Prompt Engineering  

Write Prompts to Generate Code Documentation with AI

🚀 Introduction: Documentation Made Easy

Most developers love coding, but hate writing documentation. Clear documentation is critical for:

  • Onboarding new developers

  • API integration

  • Debugging & maintenance

  • Knowledge sharing

AI can now generate docstrings, code explanations, and API docs — saving hours of work. But it depends on how you prompt it.

📌 Types of Code Documentation Prompts

1. Docstring Generation

Prompt
"Generate a Python docstring for this function that calculates factorial recursively."

Code Example

def factorial(n): if n == 0: return 1 return n * factorial(n-1)

AI Output

""" Calculates the factorial of a number recursively. Args: n (int): Non-negative integer. Returns: int: Factorial of the given number. """

2. Code Explanation for Beginners

Prompt
"Explain this C# LINQ query in plain English for junior developers."

Code Example

var highScores = students.Where(s => s.Score > 80).Select(s => s.Name);

AI Output

  • “This code filters students with scores above 80 and extracts only their names.”

3. API Documentation

Prompt
"Write OpenAPI-style documentation for this REST API endpoint: GET /users/{id} that returns user profile data."

AI Output

paths: /users/{id}: get: summary: Get user profile parameters: - name: id in: path required: true schema: type: string responses: '200': description: Successful response

4. Codebase Summarization

Prompt
"Summarize what this entire Java class does in under 5 sentences."

AI Output

  • “This class manages customer orders, including creation, validation, and cancellation. It connects to the OrderService API and ensures transaction consistency.”

5. Inline Comments

Prompt
"Add helpful inline comments to this JavaScript function that validates email format."

Code Example

function validateEmail(email) { return /^[^\s@]+@[^\s@]+\.[^\s@]+$/.test(email); }

AI Output

function validateEmail(email) { // Regex checks for a valid email structure: [email protected] return /^[^\s@]+@[^\s@]+\.[^\s@]+$/.test(email); }

👉 Related read: Best Practices for Clean Code 🔗

📊 Quick Prompt Templates for Documentation

TaskExample Prompt
Docstring“Generate Python docstrings for all functions in this file.”
Code Comments“Add explanatory inline comments for this JavaScript function.”
Explain Code“Explain this SQL query in simple terms.”
API Docs“Write API documentation in OpenAPI format for this endpoint.”
Summarize Code“Summarize what this C# class does in 3 sentences.”

✅ Benefits

  • Saves time writing repetitive documentation

  • Improves developer onboarding

  • Ensures consistent documentation style

  • Supports multi-language codebases

⚠️ Challenges

  • AI may oversimplify or miss details

  • Still requires developer review

  • Needs prompt precision (docstring vs. API doc vs. comments)

📚 Learn AI for Developer Productivity

AI is transforming software development — and documentation is a big win.

🚀 Learn with C# Corner’s Learn AI Platform

At LearnAI.CSharpCorner.com, you’ll learn:

  • ✅ How to generate docstrings, API docs, and inline comments

  • ✅ AI-powered tools for code explanation & summaries

  • ✅ Integrating AI into CI/CD pipelines for docs automation

  • ✅ Real-world projects in developer productivity

👉 Start Learning Prompt Engineering for Developers

🧠 Final Thoughts

Writing docs no longer has to be painful. With the right prompts, AI can:

  • Write docstrings

  • Explain complex code

  • Generate API documentation

  • Keep teams aligned

Think of AI as your documentation assistant — fast, consistent, and available 24/7.

Membership not found