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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
| Topic 1: Manage memory, state, and execution | 10–15% | - Implement memory cleanup and expiration rules
- Choose memory types: short-term, long-term, external
- Scope and persist agent state correctly
- Handle execution flow, retries, and interruptions
|
| Topic 2: Prepare agent architecture and SDLC processes | 15–20% | - Design agent autonomy and decision boundaries
- Plan agent deployment, monitoring, and maintenance
- Integrate agents into software development lifecycle
- Define agent purpose, scope, and success criteria
|
| Topic 3: Perform evaluation, error analysis, and tuning | 15–20% | - Test, validate, and compare agent results
- Optimize prompts, tools, and behavior through iteration
- Define metrics and quality standards for outputs
- Diagnose failures, hallucinations, and unexpected behavior
|
| Topic 4: Orchestrate multi-agent coordination | 15–20% | - Prevent conflicts and manage shared resources
- Monitor and troubleshoot multi-agent execution
- Define communication and handoff protocols
- Design workflows for multiple agents
|
| Topic 5: Implement tool use and environment interaction | 20–25% | - Connect agents to codebase, APIs, and external systems
- Manage permissions and environment access
- Implement tools, custom actions, and MCP servers
- Configure and extend GitHub Copilot agents
|
| Topic 6: Implement guardrails and accountability | 10–15% | - Log actions, decisions, and changes for audit
- Ensure compliance, safety, and responsible use
- Add validation, review, and approval gates
- Enforce least privilege and security boundaries
|
Microsoft GitHub Agentic AI Developer Sample Questions:
1. You have a GitHub Enterprise repository.
An agent opens pull requests to the main branch.
You need to ensure that changes to .github/workflows/* and /infra/* require approval from designated reviewers before merge.
What should you configure?
A) a branch protection rule and copilot-instructions.md
B) a branch protection rule and a CODEOWNERS file
C) a ruleset and a .copilotignore file
D) a ruleset and an agents.md file
2. 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

Drag and Drop Question
You need to implement the security requirements for agent1.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

3. 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: [].
4. During a Copilot CLI session, an MCP tool call fails because the external service requires re- authentication. What is the most likely resolution path?
A) Run /diff to inspect changes
B) Run /compact to clear context
C) Switch to plan mode
D) Re-authenticate the MCP server connector
5. You are architecting an agentic AI system and need the agent's tool-calling behavior to be constrained so it can only call a specific allow-listed set of MCP tools, never arbitrary ones. What should you configure?
A) Tool/server allow-list in the MCP client configuration
B) Repository ruleset
C) .copilotignore
D) /usage
Solutions:
Question # 1 Answer: B | Question # 2 Answer: Only visible for members | Question # 3 Answer: B | Question # 4 Answer: D | Question # 5 Answer: A |