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You have a custom agent profile file named test-agent.agent.md that contains the following YAML frontmatter:
---
name: test-agent
description: Custom agent description
tools: ['tool-a', 'tool-b']
---
In the same repository, you have an MCP configuration file named mcp.json.
You need to ensure that the GitHub Model Context Protocol (MCP) server is available to test the agent. The solution must allow only the Copilot toolset.
What should you do?
Answer : C
The copilot/* toolset grants the agent access to the Copilot-provided tools while avoiding unrelated tool groups. This directly meets the requirement to allow only the Copilot toolset for the test agent.
Keeping tool-a and tool-b would expand access beyond the stated requirement. Using github/* would expose the broader GitHub tool group rather than limiting the profile to the Copilot toolset. The MCP configuration retains its server structure; changing the server property name does not configure which tools the agent may use.
Toolsets are an important control surface for specialized agents. They let an architect define a narrow capability set for testing, planning, review, or implementation roles. The selected toolset should still be backed by an available and authorized MCP configuration; naming a toolset does not bypass server authentication or policy restrictions.
Study-guide topics: MCP toolsets, custom agent capabilities, and least-privilege tool access.
===============
A developer uses the GitHub Copilot CLI in plan mode.
Copilot produces a plan.
What does Copilot do next?
Answer : B
In plan mode, Copilot creates a plan before implementation and saves that plan to plan.md. This makes the proposed approach available for review, refinement, and continuation rather than immediately executing repository changes.
The plan file creates a durable handoff point between planning and implementation. A developer can inspect the proposed work, assess dependencies and risk, adjust tasks, and decide whether implementation should proceed. This separation is essential for workflows that require approval before modification.
Plan mode does not automatically open a pull request or create a branch. It also does not begin implementation simply because a plan was generated. Those actions require a subsequent transition to an implementation workflow or a direct instruction from the user.
Study-guide topics: planning mode, durable plans, state persistence, and staged agent execution.
===============
You have a GitHub repository that contains an agent named Orchestrator. Orchestrator delegates work to the following specialized subagents:
Planner reviews issues and creates a plan of action.
Implementer writes code based on the plan of action.
Reviewer reviews the code.
You create a new agent named Summarizer that produces a concise summary of the work performed by the other agents.
You need to ensure that Orchestrator can invoke Summarizer as part of its workflow.
What should you do?
Answer : A
The configuration must be changed on the agent that performs the delegation. Orchestrator is responsible for coordinating the workflow, so its allowed subagent list must include Summarizer. Adding the new agent to that list makes it an available delegation target alongside Planner, Implementer, and Reviewer.
An agent's agents property identifies the custom agents it can invoke as subagents. The tools property serves a different purpose: it identifies available capabilities such as reading files, editing code, or invoking agents. Adding a custom agent's name to the tools list does not register that agent as a callable subagent. The agent invocation tool must also be available; the scenario already establishes that Orchestrator delegates to other subagents.
Changing Reviewer's configuration would enable a relationship originating from Reviewer, rather than the requested direct invocation by Orchestrator. A handoff also represents a different interaction pattern from having the orchestrating agent invoke a subagent and receive its result.
Availability does not force execution on every task. Orchestrator's instructions should indicate when a summary is required and what information it should contain.
Study-guide topics: delegation permissions, orchestrator responsibilities, and specialized subagents. Reference: VS Code---Subagents.
===============
You have a GitHub repository that uses the GitHub Copilot coding agent to run agent plans for assigned issues.
You discover that some issues contain ambiguous implementation steps.
You need to reduce the likelihood that Copilot executes plans based on ambiguous implementation steps.
What should you do?
Answer : B
The most effective intervention occurs before the issue becomes an executable assignment. Acceptance criteria define the observable conditions that constitute success, while implementation directions establish boundaries and clarify how the work should proceed. Providing both before assignment reduces the need for the agent to infer missing requirements during planning.
Applied to this scenario, the issue should distinguish required outcomes from optional improvements and identify constraints that the implementation must respect. Where steps are ambiguous, the author should resolve the ambiguity or explicitly require clarification before execution. Reviewable criteria also give the agent and maintainers a shared basis for evaluating whether the resulting changes satisfy the original request.
Options A and D intervene after assignment or execution has begun. They may support later correction, but they do not prevent the initial plan from being based on unclear directions. Option C addresses dependency availability, which is a separate environmental concern.
The governing design principle is to make the task sufficiently definite before delegating action. Relevant curriculum topics include defining inputs and success criteria, validating agent plans, and separating preparation from execution.
===============
While using agent mode in VS Code, you want Copilot to run a specific test suite as a validation step after making changes, without manually invoking the terminal each time. What feature enables this?
Answer : B
In VS Code agent mode, GitHub Copilot can use built-in tools to perform actions required to complete and validate a development task. One of these capabilities is the terminal tool, which allows the agent to execute commands such as builds, linters, package-management operations, and test suites directly through VS Code's integrated terminal. The user can explicitly instruct the agent to make changes and then run a designated test command to verify the result.
The relevant control is the agent's tool and terminal invocation permissions. Depending on configured approval policies, Copilot can request authorization for a terminal command or execute approved commands as part of its iterative workflow. This allows validation to become part of the agent's task rather than requiring the developer to manually open the terminal after every modification. GitHub documentation specifically describes agent mode as capable of making edits, issuing terminal commands, observing results, and iterating when necessary.
Option A is unnecessary because running a local test suite does not require an MCP server. .copilotignore concerns context/access exclusions, while CODEOWNERS defines repository ownership and review responsibilities rather than agent execution capabilities.
Study Guide Reference Topics: Implement Tool Use and Environment Interaction; terminal tools; agent permissions; automated validation; iterative tool execution.
