GitHub GitHub Copilot Practice Exams
Last updated on Oct 21,2026- Exam Code: GitHub Copilot
- Exam Name: GitHub Copilot Certification Exam
- Certification Provider: GitHub
- Latest update: Oct 21,2026
What role does chat history play in GitHub Copilot’s code suggestions?
- A . Chat history is used to train the GitHub Copilot model in real-time.
- B . Chat history provides context to GitHub Copilot, improving the relevance and accuracy of its code suggestions.
- C . Chat history is stored and shared with other users to enhance collaboration.
- D . Chat history is irrelevant to GitHub Copilot and does not affect its functionality.
B
Explanation:
Chat history provides valuable context to GitHub Copilot, helping it generate more relevant and accurate code suggestions based on previous interactions and conversations.
Reference: GitHub Copilot Chat history documentation.
Which of the following is correct about GitHub Copilot Knowledge Bases?
- A . All repos are indexed
- B . Indexing is static
- C . It is an Enterprise feature
- D . All file types are indexed
C
Explanation:
GitHub Copilot Knowledge Bases is an Enterprise feature that allows the tool to use an organization’s internal documentation and code for more accurate and relevant suggestions.
Reference: GitHub Copilot Enterprise Knowledge Base documentation.
Which REST API endpoint is used to modify details about a GitHub Copilot Business subscription? (Each correct answer presents part of the solution. Choose two.)
- A . Add teams to the Copilot subscription for an organization
- B . Upgrade or downgrade the subscription tier
- C . Migrate Copilot seat assignments between GitHub organizations
- D . Reassign Copilot seats based on GitHub repository size
- E . Remove teams from the Copilot subscription for an organization
A, E
Explanation:
The REST API endpoints are used to add and remove teams from the Copilot Business subscription within an organization.
Reference: GitHub Copilot Business API documentation.
An independent contractor develops applications for a variety of different customers. Assuming no concerns from their customers, which GitHub Copilot plan is best suited?
- A . GitHub Copilot Individual
- B . GitHub Copilot Business
- C . GitHub Copilot Business for non-GHE Customers
- D . GitHub Copilot Enterprise
- E . GitHub Copilot Teams
A
Explanation:
For an independent contractor, GitHub Copilot Individual is the most suitable and cost-effective plan.
Reference: GitHub Copilot pricing documentation.
Which of the following describes role prompting?
- A . Describing in your prompt what your role is to get a better suggestion
- B . Tell GitHub Copilot in what tone of voice it should respond
- C . Prompt GitHub Copilot to explain what was the role of a suggestion
- D . Giving GitHub Copilot multiple examples of the form of the data you want to use
A
Explanation:
Role prompting involves explicitly stating your role or the persona you want GitHub Copilot to adopt within your prompt. This helps Copilot provide more contextually relevant and accurate suggestions. By defining your role (e.g., "As a senior software engineer," "As a technical writer"), you guide Copilot to tailor its responses to align with the expertise and perspective associated with that role. This improves the quality and relevance of the generated code and explanations.
Reference: GitHub Copilot documentation on prompt engineering and best practices.
What method can be used to interact with GitHub Copilot?
- A . By using a properly configured GitHub CLI
- B . By using chat capabilities in NeoVim
- C . From a watch window in an IDE debug session
- D . From a web browser at https://github.copilot.com
B
Explanation:
GitHub Copilot is an AI-powered code completion tool that integrates directly into supported Integrated Development Environments (IDEs) and code editors, such as Visual Studio Code, JetBrains IDEs, NeoVim, and others. Developers interact with it through their coding environment, where it provides real-time code suggestions, autocompletions, and (in some cases) chat-like capabilities via extensions or plugins (e.g., GitHub Copilot Chat in supported editors).
Evaluation of Options:
Select a strategy to increase the performance of GitHub Copilot Chat.
- A . Use a single GitHub Copilot Chat query to find resolutions for the collection of technical requirements
- B . Limit the number of concurrent users accessing GitHub Copilot Chat
- C . Apply prompt engineering techniques to be more specific
- D . Optimize the usage of memory-intensive operations within generated code
C
Explanation:
Applying prompt engineering techniques to be more specific is the best strategy to increase the performance and relevance of GitHub Copilot Chat’s responses.
Reference: GitHub Copilot prompt engineering best practices.
What GitHub Copilot feature can be configured at the organization level to prevent GitHub Copilot suggesting publicly available code snippets?
- A . GitHub Copilot Chat in the IDE
- B . GitHub Copilot Chat in GitHub Mobile
- C . GitHub Copilot duplication detection filter
- D . GitHub Copilot access to Bing
C
Explanation:
The duplication detection filter can be configured at the organization level to prevent GitHub Copilot from suggesting publicly available code snippets.
What are the potential risks associated with relying heavily on code generated from GitHub Copilot? (Each correct answer presents part of the solution. Choose two.)
- A . GitHub Copilot may introduce security vulnerabilities by suggesting code with known exploits.
- B . GitHub Copilot may decrease developer velocity by requiring too much time in prompt engineering.
- C . GitHub Copilot’s suggestions may not always reflect best practices or the latest coding standards.
- D . GitHub Copilot may increase development lead time by providing irrelevant suggestions.
A, C
Explanation:
Heavy reliance on GitHub Copilot can introduce security vulnerabilities if the generated code contains known exploits. Additionally, Copilot’s suggestions may not always align with best practices or the latest standards, requiring careful review and validation.
Reference: GitHub Copilot best practices and risk management.
How do you generate code suggestions with GitHub Copilot in the CLI?
- A . Write code comments -> Press the suggestion shortcut -> Select the best suggestion from the list.
- B . Use copilot suggest -> Write the command you want -> Select the best suggestion from the list.
- C . Type out the code snippet -> Use the copilot refine command to enhance it -> Review the suggested command.
- D . Describe the project’s architecture -> Use the copilot generate command -> Accept the generated suggestion.
A
Explanation:
In the CLI, GitHub Copilot generates code suggestions by analyzing code comments. You write comments describing what you want, and Copilot provides relevant code suggestions. You then select the best suggestion from the list.
Reference: GitHub Copilot CLI documentation.