- Exam Code: GH-600
- Exam Name: GitHub Agentic AI Developer
- Certification Provider: Microsoft
- Corresponding Certification:GitHub Administrator
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Microsoft GH-600 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Prepare agent architecture and SDLC processes | 15–20% | - Integrate agents into software development lifecycle - Design agent autonomy and decision boundaries - Plan agent deployment, monitoring, and maintenance - Define agent purpose, scope, and success criteria |
| Implement guardrails and accountability | 10–15% | - Enforce least privilege and security boundaries - Ensure compliance, safety, and responsible use - Log actions, decisions, and changes for audit - Add validation, review, and approval gates |
| Orchestrate multi-agent coordination | 15–20% | - Design workflows for multiple agents - Monitor and troubleshoot multi-agent execution - Define communication and handoff protocols - Prevent conflicts and manage shared resources |
| Manage memory, state, and execution | 10–15% | - Choose memory types: short-term, long-term, external - Handle execution flow, retries, and interruptions - Scope and persist agent state correctly - Implement memory cleanup and expiration rules |
| Perform evaluation, error analysis, and tuning | 15–20% | - Diagnose failures, hallucinations, and unexpected behavior - Define metrics and quality standards for outputs - Test, validate, and compare agent results - Optimize prompts, tools, and behavior through iteration |
| 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 |
Microsoft GitHub Agentic AI Developer Sample Questions:
1. 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 resolve the issue of the agents generating conflicting output. The solution must meet the implementation guidelines.
What should you do?
A) Add shared/config.yaml to a CODEOWNERS file that requires SG_Review approval before any changes can be merged.
B) Configure a concurrency group on both agent workflows so that only one workflow runs at a time.
C) Configure each agent to work on a separate branch and add a required status check that detects file-level overlap before either pull request can be merged.
D) Configure tools: ['read', 'search'] in both agent profiles to prevent either agent from writing files.
2. You assigned an issue to the Copilot coding agent, and it opened a pull request. You want to inspect exactly what code changes were made before merging. Which CLI slash command lets you view the change set directly in the terminal?
A) /context
B) /plan
C) /compact
D) /diff
3. A team assigns an issue to the GitHub Copilot coding agent by using the following one-line description: Fix the login bug.
Copilot creates a pull request, but the pull request is missing changes and has an incorrect scope.
How should you resolve the issue?
A) Allocate more resources to copilot-setup-steps.yml.
B) Update the Model Context Protocol (MCP) server rate limits.
C) Enable Copilot memory.
D) Add a clear description of the problem to the issue.
4. You have multiple GitHub Copilot coding agents that run tasks concurrently.
You are monitoring the agents from the terminal by using the GitHub CLI.
An agent appears stalled.
You need to live stream the session log output.
What should you do?
A) Run gh agent-task list and specify the --status and --jq parameters.
B) Run gh agent-task view and specify the --log and --follow parameters.
C) Run gh agent-task view and specify the --log and --jq parameters.
D) Run gh agent-task list and specify the --web parameter.
5. Hotspot Question
You have a GitHub repository that contains the following custom agent files:
- A file named planner.agent.md that includes YAML frontmatter with a
handoffs entry that has label: Start Implementation, agent:
implementer, and prompt: Now implement the plan outlined above
- A file named implementer.agent.md that is in the same directory as
planner.agent.md and includes YAML frontmatter that has name:
IMPLEMENTER
You add a third agent file named review.agent.md.review.agent.md includes YAML frontmatter that has name: code-review.
You make the following changes to planner.agent.md:
- Update the existing handoff to include send: true and model: GPT-5.2
(copilot).
- Add a second handoff that has label: Run Review, agent: code-review,
and prompt: Review the code changes made in the previous step.
No other agent files are modified.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: D | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: Only visible for members |
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