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Microsoft GH-600 Exam Syllabus Topics:

SectionWeightObjectives
Manage memory, state, and execution10-15%- Control execution flow
  • 1. Monitor execution lifecycle
  • 2. Recover from interruptions and failures
- Manage context and memory
  • 1. Handle long-running execution
  • 2. Maintain agent state
Perform evaluation, error analysis, and tuning15-20%- Evaluate agent performance
  • 1. Measure outcomes and quality
  • 2. Analyze scans, logs, and artifacts
- Improve agent behavior
  • 1. Perform error analysis
  • 2. Tune prompts, tools, and configurations
Prepare agent architecture and SDLC processes15-20%- Integrate agents into the software development lifecycle
  • 1. Identify and mitigate agent anti-patterns
  • 2. Identify steps for agents to perform
  • 3. Define inputs, outputs, and success criteria
- Configure observability and control
  • 1. Generate inspectable artifacts
  • 2. Implement autonomy levels and guardrails
  • 3. Enable human intervention when required
- Define boundaries between planning, reasoning, and action
  • 1. Validate and approve plans before execution
  • 2. Separate planning from execution
  • 3. Configure structured plans
Orchestrate multi-agent coordination15-20%- Coordinate multiple agents
  • 1. Manage communication and task delegation
  • 2. Design multi-agent workflows
- Ensure safe collaboration
  • 1. Prevent conflicts and unsafe actions
  • 2. Coordinate execution across agents
Implement guardrails and accountability10-15%- Implement governance controls
  • 1. Apply security and compliance requirements
  • 2. Configure approval workflows
- Ensure accountability
  • 1. Establish human-in-the-loop processes
  • 2. Track actions and decisions
Implement tool use and environment interaction20-25%- Manage execution environments
  • 1. Configure environments for agents
  • 2. Control access to resources and services
- Select and configure agent tools
  • 1. Identify required tools
  • 2. Configure tools and permissions

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Microsoft GitHub Agentic AI Developer Sample Questions (Q79-Q84):

NEW QUESTION # 79
You have a GitHub Enterprise Cloud repository that uses GitHub Actions for CI and requires pull requests for all changes.
You are planning a GitHub Actions workflow where a coding agent drafts implementation changes and tests from GitHub issues, and an automated review runs before human review.
You need the agent to draft changes from an assigned issue, open a pull request, and add an automated review to the pull request before requesting a human review.
What should you do? To answer, select the appropriate options in the answer area.

Answer:

Explanation:


NEW QUESTION # 80
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?

Answer: A

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 # 81
You want the GitHub Copilot coding agent to follow project-specific conventions (coding style, testing requirements, folder structure) on every task it performs in a repository. What should you create?

Answer: B

Explanation:
The correct configuration is .github/copilot-instructions.md. GitHub defines this file as the repository-wide custom-instructions mechanism for providing persistent project-specific guidance to Copilot. Instructions stored there are automatically incorporated when Copilot works in the repository, making the file appropriate for conventions that should apply repeatedly, such as coding standards, architectural expectations, preferred test frameworks, build and validation commands, repository layout, and required implementation patterns.
This is particularly important for a coding agent because the instructions establish persistent SDLC context rather than relying on developers to repeat requirements in every issue or prompt. GitHub explicitly describes repository instructions as a way to tell Copilot how to understand, build, test, and validate repository changes.
CODEOWNERS controls ownership and review assignment rather than Copilot behavior. A .copilotignore file is not the repository-wide custom-instructions mechanism, and agents.yml is not the prescribed file for persistent repository conventions.
Study Guide Reference Topics: Prepare agent architecture and SDLC processes; repository-level agent instructions; persistent development conventions; automated build and test guidance.


NEW QUESTION # 82
You have a multi-agent GitHub Actions workflow that uploads review artifacts for each run.
You discover that some workflow run artifacts are being deleted manually.
You need to use your organization's audit log data to identify which user deleted the artifacts.
Which audit log search filter should you use?

Answer: A

Explanation:
To identify which user manually deleted the workflow run artifacts, you should use the action:artifact.destroy search filter.When searching your GitHub Organization Audit Log, this filter targets the exact event triggered when a workflow run artifact is manually removed.
Reference:
https://docs.github.com/en/organizations/keeping-your-organization-secure/managing-security-settings-for-your-organization/reviewing-the-audit-log-for-your-organization


NEW QUESTION # 83
You have a GitHub Enterprise Cloud organization that has Copilot agents enabled.
You discover activity in a repository.
You need to identify whether the activity was initiated by an agent.
Which two audit log fields can you use? Each correct answer presents a complete solution.

Answer: A,C


NEW QUESTION # 84
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