Documentation Writer

Overview

This skill specializes in creating clear, comprehensive, and well-structured technical documentation. It helps with READMEs, API documentation, user guides, and inline code comments.

Instructions

When creating or improving documentation:

•Identify Audience: Determine who will read this documentation (developers, end-users, etc.)
•Structure Content: Organize information logically with clear sections
•Be Clear and Concise: Use simple language and avoid jargon when possible
•Provide Examples: Include code examples and use cases
•Keep Updated: Ensure documentation matches current implementation

Documentation Elements

README Structure

•Project title and description
•Installation instructions
•Quick start guide
•Usage examples
•API reference (if applicable)
•Contributing guidelines
•License information

API Documentation

•Endpoint/function purpose
•Parameters with types and descriptions
•Return values
•Error handling
•Example requests and responses

Examples

Example 1: Function Documentation

Input:

python

def process_data(data, filter=None):
    # Process the data
    result = []
    for item in data:
        if filter and not filter(item):
            continue
        result.append(transform(item))
    return result

Output:

python

def process_data(data, filter=None):
    """
    Process and transform a collection of data items with optional filtering.
    
    Args:
        data (list): A list of items to process
        filter (callable, optional): A function that returns True for items 
            to include. If None, all items are processed.
    
    Returns:
        list: A list of transformed items that passed the filter
    
    Example:
        >>> data = [1, 2, 3, 4, 5]
        >>> process_data(data, filter=lambda x: x > 2)
        [3, 4, 5]
    """
    result = []
    for item in data:
        if filter and not filter(item):
            continue
        result.append(transform(item))
    return result

Example 2: README Section

Input: Project is a web scraper

Output:

markdown

# Web Scraper Tool

A lightweight, efficient web scraping library for extracting structured data from websites.

## Features
- 🚀 Fast and asynchronous scraping
- 🛡️ Built-in rate limiting and error handling
- 📊 Export data to JSON, CSV, or databases
- 🔍 CSS and XPath selector support

## Installation

```bash
pip install web-scraper-tool

Quick Start

python

from scraper import WebScraper

# Initialize scraper
scraper = WebScraper()

# Scrape a website
data = scraper.scrape('https://example.com', {
    'title': 'h1.title',
    'price': '.price'
})

print(data)

Documentation

For detailed documentation, visit docs.example.com

code


## Notes
- Keep documentation up-to-date with code changes
- Use consistent formatting and style
- Include visual aids when helpful (diagrams, screenshots)
- Test all code examples to ensure they work
- Consider internationalization for broader audiences