GitHub Copilot Chat

GitHub Copilot Chat Cheat Sheet

GitHub Copilot Chat is an AI-powered chat interface built into GitHub’s ecosystem. It enables developers to ask questions in natural language and receive assistance with tasks such as code generation, explanations, debugging, refactoring, documentation, and testing.

GitHub.com – Copilot Chat panel on pull requests, issues, and code view.
IDEs
- Visual Studio Code
- Visual Studio
- JetBrains IDEs
- Xcode
- Eclipse
GitHub Mobile – Ask questions about repos & code on iOS/Android.
Command Line – GitHub Copilot CLI gives a chat-like experience in the terminal.
Windows Terminal – Copilot integration to explain & generate shell commands.

Always review generated code for correctness, security, license compatibility, and secrets exposure. Copilot Chat can be incorrect or insecure, even when it appears confident and accurate.

Key Features & Concepts

Core Capabilities

Capability	Description
Explaining code and concepts	Explains what code does or clarifies concepts. “What does this function do?”, “Explain async/await.”
Generating new code	Generates new functions, classes, components, scripts, and other boilerplate.
Debugging	Helps find and fix issues in code. “Why is this throwing a null reference error?”, use /fix on selected code.
Refactoring	Refactors code for readability, performance, or style while preserving behavior.
Generating unit tests	Creates unit tests using /tests or custom prompts for the selected code or file.
Adding documentation comments	Generates docstrings/comments using /doc or custom instructions.
Working across files & structure	Uses project context (e.g., @workspace, #file, #selection) to understand overall structure and relationships.

Customization & Context

Custom Instructions
Instruction Type	Description
Personal custom instructions	Define how responses should be written for a specific account (tone, level of detail, style).
Repository-wide instructions	Use .github/copilot-instructions.md to define repo-specific rules (coding style, frameworks, architecture patterns).
Organization instructions	Org-wide rules and policies (e.g., preferred internal libraries, security standards, coding guidelines).

Custom Sources
Context Source	How It’s Used
Current file/editor	Uses the code currently open in the editor as primary context.
Other open files	Considers additional files opened in the IDE for broader context.
Workspace codebase	Looks at the project/workspace code (via @workspace or #codebase, depending on environment).
Chat history	Uses prior messages in the conversation to maintain continuity and refine answers.
Explicit references	Uses explicit references like #file, #selection, specific symbols, links, or pasted snippets.
Prompting with context	Being explicit (e.g., “Explain the createUser function in #file:userService.ts”) improves results.

Models & Agents

Feature	Description
AI models	Define how responses should be written for a specific account (tone, level of detail, style).
Copilot coding agents / CLI	Use .github/copilot-instructions.md to define repo-specific rules (coding style, frameworks, architecture patterns).
Model Context Protocol (MCP)	Org-wide rules and policies (e.g., preferred internal libraries, security standards, coding guidelines).
Responsible	MCP and agents are powerful and can modify files or run commands; always review proposed plans and changes before applying them.

Permissions, Privacy & Limitations

Feature	Description
Scope & permissions	Features and capabilities depend on plan (Free/Pro/Business/Enterprise) and organization policies; some features (e.g., Copilot CLI, MCP) require specific plans and configuration.
Content exclusion	Organizations can configure content exclusion to prevent specific repositories or paths from being used as training data or context.
Intended usage	Copilot Chat is designed primarily for software-development questions and workflows, not as a general-purpose chatbot.

CONCLUSION

GitHub Copilot Chat brings conversational AI directly into the developer workflow across GitHub.com, IDEs, mobile, and the command line. It can explain unfamiliar code, generate new implementations, refactor existing logic, write tests and documentation, and reason across multiple files using project context. With custom instructions, context variables, and integrations such as Copilot CLI and MCP-based extensions, teams can tailor Copilot Chat to match their coding standards, tools, and architectures.

However, Copilot Chat is an assistant, not an authority: always review generated code for correctness, security, licensing, and performance before adopting it. Treat it as a powerful collaborator that accelerates everyday tasks while developers remain responsible for design decisions, code quality, and compliance.

REFERENCES

https://docs.github.com/en/copilot

https://docs.github.com/en/copilot/how-tos/chat-with-copilot

https://docs.github.com/en/copilot/reference/cheat-sheet

https://docs.github.com/en/copilot/how-tos/configure-custom-instructions

https://docs.github.com/en/copilot/how-tos/configure-custom-instructions/add-repository-instructions

https://docs.github.com/en/copilot/how-tos/provide-context/use-mcp/extend-copilot-chat-with-mcp

https://docs.github.com/en/copilot/tutorials/copilot-chat-cookbook

Written by: Ace Kenneth Batacandulo

Ace is AWS Certified, AWS Community Builder, and Cloud Consultant at Tutorials Dojo Pte. Ltd. He is also the Co-Lead Organizer of K8SUG Philippines and a member of the Content Committee for Google Developer Groups Cloud Manila. Ace actively contributes to the tech community through his volunteer work with AWS User Group PH, GDG Cloud Manila, K8SUG Philippines, and Devcon PH. He is deeply passionate about technology and is dedicated to exploring and advancing his expertise in the field.

GitHub Copilot Chat

GitHub Copilot Chat

GitHub Copilot Chat Cheat Sheet