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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Manage memory, state, and execution | 10–15% | - Handle execution flow, retries, and interruptions - Choose memory types: short-term, long-term, external - Implement memory cleanup and expiration rules - Scope and persist agent state correctly |
| Topic 2: Perform evaluation, error analysis, and tuning | 15–20% | - Diagnose failures, hallucinations, and unexpected behavior - Optimize prompts, tools, and behavior through iteration - Test, validate, and compare agent results - Define metrics and quality standards for outputs |
| Topic 3: Orchestrate multi-agent coordination | 15–20% | - Design workflows for multiple agents - Prevent conflicts and manage shared resources - Define communication and handoff protocols - Monitor and troubleshoot multi-agent execution |
| Topic 4: Prepare agent architecture and SDLC processes | 15–20% | - Design agent autonomy and decision boundaries - Plan agent deployment, monitoring, and maintenance - Define agent purpose, scope, and success criteria - Integrate agents into software development lifecycle |
| Topic 5: Implement tool use and environment interaction | 20–25% | - Implement tools, custom actions, and MCP servers - Configure and extend GitHub Copilot agents - Connect agents to codebase, APIs, and external systems - Manage permissions and environment access |
| Topic 6: Implement guardrails and accountability | 10–15% | - Enforce least privilege and security boundaries - Ensure compliance, safety, and responsible use - Add validation, review, and approval gates - Log actions, decisions, and changes for audit |
1. A pull request created by the Copilot coding agent needs to be automatically closed if it fails to pass required checks after three retry attempts, per your organization's governance policy. What should you configure?
A) agents.md
B) /compact
C) .copilotignore
D) A repository ruleset with agent-specific merge conditions and CI enforcement
2. You have a GitHub repository that uses the GitHub Copilot coding agent.
Your company restricts GitHub Actions secrets.
Developers need the Copilot coding agent to call an internal dependency-scanning API during its run. The API requires an access token.
You need to ensure that the Copilot coding agent can use the token during execution without accessing the repository's Actions secrets and variables. The solution must prevent exposing the token in plaintext.
What should you do?
A) Store the token in a repository custom instructions file.
B) Add the token as an Actions repository secret.
C) Add the token as a secret in the Copilot environment.
D) Store the token in the agent configuration file.
3. Hotspot Question
You have a GitHub repository that uses the GitHub Copilot coding agent to resolve issues and create draft pull requests.
You assign an issue to Copilot. Copilot creates a draft pull request. The pull request timeline shows Copilot started work, followed by status updates. The most recent status update is 55 minutes old.
You discover that the agent is no longer making progress.
You need to ensure that the work resumes without redoing the completed steps or changing the previously chosen approach.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
4. You have a GitHub Enterprise Cloud Organization that uses GitHub Actions for CI/CD.
You plan to enable an agent to update and deploy workflows that access production environment secrets.
You need to select an autonomy level for a compliance-sensitive workflow.
Which autonomy level should you select?
A) fully autonomous execution without approvals
B) autonomous execution limited to non-production environments
C) read-only analysis with no ability to trigger workflows
D) human-in-the-loop with required manual approvals for production
5. Drag and Drop Question
You have a GitHub repository that uses GitHub Actions for CI on pull requests.
You have a GitHub Copilot coding agent that opens pull requests for backlog items, and your company requires automated checks for agent-generated changes.
You plan to standardize success criteria so that pull requests created by agents only succeed when unit tests pass and CodeQL analysis completes.
You need to configure a GitHub Actions workflow that runs on pull requests, executes unit tests, and performs CodeQL analysis.
How should you complete the workflow? 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.
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: C | Question # 3 Answer: Only visible for members | Question # 4 Answer: D | Question # 5 Answer: Only visible for members |
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