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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Implement tool use and environment interaction | 20–25% | - Connect agents to codebase, APIs, and external systems - Configure and extend GitHub Copilot agents - Implement tools, custom actions, and MCP servers - Manage permissions and environment access |
| Topic 2: Prepare agent architecture and SDLC processes | 15–20% | - Define agent purpose, scope, and success criteria - Plan agent deployment, monitoring, and maintenance - Design agent autonomy and decision boundaries - Integrate agents into software development lifecycle |
| Topic 3: Implement guardrails and accountability | 10–15% | - Ensure compliance, safety, and responsible use - Add validation, review, and approval gates - Enforce least privilege and security boundaries - Log actions, decisions, and changes for audit |
| Topic 4: Perform evaluation, error analysis, and tuning | 15–20% | - Test, validate, and compare agent results - Define metrics and quality standards for outputs - Diagnose failures, hallucinations, and unexpected behavior - Optimize prompts, tools, and behavior through iteration |
| Topic 5: Orchestrate multi-agent coordination | 15–20% | - Prevent conflicts and manage shared resources - Define communication and handoff protocols - Monitor and troubleshoot multi-agent execution - Design workflows for multiple agents |
| Topic 6: Manage memory, state, and execution | 10–15% | - Choose memory types: short-term, long-term, external - Scope and persist agent state correctly - Implement memory cleanup and expiration rules - Handle execution flow, retries, and interruptions |
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NEW QUESTION # 43
You have a GitHub repository that uses GitHub Copilot code review on pull requests.
You plan to add repository-wide code review guidance that will apply to all files.
You need Copilot code review to consistently apply the guidance during pull request reviews.
What should you do?
Answer: B
Explanation:
The repository-wide Copilot instruction file is .github/copilot-instructions.md. GitHub explicitly identifies this file as the location for review guidance that should apply throughout the codebase. It can describe coding standards, security expectations, error-handling requirements, and other review criteria that should be considered across pull requests.
A pull request template primarily structures the description supplied when a pull request is created. It is not the designated repository-wide Copilot instruction mechanism. Files beneath .github/instructions support instructions with defined applicability, commonly using path patterns. The filename in option C alone does not establish repository-wide scope. Custom agent profiles define the behavior of particular agents and do not replace the standard configuration for Copilot code review.
The instructions should state concrete, reviewable requirements rather than vague pReference. For example, a rule about checking authorization at a defined service boundary is more actionable than a general instruction to "ensure security." Repository settings must also allow custom instructions to be used for code review.
This configuration improves consistency while human reviewers remain responsible for evaluating the resulting findings.
Relevant curriculum topics are tuning instructions, defining evaluation criteria, and aligning automated review with development intent.
Reference:
NEW QUESTION # 44
You are about to start a complex refactoring task in the GitHub Copilot CLI.
Before Copilot makes any changes, you need to review and agree on the approach.
What should you do first?
Answer: A
Explanation:
GitHub Copilot CLI plan mode is specifically designed for situations in which an implementation strategy must be developed and reviewed before code modifications begin. In plan mode, Copilot can inspect and analyze the repository, ask clarifying questions, and construct a structured implementation plan while protecting project files from normal editing operations. The resulting plan can then be reviewed and approved before Copilot proceeds with implementation. GitHub explicitly describes plan mode as a mechanism for identifying misunderstandings before code is written and maintaining human control over complex, multi-step work.
Option A is incorrect because --agent=AGENT selects a custom agent; it does not establish a planning-and-approval phase. Option B is the opposite of the requirement: --allow-all grants Copilot broad permission to use tools, paths, and URLs without individual approval. Option D is also incorrect because /compact relates to managing conversation/context size rather than establishing an implementation plan.
Therefore, switching to plan mode is the appropriate first action when the development process requires human review and agreement before changes are applied.
Study Guide Reference Topics: Prepare agent architecture and SDLC processes; human-in-the-loop development; planning before implementation; controlled agent execution.
NEW QUESTION # 45
You have a GitHub repository that uses the GitHub Copilot coding agent to resolve issues in an ephemeral GitHub Actions environment.
Builds fail unless an environment variable named NPM_TOKEN is available, because the repository depends on a private package registry.
A workflow named .github/workflows/copilot-setup-steps.yml was added but was merged into a non-default branch and does NOT run when new agent sessions start.
You need to ensure that for every new agent session, the setup steps run, and the private registry token is available as NPM_TOKEN, without hardcoding secrets in the repository.
What should you do?
Answer: A
Explanation:
The Copilot setup workflow must be present on the repository's default branch to be used for new coding-agent sessions. Moving .github/workflows/copilot-setup-steps.yml there ensures the setup procedure is discoverable for every newly created agent environment.
The package-registry credential should be stored as an environment secret in the Copilot environment and exposed using the required variable name, NPM_TOKEN. This permits package installation without committing the token into workflow YAML, instructions, source code, or pull requests.
Disabling network controls does not resolve missing credentials and expands risk unnecessarily. Repository instructions can describe setup expectations but cannot safely substitute for an injected runtime secret. Adding the raw token to YAML permanently exposes it to repository history and anyone with repository access.
Study-guide topics: ephemeral environments, setup workflows, environment secrets, and secure dependency access.
NEW QUESTION # 46
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: C
Explanation:
To automatically run a Shell command whenever a GitHub Copilot coding agent execution fails, you should use the errorOccurred (also referred to as onErrorOccurred) hook.
Hook Mechanics & ConfigurationGitHub Copilot agent hooks are defined using JSON configuration files placed in the .github/hooks/ directory.
Event Type: errorOccurred (or onErrorOccurred depending on your specific environment and version).
Execution Behavior: When an execution fails, the agent stops, triggers this hook, and passes detailed error metrics and session context as a JSON payload to the script's standard input (stdin).
Incorrect:
[Not B]
sessionEnd - Agent session completes or is terminated.
Reference:
https://awesome-copilot.github.com/learning-hub/automating-with-hooks/
NEW QUESTION # 47
Hotspot Question
You have a GitHub repository that uses GitHub Actions to validate pull requests opened by the GitHub Copilot coding agent. The workflow runs unit tests and a linter on pull request triggers, and Copilot opens draft pull requests on dedicated branches while iterating by using commits.
You discover that when multiple Copilot sessions push updates to the same pull request branch in quick succession, multiple workflow runs execute concurrently.
You need to enable parallel workflow executions across different pull request branches.
How should you configure workflow-level concurrency? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Set the concurrency at the workflow level
Isolates this concurrency rule to this specific workflow so it does not accidentally cancel other automation types.
Box 2: group:${{ github.head_ref || github.run_id}}
${{ github.head_ref }}: Evaluates to the source branch name during pull_request triggers, grouping all consecutive Copilot pushes to that specific branch together.
|| github.run_id: Serves as a fallback for non-PR triggers (like a direct push to main), ensuring the workflow still runs safely without canceling itself.
Reference:
https://www.meziantou.net/how-to-cancel-github-workflows-when-pushing-new-commits-on-a-branch.htm
NEW QUESTION # 48
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