How to Use GitHub Copilot for Code Documentation

According to empirical studies, 58%-70% of developers’ working time is spent reading and understanding existing code rather than writing it. Yet, most codebases have documentation that’s either outdated, incomplete, or nonexistent.

In this article, we’ll show you how to streamline your documentation process and keep your team aligned by using GitHub Copilot’s AI-powered suggestions. You’ll see how you can generate docstrings, inline comments, and README files directly in your IDE, and then integrate those docs into a sustainable workflow with ClickUp.

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Why Code Documentation Is So Challenging

The main problems with code documentation can be broken down into these simple points:

• Outdated info: Documentation often becomes outdated the moment code changes, creating a gap between what the code does and what the docs say it does
• Missing experts: When original developers leave a project, their undocumented code becomes a black box that slows down the entire team, creating knowledge silos. This contributes to context sprawl—teams waste hours searching for information across disconnected apps, hunting down files, and switching between platforms. It also makes knowledge transfer nearly impossible. New team members face a steep learning curve, struggling to contribute effectively
• Time trade-offs: Faced with tight deadlines, most developers focus on shipping features first, which makes it tough to keep documentation up to date and builds technical debt over time. It’s not just about time constraints—it’s about the friction involved. The constant context switching between writing code and writing prose breaks a developer’s flow state, reducing productivity and making documentation feel like a chore
• Legacy code complexity: Older, complex codebases often have minimal or misleading documentation, making them much harder to decipher and update
• Growing pains: Even in projects that start with great intentions, documentation drift is inevitable. As the codebase grows in complexity and features evolve, the docs fall out of sync, eroding trust and rendering them less maintainable

Using GitHub Copilot for code documentation can be a game-changer for developers, engineering teams, and anyone maintaining codebases who struggle to keep documentation current.

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What You Need Before Using GitHub Copilot for Documentation

Jumping into a new tool without the right setup is a recipe for frustration. Before you start generating documentation, quickly run through this checklist to make sure your workspace is ready. This will save you from hitting roadblocks later.

• GitHub account with Copilot access: Copilot is a subscription-based service. You’ll need an active subscription, whether it’s for an individual, business, or enterprise plan
• Supported IDEs: While VS Code is the most common environment, Copilot also integrates smoothly with the JetBrains suite of IDEs (like PyCharm or WebStorm), Visual Studio, and Neovim
• Copilot extension installed: You must install the official GitHub Copilot extension from your IDE’s marketplace and authenticate it with your GitHub account
• Copilot Chat enabled: For documentation tasks, Copilot Chat is your most powerful tool. It provides a conversational interface for making requests, which is far more effective for generating explanations than relying on inline suggestions alone
• Repository access: Ensure you have at least read access to the code repository you intend to document. You can’t document what you can’t see
• Basic understanding of documentation formats: While Copilot does the heavy lifting, having a basic familiarity with docstrings, Markdown, and your programming language’s specific documentation conventions will help you guide the AI more effectively

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How GitHub Copilot Helps With Code Documentation

Think of GitHub Copilot as a coding assistant that understands the context of your code. It doesn’t just guess; it reads your function signatures, variable names, and surrounding logic to generate relevant documentation.

Using GitHub Copilot for code documentation streamlines a tedious process into a few simple actions.

Here’s how it works in practice:

• Inline suggestions: As you begin typing comment markers (like // or #) or docstring syntax (like """), Copilot anticipates your intent and auto-completes with context-aware documentation
• Copilot Chat for explanations: You can open a chat window and ask Copilot to explain what a function or code block does. It will generate a clear, documentation-ready summary that you can copy and paste
• Selection-based documentation: Simply highlight a block of code, right-click, and prompt Copilot to document that specific selection. This is perfect for targeting complex functions or classes
• Multi-language support: Copilot isn’t limited to one language. It works across Python, JavaScript, TypeScript, Java, C#, Go, and many other popular programming languages
• Context awareness: This is Copilot’s superpower. It doesn’t just look at the code in isolation; it analyzes how different parts of your file interact to generate more accurate and helpful descriptions

To see how AI agents are transforming coding workflows beyond just documentation, watch this video.

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Step-by-Step Guide to GitHub Copilot Documentation Generation

This workflow is your GitHub Copilot tutorial for turning an unfamiliar or undocumented codebase into a well-documented asset. By following these steps, you can systematically create comprehensive documentation with AI. 🛠️

Step 1: Understand the codebase structure

You can’t document what you don’t understand. When you’re faced with a new or complex project, your first step is to get a high-level overview. Instead of spending hours manually tracing connections, use Copilot Chat as your guide.

Open the main project folder in your IDE and ask Copilot Chat broad questions to get oriented.

• “Explain the overall structure of this repository”
• “What are the main modules and how do they interact?”
• “Summarize what this file does”

A practical tip is to start with the application’s entry points, like main.py, index.js, or the primary API routes file. Understanding where the program begins helps you follow the flow of logic and dependencies outward.

Step 2: Generate function and class summaries

This is where you’ll feel Copilot’s immediate impact. Generating docstrings—the summaries that explain what a function or class does—is incredibly fast. The workflow is simple: place your cursor, type the starting syntax for a docstring, and let Copilot handle the rest.

• For Python: Place your cursor on the line after a function definition and type """. Copilot will instantly suggest a complete docstring, including descriptions for parameters (Args), return values (Returns), and any exceptions the function might raise (Raises)
• For JavaScript/TypeScript: Place your cursor above a function and type /**. Copilot will generate JSDoc-style comments, which are standard for documenting JavaScript codebases

You can also use Copilot Chat for more control. Highlight an entire function or class and ask it directly: “Document this function, including parameters and return type.”

Step 3: Add inline comments for complex logic

While docstrings explain the what, inline comments explain the why. Your goal here isn’t to restate what the code does, but to clarify the intent behind non-obvious decisions. This is crucial for future maintainability.

Focus on the trickiest parts of your code. Highlight a complex block and ask Copilot Chat, “Explain this logic step by step.” Then, take its explanation and distill it into a concise inline comment.

Good places to add inline comments include:

• Complex regular expressions (regex)
• Performance optimizations that use unconventional logic
• Workarounds for known bugs or third-party library issues
• Business logic that isn’t immediately obvious from variable names alone

Step 4: Create README and project documentation

Once you’ve handled the code-level documentation, it’s time to zoom out to the project level. A good README file is the front door to your project, and Copilot can help you build one that stands out, much like the best API documentation.

Here’s how to proceed:

• Create a new README.md file in your project’s root directory
• Use Copilot Chat to generate the main sections. For example, you can ask: “Generate a README for this project, including installation, usage, and contributing sections.” Copilot will scan your project files (like package.json or requirements.txt) to create accurate installation instructions and usage examples
• You can then refine and customize the generated Markdown to fit your project’s specific needs. This same process works for creating CONTRIBUTING.md or other high-level project documents

Step 5: Review and refine AI-generated documentation

This is the most important step. AI-generated documentation is a powerful starting point, but it is not a finished product. Always treat it as a first draft that requires human review and refinement.

Use this checklist to guide your review:

• Accuracy: Does the documentation correctly describe what the code actually does?
• Completeness: Are all parameters, return values, and potential exceptions documented?
• Clarity: Would a new team member understand this without needing to ask for help?
• Consistency: Does the tone and style match your team’s established documentation standards?
• Edge cases: Are important limitations or potential edge cases mentioned?

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GitHub Copilot Documentation Example in Action

Let’s look at a concrete example. Imagine you encounter this undocumented Python function in a legacy codebase:

def process_user_data(user_dict, validate=True):
    if validate and not user_dict.get('email'):
        raise ValueError("Email required")
    cleaned = {k: v.strip() if isinstance(v, str) else v for k, v in user_dict.items()}
    cleaned['processed_at'] = datetime.now()
    return cleaned

It’s not immediately clear what it does or why. You can highlight the function and ask Copilot Chat: “Document this function including parameters, return type, and exceptions.”

Within seconds, Copilot provides the following:

def process_user_data(user_dict, validate=True):
    """
    Process and clean user data dictionary.

    This function takes a dictionary of user data, strips leading/trailing
    whitespace from all string values, and adds a processing timestamp.
    It can optionally validate that an email address is present.

    Args:
        user_dict (dict): A dictionary containing user information.
        validate (bool): If True, validates that the 'email' key exists.
                         Defaults to True.

    Returns:
        dict: A new dictionary with cleaned user data and an added
              'processed_at' timestamp.

    Raises:
        ValueError: If 'validate' is True and the 'email' key is missing
                    from the user_dict.
    """
    # Raise an error if validation is on and the email is missing.
    if validate and not user_dict.get('email'):
        raise ValueError("Email required")
    
    # Clean the dictionary by stripping whitespace from string values.
    cleaned = {k: v.strip() if isinstance(v, str) else v for k, v in user_dict.items()}
    
    # Add a timestamp to record when the processing occurred.
    cleaned['processed_at'] = datetime.now()
    return cleaned

This example shows GitHub Copilot documentation generation for a single function. For larger codebases, you can repeat this process systematically, starting with public APIs and working toward internal utilities.

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Best Practices for AI-Powered Code Documentation

Generating documentation is only half the battle. The real challenge is keeping it useful and up-to-date. This is where you need to move beyond the IDE and integrate documentation into your team’s core workflows.

Combine GitHub Copilot with project management tools

Centralize your documentation and development tasks to eliminate chaos and keep your team aligned. Combine GitHub Copilot with project management tools like ClickUp to create specific, assignable work items for documentation, link them directly to code changes, and build a centralized knowledge base that integrates with your workflow—empowering your team to take action faster.

ClickUp makes it easy to do this with the native GitHub integration. This is particularly handy when multiple Git repositories feed into the same product area, and you still want a single source of truth for status and context.

Keep documentation synced with code changes

The moment code changes, documentation starts to decay. This “documentation drift” is what makes most team wikis unreliable. You can fight back by building a process that keeps your docs in sync with your code.

• Document during PR review: Make documentation updates a mandatory part of your team’s pull request checklist, a key step in any solid development workflow. No code gets merged until the docs are updated
• Use Copilot on changed files: As part of the code review process, reviewers can use Copilot to quickly verify that the documentation still accurately reflects the modified code
• Automate reminders: Don’t rely on memory. Set up automated workflows that flag PRs that touch undocumented code or remind developers to update docs

Make documentation updates seamless and trackable by automating review tasks with ClickUp Automations whenever a GitHub pull request is merged. By linking GitHub PRs directly to ClickUp Tasks, you ensure documentation is always visible and part of every code change.

Use AI to maintain documentation standards

Inconsistent documentation is confusing. When developers use slightly different styles, the codebase becomes harder to read, and new team members struggle to get up to speed. AI can help enforce consistency across the board.

Start by creating a clear documentation style guide. Then, you can reference it directly in your Copilot prompts, like “Document this function following our team’s JSDoc standards.”

You can also use Copilot to audit existing documentation, asking it to “Review this file for any functions missing docstrings.”

💡Pro Tip: In ClickUp, you can create documentation guidelines and templates in seconds with ClickUp Brain, the integrated AI assistant.

Try ClickUp Brain

To make this process scalable, store your official documentation style guide in ClickUp Docs. This creates a shared knowledge management system that everyone on the team can access.

When a new developer has a question about standards, they can ask ClickUp Brain, which uses your Docs as a knowledge source to provide instant, accurate answers without interrupting a senior engineer.

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Limitations of Using GitHub Copilot for Code Documentation

While Copilot is a powerful ally, it’s important to be aware of its limitations. Treating it as a magic wand can lead to problems down the road.

• Context window limits: Copilot can only “see” a portion of your codebase at once. For highly complex systems with many interconnected files, it may not grasp the full picture, leading to incomplete or slightly inaccurate suggestions
• Accuracy requires verification: The generated documentation can sometimes contain subtle errors, especially for nuanced or proprietary business logic. It’s a great first draft, but it always needs a human eye
• No institutional knowledge: Copilot understands what the code does, but it has no idea why a particular decision was made. It can’t capture the historical context or business trade-offs that led to a specific implementation
• Subscription required: Unlike some free AI tools, Copilot requires a paid subscription for most users, which can be a consideration for individuals or small teams
• Language and framework variations: The quality of suggestions can vary. Copilot is exceptionally strong with popular languages like Python and JavaScript, but may be less effective with more niche languages or brand-new frameworks

These limitations don’t make Copilot unsuitable for documentation. They simply highlight why combining AI assistance with robust workflow tools creates a far better outcome than relying on any single tool alone.

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Alternative to GitHub Copilot for Code Documentation

Teams that treat documentation as an integral part of their workflow—not an afterthought—ship features faster and build a more resilient, maintainable codebase. While GitHub Copilot is fantastic for generating documentation inside your IDE, it doesn’t solve the larger problem.

How do you organize, track, and maintain that documentation as a collaborative team asset? This is where a converged workspace becomes essential.

While Copilot helps you write the docs, ClickUp helps you manage the entire documentation lifecycle. Eliminate context sprawl with ClickUp—a Converged AI Workspace that brings all your work, data, and workflows into a single platform.

Here are just some of the reasons to try ClickUp today:

• Store and collaborate on all your project documentation, API references, and README files in one central, searchable place with ClickUp Docs
• Empower team members to find the answers to common questions like “How does our authentication module work?” with ClickUp Brain, which surfaces the right answers using context from your workspace and official documentation
• Automate repetitive tasks with ClickUp Automations, so your engineering team stays focused and clears backlogs efficiently
• Keep teams updated without effort by setting up AI Agents in ClickUp to track essential updates or missing documentation and alert you

GitHub Copilot helps you write documentation. ClickUp helps you manage it. Together, they solve the full documentation challenge. ✨

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Ease Your Code Documentation Woes With ClickUp

Outdated documentation slows teams down, creates knowledge silos, and makes onboarding a nightmare. GitHub Copilot transforms code documentation from a dreaded chore into an efficient, AI-assisted workflow.

However, the key to success is combining that AI-generated content with human review and a sustainable team process. Documentation that stays current and trustworthy requires both good tools and good habits.

With ClickUp and its GitHub integration, code documentation and its consistent management become a breeze. By using AI for the heavy lifting, you free up your developers to focus on what matters most: ensuring accuracy, completeness, and clarity.

Ready to bring your documentation workflow together with your development tasks? Get started for free with ClickUp and start streamlining your process today.

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