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Microsoft GH-600 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Prepare agent architecture and SDLC processes	15–20%	- Configure observability and control for autonomous agents 1. Configure human intervention for autonomous agents without slowing delivery 2. Configure agents to produce inspectable artifacts within standard development tooling 3. Plan and implement the degree of agent autonomy, including guardrails - Define boundaries between planning, reasoning, and action 1. Prevent agent action until the agent checks and approves 2. Configure an agent to output a structured plan 3. Configure agent planning to be distinct from agent execution 4. Validate agent plans - Integrate agents into the software development lifecycle (SDLC) 1. Identify and mitigate common anti-patterns in agents 2. Define inputs, outputs, and success criteria for agents 3. Identify steps for agents to perform
Topic 2: Manage memory, state, and execution	10–15%	- Ensure continuity of agent memory and state across tools and environments 1. Prevent stale context 2. Prevent conflicting context 3. Share agent state - Implement agent memory strategies 1. Define memory expiration, pruning, and reset rules 2. Choose between short-term, long-term, and external memory 3. Scope agent memory to task-relevant information - Persist agent state and manage context drift 1. Resume agent work without repeating steps or diverging from prior decisions 2. Capture task progress and decisions as durable artifacts 3. Detect and correct drift during extended agent execution
Topic 3: Orchestrate multi-agent coordination	15–20%	- Manage the lifecycle of agents within multi-agent workflows 1. Retire agents while preserving auditability and workflow continuity 2. Update, reconfigure, or replace agents without disrupting active workflows 3. Add agents to existing multi-agent workflows - Operate and manage multi-agent workflows 1. Detect and resolve agent conflicts, including overlapping code changes, duplicated effort, and contradictory outputs 2. Apply an orchestration pattern to coordinate multiple agents 3. Configure agent isolation for parallel execution - Detect and respond to multi-agent failures and degraded behavior 1. Identify failed, partial, or stalled agent executions 2. Implement multi-agent recovery patterns, including rollback and human-in-the-loop 3. Respond to degraded behavior or coordination across agents - Configure observability for multi-agent behavior by using logs, artifacts, and operational signals 1. Configure multi-agent workflows to produce artifacts suitable for review and audit 2. Perform post-hoc analysis of multi-agent behavior 3. Document key decisions, handoffs, and outcomes across agents
Topic 4: Perform evaluation, error analysis, and tuning	15–20%	- Define success criteria and evaluation signals for agent tasks 1. Align evaluation criteria with development intent 2. Generate evaluation signals by using automated scanning tools 3. Specify expected outcomes and operational constraints for agent tasks 4. Identify qualitative and quantitative evaluation signals to evaluate agents - Analyze agent failures and identify root causes 1. Classify root causes, including reasoning errors, tool misuse, and context or environment issues 2. Identify failures by using logs, plans, traces, outputs, and workflow artifacts - Tune agent behavior based on evaluation results 1. Revise instructions, workflows, or constraints 2. Refine tool usage and tool access 3. Refine memory usage
Topic 5: Implement tool use and environment interaction	20–25%	- Operate agents with safe execution paths and robust error handling 1. Implement error handling 2. Implement traceability and accountability for agent actions 3. Implement rollbacks 4. Implement retries 5. Implement escalation paths - Configure MCP servers 1. Configure a GitHub remote MCP server 2. Add an MCP server as a tool to an agent 3. Configure MCP allow lists 4. Configure MCP registries - Select and configure agent tools 1. Identify required tools 2. Configure agent tool permissions 3. Configure agent tools - Integrate agents within development environments 1. Configure an agent to be invoked in a CI workflow 2. Evaluate the execution context for an agent 3. Configure an agent to use branch-based scope 4. Configure an agent to handle environment-specific constraints 5. Enable an agent to perform autonomous actions, including creating branches and pull requests 6. Configure an agent's scope to a specific repository
Topic 6: Implement guardrails and accountability	10–15%	- Define autonomy levels 1. Assign autonomy levels to maximize delivery speed while remaining compliant with organizational security and Responsible AI standards 2. Classify agent actions by operational, security, and compliance risk to right-size human interventions - Implement guardrails and human-in-the-loop workflows 1. Require explicit authorization or controlled paths for irreversible or compliance-sensitive changes 2. Block actions that violate defined security, compliance, or Responsible AI policies 3. Preserve execution velocity by minimizing approvals that do not materially reduce risk 4. Scope permissions and execution contexts to enforce least-privilege access 5. Identify the subset of actions that require human judgment

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Microsoft Developing in Agentic AI Systems Sample Questions (Q62-Q67):

NEW QUESTION # 62
You have a GitHub repository that uses the GitHub Copilot CLI to run autonomous tasks.
You need to validate each generated command before it runs. Any commands that attempt to modify paths outside the repository must be blocked.
How should you complete the YAML? 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:
Target
Intended selection in the supplied question
event
pre-exec
cli.hooks.config
copilot/hooks.yaml
Verification correction: These are the intended selections within the supplied YAML. Current official Copilot documentation specifies JSON hook configuration and the preToolUse event; the supplied YAML is not a verified current Copilot CLI configuration.
Within the question's own schema, pre-exec is the logical event because validation must occur before a command can modify the filesystem. A post-exec event would run after the potentially prohibited action. The configuration path must reference the hook file identified in the exhibit, .copilot/hooks.yaml, rather than a workflow file under .github/workflows.
However, official Copilot documentation defines repository hook files under .github/hooks/*.json and uses the preToolUse lifecycle event. A blocking hook can return a structured permission decision of " deny " . The supplied YAML names and configuration structure therefore should not be copied into a current deployment as documented syntax.
The depicted command-string filter also does not establish complete filesystem confinement. Detecting obvious absolute paths and parent traversal cannot reliably resolve symbolic links, variable expansion, or the behavior of invoked programs. Enforcing the requirement that all external modifications be blocked requires a genuine execution boundary alongside command validation.
The question tests the correct preventive-control concept but presents an implementation that needs correction. Relevant curriculum topics are blocking prohibited actions, enforcing least privilege, and constraining execution contexts.
Reference: GitHub Copilot hooks reference .

NEW QUESTION # 63
You have a GitHub Copilot coding agent named CodeAgent. The .agent.md file of CodeAgent contains the following YAML frontmatter.
name: CodeAgent
description: Performs repository analysis and code review tasks.
tools: ['edit', 'execute', 'read', 'search']
You need to issue a GitHub Copilot CLI command that preserves execution velocity for read-only tasks by eliminating approval prompts for low-risk tools. The solution must ensure that high-risk tools that can make changes remain available but still require explicit user approval before running.
Which command should you run?

A. copilot agent run CodeAgent --deny-tool 'edit,execute'
B. copilot agent run CodeAgent --allow-all-tools
C. copilot agent run CodeAgent
D. copilot agent run CodeAgent --allow-tool 'read,search'

Answer: D

Explanation:
Allowing only read and search removes approval friction for operations that inspect repository content without modifying it. The edit and execute tools remain available in the agent profile, but they continue to require explicit approval because they are not included in the command's approval bypass.
Using no option preserves the default approval behavior for all tools, including low-risk inspection tools, which does not meet the velocity requirement. Allowing all tools would remove the approval safeguard for file modifications and shell execution. Denying edit and execute prevents those tools from being used at all, rather than keeping them available under human control.
This design separates tool availability from automatic authorization. Read-only operations can proceed autonomously, while potentially impactful operations remain subject to a human decision at the point of use.
Study-guide topics: tool approval boundaries, least privilege, read-only execution, and controlled agent autonomy.

NEW QUESTION # 64
You have a GitHub repository that uses GitHub Copilot Chat in Microsoft Visual Studio Code. Custom agents are stored in the repository under version control.
Your team uses a multi-agent workflow where a planner agent produces an implementation plan that is then handed off to an implementation agent to make changes.
Recent prompts cause the planner agent to start editing files and running commands before the plan is approved.
You need to configure the planner agent to meet the following requirements:
* Use only read-only tools.
* Hand off to the implementation agent only after the plan is approved.
How should you configure the agent? To answer, select the appropriate options in the answer area.

Answer:

Explanation:

Explanation:
tools: [ ' search ' , ' read ' , ' fetch ' ]
send: false
The completed configuration is:
name: planner-agent
description: Planning
tools: [ ' search ' , ' read ' , ' fetch ' ]
handoffs:
- label: Start Implementation
agent: implementer
prompt: Now implement the plan outlined above.
send: false
The planner must be restricted to read-only capabilities, so [ ' search ' , ' read ' , ' fetch ' ] is the correct tool set. search locates repository information, read inspects file contents, and fetch retrieves supporting information without modifying source files. The other available tool combinations contain write-capable operations such as edit, commit, push, merge, or publish, which would violate the requirement that the planner must not alter the repository before approval. VS Code custom agents explicitly support scoping tools so that planning agents can be constrained to research and analysis capabilities.
The send property must be false. A handoff appears as an interactive transition after the planner produces its response. With send: false, selecting the handoff switches to the implementation agent and pre-fills the implementation prompt, but the prompt is not automatically submitted. This provides the necessary human approval gate: the plan can be reviewed before implementation begins. By contrast, send: true immediately submits the handoff prompt after the transition.
Study Guide Reference Topics: agent role separation, least-privilege tool assignment, planning versus execution, multi-agent handoffs, and human approval gates.

NEW QUESTION # 65
You are troubleshooting why a Copilot coding agent pull request keeps failing CI checks after every attempted fix. What is the most effective first step?

A. Enable Copilot memory
B. Switch the agent to --allow-all mode
C. Increase MCP server rate limits
D. Add clear, reproducible steps and expected behavior to the issue

Answer: D

NEW QUESTION # 66
You have a GitHub repository that contains an agent named Orchestrator. Orchestrator delegates work to the following specialized subagents:
Planner reviews issues and creates a plan of action.
Implementer writes code based on the plan of action.
Reviewer reviews the code.
You create a new agent named Summarizer that produces a concise summary of the work performed by the other agents.
You need to ensure that Orchestrator can invoke Summarizer as part of its workflow.
What should you do?

A. In the YAML frontmatter of the Orchestrator agent, add Summarizer to the agents list.
B. In the YAML frontmatter of the Reviewer agent, add Summarizer to the agents list.
C. In the YAML frontmatter of the Reviewer agent, add a handoffs entry that points to the Summarizer agent.
D. In the YAML frontmatter of the Orchestrator agent, add Summarizer to the tools list.

Answer: A

Explanation:
The configuration must be changed on the agent that performs the delegation. Orchestrator is responsible for coordinating the workflow, so its allowed subagent list must include Summarizer. Adding the new agent to that list makes it an available delegation target alongside Planner, Implementer, and Reviewer.
An agent's agents property identifies the custom agents it can invoke as subagents. The tools property serves a different purpose: it identifies available capabilities such as reading files, editing code, or invoking agents. Adding a custom agent's name to the tools list does not register that agent as a callable subagent. The agent invocation tool must also be available; the scenario already establishes that Orchestrator delegates to other subagents.
Changing Reviewer's configuration would enable a relationship originating from Reviewer, rather than the requested direct invocation by Orchestrator. A handoff also represents a different interaction pattern from having the orchestrating agent invoke a subagent and receive its result.
Availability does not force execution on every task. Orchestrator's instructions should indicate when a summary is required and what information it should contain.
Study-guide topics: delegation permissions, orchestrator responsibilities, and specialized subagents. Reference: VS Code-Subagents.

NEW QUESTION # 67
......

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