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Microsoft GH-600 Exam Syllabus Topics:

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

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Microsoft Developing in Agentic AI Systems Sample Questions (Q88-Q93):

NEW QUESTION # 88
You have a repository that uses the GitHub Copilot coding agent and supports hooks stored under .github/hooks.
You need a Shell command to run automatically whenever an agent execution fails.
Which type of hook should you use?

A. postToolUse
B. agentStop
C. errorOccurred
D. sessionEnd

Answer: C

Explanation:
The errorOccurred hook is designed to respond to failures during an agent session. It can invoke a shell command when an agent execution encounters an error, enabling automated capture of diagnostic information, cleanup actions, or controlled escalation.
A postToolUse hook runs after individual tool calls, whether or not the overall agent execution subsequently fails. It is suitable for logging or post-processing tool activity but does not specifically target an execution failure. A session-end event indicates that a session has ended; it does not necessarily represent an error condition. agentStop is not the defined hook required by the scenario.
Failure hooks should be used carefully. Their commands should collect only the required diagnostics and must avoid exposing secrets in logs. If the failure itself results from a prohibited operation, the hook should preserve the reason and relevant metadata so that a human can distinguish policy denial from a technical execution failure.
Study-guide topics: lifecycle hooks, failure handling, diagnostic collection, and accountability.

NEW QUESTION # 89
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?

A. /compact
B. /clear
C. /usage
D. /reset-context

Answer: B

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 # 90
Your company uses GitHub Copilot Enterprise.
Developers use GitHub Copilot agent mode in Microsoft Visual Studio Code on their laptops and Copilot Chat on github.com when they are away from their laptops.
When switching between environments, the developers notice that agent workflows lose continuity because the tools available in Visual Studio Code are unavailable on github.com.
You need to ensure that the agent tools and state are available consistently across environments and can be used from any device without local setup.
What should you do for each requirement? To answer, drag the appropriate actions to the correct requirements.

Answer:

Explanation:

NEW QUESTION # 91
Drag and Drop Question
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:
Box 1: pre-exec
The hook needs to inspect and validate the generated shell commands before they are allowed to execute. The pre-exec event interceptor serves exactly this guardrail purpose. (post-exec would run only after the command has already finished).
Box 2: .copilot/hooks.yaml
The config property under the cli.hooks block points to the local path of the hooks configuration file itself so that the CLI can parse and load the defined Reference:
https://docs.github.com/en/copilot/how-tos/copilot-cli/cli-best-practices

NEW QUESTION # 92
You are analyzing the following agent logs.

You need to classify the error in a report for your company's CTO.
How should you classify the error?

A. Tool misuse
B. Context Issue
C. Network issue
D. Reasoning error

Answer: A

Explanation:
This is a Tool misuse error (specifically, a configuration/implementation bug).The agent successfully passed the reasoning and context phases, but the environment's internal handler failed because the mcp_microsoftdocs_microsoftdocs_search tool was not properly registered or the IDE failed to process the tool call's schema.
Reference:
https://github.com/anthropics/claude-quickstarts/issues/345

NEW QUESTION # 93
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