GitHub Copilot Customization Explained for Beginners: Instructions, Prompt Files, Skills, Agents, and Hooks
Introduction
If you've recently started using GitHub Copilot, you've probably come across terms like Instructions, Prompt Files, Skills, Agents, and Hooks. At first glance, they all seem to do the same thing—they tell Copilot what to do.
So why does GitHub have five different customization features?
The answer is simple: each feature solves a different problem.
Think of GitHub Copilot as a new developer joining your team. On their first day, you don't just hand them code. You explain your coding standards, give them reusable templates, teach them specialized knowledge, assign them a role, and automate repetitive tasks.
That's exactly how GitHub Copilot customization works.
In this article, you'll learn what each feature does, when to use it, and how they all work together. By the end, you'll know which feature to start with and which ones can wait until you're more experienced.
Why GitHub Copilot Needs Customization
Out of the box, GitHub Copilot is trained on a vast amount of public code and documentation. That makes it a great general-purpose coding assistant, but it doesn't know anything about your project.
For example, it doesn't automatically know:
Your coding standards
Your preferred architecture
Your naming conventions
Your deployment process
Your company guidelines
Your testing framework
Customization bridges that gap by giving Copilot context about your project.
Instead of repeating the same instructions in every chat, you teach Copilot once and let it remember.
Understanding the Big Picture
The easiest way to understand GitHub Copilot customization is to compare it to a software development team.
| GitHub Copilot Feature | Real-Life Analogy |
|---|---|
| Instructions | Company policies |
| Prompt Files | Reusable templates |
| Skills | Technical expertise |
| Agents | Specialized employees |
| Hooks | Automation scripts |
Each feature builds on the previous one.
Let's look at them one by one.
1. Custom Instructions
What Are Instructions?
Instructions are project-wide rules that GitHub Copilot automatically follows every time it generates code or answers questions.
Think of them as your team's coding standards.
Instead of repeatedly saying:
Use Java 21
Use Spring Boot 3
Write JUnit 5 tests
Use constructor injection
Follow REST API naming conventions
you define these rules once.
Whenever Copilot works inside your repository, those rules are already available.
Where Are Instructions Stored?
Typically, you'll create:
.github/
└── copilot-instructions.md
You can also create additional instruction files for specific folders if different parts of your project follow different conventions.
Example
Suppose every Spring Boot project in your company follows these standards.
# GitHub Copilot Instructions
Always:
- Use Java 21
- Use constructor injection
- Use Lombok
- Use JUnit 5
- Follow REST naming standards
- Add JavaDoc to public methods
Now when you ask: Create a REST Controller
Copilot already knows your preferred coding style.
No need to explain it every time.
When Should You Use Instructions?
Instructions are perfect for information that rarely changes.
Examples include:
Coding standards
Naming conventions
Project architecture
Framework versions
Documentation style
Testing strategy
Think of Instructions as permanent project rules.
2. Prompt Files
What Are Prompt Files?
Prompt Files are reusable prompts that you can run whenever you need them.
Unlike Instructions, they are not loaded automatically.
Instead, you choose them for a specific task.
Why Use Prompt Files?
Imagine that every Friday you generate API documentation.
Each time, you write:
Generate Swagger documentation
Create examples
Explain endpoints
Include request and response payloads
That's repetitive.
Instead, save that prompt once.
Folder Structure
.github/
└── prompts/
├── generate-api.prompt.md
├── code-review.prompt.md
└── security-review.prompt.md
Example Prompt File
Generate a complete Spring Boot REST API.
Requirements:
- DTOs
- Validation
- Swagger
- Unit Tests
- Exception Handling
- Service Layer
- Repository Layer
Next time, instead of writing a long prompt, simply reference the prompt file.
Best Use Cases
Prompt Files work well for repetitive activities such as:
API generation
Code reviews
README creation
Test generation
Documentation
Database migrations
Think of Prompt Files as reusable templates.
3. Skills
Now we move beyond prompts.
Skills teach Copilot how to perform specialized tasks.
What Is a Skill?
A Skill is a collection of knowledge focused on one specific area.
It can contain:
Documentation
Examples
Scripts
Best practices
Reference material
The important part is that Copilot loads a Skill only when it's relevant.
Folder Structure
.github/
└── skills/
└── kubernetes/
├── SKILL.md
├── examples/
└── scripts/
Example
Suppose your team deploys applications to Kubernetes.
Your Skill could include:
Deployment process
Rollback procedure
Troubleshooting guide
kubectl examples
Helm commands
Now if you ask: Deploy the application to Kubernetes
Copilot automatically uses that specialized knowledge.
Instructions vs Skills
Many beginners confuse these two.
The difference is simple.
Instructions are always loaded.
Skills are loaded only when necessary.
If every request should follow a rule, use Instructions.
If only Kubernetes questions need Kubernetes knowledge, create a Skill.
4. Agents
Imagine your development team.
One developer focuses on security.
Another writes documentation.
Another reviews pull requests.
GitHub Copilot can work the same way.
What Is an Agent?
An Agent is a specialized AI assistant designed for a particular responsibility.
Instead of one general-purpose Copilot, you can have multiple experts.
Examples include:
Security Agent
Documentation Agent
Backend Agent
Frontend Agent
Database Agent
DevOps Agent
Each agent has its own instructions, tools, permissions, and context.
Example
Suppose you ask: Review my authentication code.
If you use a Security Agent, it already understands secure coding practices and focuses on vulnerabilities.
If you switch to a Documentation Agent, it explains the code and generates documentation instead.
Same code.
Different expertise.
When Should Beginners Use Agents?
Agents become valuable when:
Working in large teams
Managing enterprise projects
Handling specialized responsibilities
Using GitHub Copilot Agent Mode
For small personal projects, Instructions and Prompt Files are usually enough.
5. Hooks
Hooks are different from every feature we've discussed.
They don't provide instructions.
They perform actions automatically.
What Is a Hook?
A Hook runs commands during an Agent workflow.
Instead of reminding Copilot to perform repetitive tasks, Hooks do them automatically.
Example
Imagine every code change should be formatted.
Without Hooks:
Generate code.
Run formatter.
Run tests.
Fix issues.
Commit changes.
With Hooks:
Generate code.
Hook automatically formats the project.
Hook runs unit tests.
Hook validates the build.
Everything happens without manual intervention.
Common Hook Examples
Run unit tests
Execute Maven build
Run ESLint
Check formatting
Validate Terraform
Scan for secrets
Run security checks
Hooks are ideal for repetitive automation.
How All These Features Work Together
Let's see a complete workflow.
Imagine you're building a Spring Boot application.
Step 1
Instructions tell Copilot:
Use Java 21
Use Spring Boot 3
Follow REST standards
Step 2
You choose the Backend Agent.
Now Copilot behaves like a backend developer.
Step 3
You use a Prompt File.
It tells Copilot:
Generate a CRUD API with validation and Swagger.
Step 4
Copilot realizes Kubernetes deployment is involved.
It automatically loads the Kubernetes Skill.
Step 5
After generating the code, a Hook runs.
It automatically:
Formats the project
Executes tests
Builds the application
You didn't need to ask for any of these steps.
Which Feature Should Beginners Learn First?
Here's the learning path I recommend.
1. Instructions
Start here.
They improve every Copilot interaction.
2. Prompt Files
The easiest productivity improvement.
Perfect for repetitive work.
3. Skills
Learn Skills once you're working on medium or large projects.
4. Agents
Useful when your workflow becomes more specialized.
5. Hooks
Learn Hooks after becoming comfortable with Agent Mode and automation.
Common Beginner Mistakes
Mistake 1
Putting everything inside Instructions.
Instructions should remain short and contain only project-wide rules.
Mistake 2
Creating Prompt Files for information that never changes.
That's what Instructions are for.
Mistake 3
Using Skills for simple prompts.
Skills should contain specialized knowledge rather than one-off prompts.
Mistake 4
Creating too many Agents.
Start with one or two specialized agents before expanding.
Mistake 5
Ignoring Hooks.
If you repeatedly run the same commands after generating code, Hooks can save significant time.
Quick Cheat Sheet
| Feature | Best For | |
|---|---|---|
| Instructions | Project standards | |
| Prompt Files | Reusable prompts | |
| Skills | Specialized expertise | |
| Agents | Different AI roles | |
| Hooks | Workflow automation |
Conclusion
GitHub Copilot has evolved into much more than an autocomplete tool. With the right customization, it becomes a teammate that understands your project's standards, performs repetitive tasks, applies specialized knowledge, and even automates parts of your development workflow.
If you're just starting out, don't try to learn everything at once. Begin with Custom Instructions to teach Copilot your project's coding standards. Next, create Prompt Files for the tasks you perform repeatedly. As your projects grow, explore Skills for domain-specific expertise, Agents for role-based assistance, and Hooks to automate routine workflows.
Have you started customizing GitHub Copilot yet? Share your experience or your favorite workflow in the comments below!
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