents in its agents property.
After adding the Summarizer agent, Orchestrator successfully runs Explorer and Modifier but fails to run Summarizer.
What is a possible cause of the failure?
Answer: D
Explanation:
D is the best answer among the available choices. The key detail is that Summarizer is explicitly listed in Orchestrator's agents property. Current VS Code agent orchestration behavior states that explicitly listing a custom agent in the parent's agents array overrides disable-model-invocation: true for that coordinator. Therefore, option A does not explain the failure in this scenario.
Likewise, user-invocable: false does not prohibit programmatic or subagent invocation. It merely prevents users from manually selecting that agent from the agent picker; this setting is commonly used specifically for worker agents that should only operate as subagents.
Option C is also incorrect because Summarizer's function is to produce a summary, not modify repository content. It therefore does not inherently require editing tools.
The agents property establishes which subagents the coordinator is permitted to invoke; it does not itself define the sequence of workflow transitions. Handoffs are the mechanism for defining explicit guided transitions between agents. If the workflow expects Summarizer to run as the next defined phase but no corresponding transition/invocation exists, the missing handoff can explain why execution stops after Modifier.
Study Guide Reference Topics: Orchestrate Multi-Agent Coordination; custom subagents; agents restrictions; agent invocation controls; sequential handoffs and workflow transitions.
NEW QUESTION # 55
You are using GitHub Copilot Chat's agent mode in VS Code and want it to autonomously use tools (terminal, file edits, tests) to complete a multi-step task, checking in with you between major steps. What is this interaction mode called?
Answer: D
Explanation:
Agent mode allows Copilot Chat to autonomously plan and execute multi-step tasks using available tools, pausing for confirmation at key decision points rather than requiring manual step- by-step prompting.
NEW QUESTION # 56
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