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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Implement tool use and environment interaction | 20–25% | - MCP server configuration
- 1. Add MCP servers to agents
- 2. Configure registries and allow lists
- Safe execution and error handling
- 1. Retries and rollback strategies
- 2. Escalation paths and traceability
- Agent tool configuration
- 1. Select and configure tools
- 2. Configure tool permissions and scope
- Development environment integration
- 1. Scope agents to repositories or branches
- 2. Enable CI-based agent execution
- 3. Enable autonomous actions (PRs, branches)
|
| Manage memory, state, and execution | 10–15% | - State persistence and drift control
- 1. Persist task progress as artifacts
- 2. Detect and correct context drift
- Agent memory strategies
- 1. Short-term vs long-term memory selection
- 2. Memory scoping and expiration rules
- Cross-tool continuity
- 1. Share state across tools and environments
- 2. Prevent stale or conflicting context
|
| Prepare agent architecture and SDLC processes | 15–20% | - Integrate agents into SDLC workflows
- 1. Define inputs, outputs, and success criteria
- 2. Identify and mitigate agent anti-patterns
- 3. Define agent steps in SDLC
- Observability and control
- 1. Define autonomy levels and guardrails
- 2. Produce inspectable artifacts in GitHub
- 3. Enable human-in-the-loop controls
- Planning vs execution boundaries
- 1. Prevent execution before approval
- 2. Validate structured agent plans
- 3. Separate planning and execution phases
|
| Implement guardrails and accountability | 10–15% | - Autonomy and risk levels
- 1. Classify agent actions by risk
- 2. Assign autonomy levels with compliance constraints
- Guardrails and human-in-the-loop
- 1. Require approvals for sensitive actions
- 2. Enforce least-privilege execution
|
| Evaluation, error analysis, and tuning | 15–20% | - Tuning agent behavior
- 1. Optimize memory usage and constraints
- 2. Refine prompts, tools, and workflows
- Define evaluation criteria
- 1. Generate automated evaluation signals
- 2. Define success metrics and constraints
- Failure analysis
- 1. Analyze logs, traces, and artifacts
- 2. Classify reasoning, tool, and context errors
|
| Orchestrate multi-agent coordination | 15–20% | - Failure handling and recovery
- 1. Detect stalled or degraded agents
- 2. Implement rollback and recovery patterns
- Multi-agent workflows
- 1. Coordinate parallel agent execution
- 2. Resolve conflicts and overlaps
- Lifecycle management
- 1. Add/replace/retire agents safely
- Observability and auditability
- 1. Document agent handoffs and decisions
- 2. Generate logs and artifacts for review
|
Microsoft GitHub Agentic AI Developer Sample Questions:
1. Your team wants Copilot's suggestions to reflect knowledge of internal library APIs that are not publicly documented and not present in the codebase being edited. What is the most appropriate solution?
A) Add the internal docs as copilot-instructions.md
B) Use .copilotignore to hide public APIs
C) Enable plan mode
D) Connect an MCP server that exposes the internal documentation
2. Hotspot Question
You have the following agent logs.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

3. You have a GitHub Enterprise Cloud repository that uses the GitHub Copilot coding agent.
Engineers assign issues to Copilot, and Copilot creates draft pull requests. The engineers start tasks either by assigning issues on github.com or by using GitHub Copilot Chat in an IDE.
Reviewers request updates by leaving pull request comments.
You discover that sometimes, Copilot uses outdated requirements after a reviewer posts an updated instruction in a pull request comment, and, in several cases, Copilot fails to resume work from the comment.
You need to ensure that iteration requests are applied to the correct pull request session and are processed consistently.
What should you do?
A) Ensure that the agent has write access to the repository. Instruct the reviewer to unassign and reassign the original issue to Copilot.
B) Start a new task from Copilot Chat in the IDE. Instruct the reviewer to mention @github in the task comments.
C) Ensure that the reviewer has write access to the repository. Instruct the reviewer to mention
@copilot in the pull request comments.
D) Ensure that the agent has write access to the repository. Instruct the reviewer to mention @github in the task comments.
4. Your organization requires that any workflow file changes proposed by an autonomous agent be reviewed by a member of the security team before merging, regardless of who opened the pull request. What combination should you configure?
A) MCP server permissions + repository ruleset
B) copilot-instructions.md + required status checks
C) .copilotignore + agents.md
D) CODEOWNERS + a required branch protection rule
5. Case Study 2
Existing Environment
GitHub Environment
The GitHub environment contains the following:
- Three repositories named product-api, billing-service, and infra-terraform.
- Branch protection on the main branch in all repositories that requires at least one pull request review before merging
- GitHub Actions runners used across all workflows
- A GitHub team named SG_Dev that contains developers
- A GitHub team named SG_Review that contains senior engineers and a security team
- A .github/copilot-instructions.md file that includes general coding conventions for all features Agent environment The product-api repository uses a GitHub Copilot coding agent named agent1 that has the following configurations:
- No custom agent profile is defined.
- A Model Context Protocol (MCP) server named MCP1 is deployed to
https://mcp.litwareinc.internal and provides access to internal ticketing and deployment APIs.
MCP1 requires an API key for authentication.
A second Copilot coding agent named agent2 handles changes in infra-terraform and runs in parallel with agent1 when both agents have open assigned issues.
Copilot memory is NOT enabled for the organization.
Problem Statements
Litware identifies the following issues:
- During two recent sessions, agent1 accessed files in billing-service, which is outside the agent's intended scope.
- agent1 makes code changes immediately after receiving a task.
- A developer named Ben, who is on the SG_Dev team, reports that agent1 completed a session with a successful status and opened a pull request, but the pull request contains no file changes.
Other developers report this intermittently as well.
- Both agent1 and agent2 modified shared/config.yaml in a parallel test run, generating conflicting outputs.
agent1 consistently uses raw try-catch blocks for error handling, which violates the defined implementation guidelines of SG_Dev.
Requirements
Planned Changes
Litware plans to make the following changes:
- Ensure that agent1 can access all the tools in the environment.
- Provide product-api with specific instructions to agent1 without affecting Copilot Chat or Copilot code review.
- Configure MCP1 as a tool for agent1 by modifying the product-api repository MCP configuration.
- Ensure that Copilot retains details that it has learned and uses that knowledge for future work.
This must be applied to all licensed members of the organization.
Implementation guidelines
The development team at Litware identifies the following implementation guidelines:
- Agent workflows must be able to run in parallel.
- Application error handling must use the repository ErrorHandler class.
- agent1 and agent2 must run on isolated branches during parallel execution. File-level conflicts must be detected before merges, and both agents must be able to run concurrently.
Security requirements
Litware identifies the following security requirements:
- Only the members of SG_Review must be able to approve agent1 plan outputs.
- All API keys must be stored and accessed securely.
- The developers must NOT be able to self-approve.
Agent configuration

You need to configure agent1 to support the planned changes.
What should you do?
A) Add Use all available tools to the instructions in the agent configuration.
B) Delete line 05 from the agent configuration.
C) Add the mcp-servers property to the agent configuration.
D) Add Use all available tools to the .github/copilot-instructions.md file.
E) In the agent configuration, replace line 05 with the following.05 tools: [].
Solutions:
Question # 1 Answer: D | Question # 2 Answer: Only visible for members | Question # 3 Answer: C | Question # 4 Answer: D | Question # 5 Answer: B |