WAQ-analyzer

Making Wikipedia quality assessment accessible with AI-enhanced insights

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AtiQr - Wikipedia Training Tool

A Wikipedia training tool designed for school Wikipedia clubs to help beginners, intermediate, and expert writers improve their editing skills. Get real-time analysis, side-by-side corrections, and learn Wikipedia guidelines through practice.

📚 Learn by Doing | 🎯 Real-time Corrections | 🌍 Multilingual Support | 📖 Wikipedia Guidelines Mastery

AtiQr Training Tool

🌟 Features

Dual Canvas Training Mode

  • 📝 Paste & Analyze: Paste your draft and see corrections side-by-side
  • 📖 Article Study Mode: Analyze existing Wikipedia articles to learn from good examples
  • 🎯 Visual Corrections: Original text vs. improved version with detailed explanations
  • 📋 Learning Points: Understand why each correction matters
  • 🔍 Citation Training: Learn where and how to add proper citations

Wikipedia Policy Compliance

  • ✅ Neutral Point of View (NPOV): Detect biased language and promotional content
  • 📚 Verifiability: Check citation requirements and source quality
  • 🚫 No Original Research: Flag unsourced claims and synthesis
  • ⚖️ Notability: Assess if topic meets notability guidelines
  • 🤝 Code of Conduct: Ensure respectful, collaborative tone

Quality Metrics

  • Readability Analysis: Flesch reading score, sentence complexity, vocabulary level
  • Citation Quality: Inline citations, citation density, reference formatting
  • Reference Assessment: Source reliability, diversity, and recency
  • Structural Analysis: Section organization, header hierarchy, content balance
  • Language Quality: Grammar, spelling, and style consistency

Multilingual Support

  • 🌍 8 Languages: English, French, Arabic, Swahili, Hausa, Yoruba, Amharic, Zulu
  • 🗣️ Language-specific Analysis: Adapted guidelines for different Wikipedia editions
  • 📖 Cross-language Learning: Study articles in multiple languages
  • 🎓 Beginner-friendly: Perfect for school Wikipedia clubs

Training Features

  • 📊 Progress Tracking: Track common mistakes and improvements over time
  • 🎯 Targeted Learning: Focus on specific Wikipedia guidelines
  • 💡 Learning Points: Understand the "why" behind each correction
  • 📱 Mobile Friendly: Practice on any device
  • 🔗 Guideline Links: Direct links to Wikipedia policy pages
  • 👥 Perfect for Groups: Ideal for school Wikipedia clubs and training sessions

Export Features

  • 🖨️ Print/PDF: Generate printable training reports with full analysis
  • 📝 Markdown: Export to Markdown format for documentation
  • 📊 CSV: Export corrections to spreadsheet format for tracking
  • 💾 JSON: Export complete analysis data for developers
  • 📤 Share with Teachers: Save and share your progress for feedback

🚀 Quick Start

Prerequisites

  • Node.js 18+ and npm
  • Modern web browser with JavaScript enabled

Installation

# Clone the repository
git clone https://github.com/your-username/atiqr.git
cd atiqr

# Install dependencies
npm install

# Start development server
npm run dev

The application will be available at http://localhost:5173

Building for Production

# Build the application
npm run build

# Preview the production build
npm run preview

📖 Usage Guide

Two Training Modes

1. Paste & Analyze Mode

  1. Write or paste your Wikipedia draft in the text area
  2. Select your language (English, French, Arabic, Swahili, etc.)
  3. Click "Analyze & Learn"
  4. Review corrections side-by-side with explanations

2. Article Study Mode

  1. Paste a Wikipedia article URL
  2. Click "Analyze & Learn"
  3. Study how the article follows (or breaks) Wikipedia guidelines
  4. Learn from good examples and identify areas for improvement

Understanding Corrections

AtiQr identifies three types of issues:

  • 🔴 Critical (Errors): Violations of core Wikipedia policies (NPOV, Verifiability, No Original Research)
  • 🟠 Important (Warnings): Style issues that affect article quality (weasel words, peacock terms)
  • 🔵 Suggestions: Recommendations for improvement (citation placement, structure)

Learning from Corrections

Each correction includes:

  • Original Text: What you wrote
  • Improved Version: How it should be written
  • Explanation: Why the change is needed
  • Guideline Link: Direct link to Wikipedia policy page
  • Category: Type of issue (citation, NPOV, style, etc.)

Common Issues AtiQr Catches

  1. Missing Citations: Factual claims without sources
  2. Biased Language: Words like "clearly", "obviously", "best"
  3. Weasel Words: Vague phrases like "some people say"
  4. Peacock Terms: Promotional language like "legendary", "world-famous"
  5. Original Research: Personal opinions or conclusions
  6. Poor Structure: Missing sections or unbalanced content

🛠️ Technical Architecture

Frontend Stack

  • React 18: Modern React with hooks and functional components
  • TypeScript: Type-safe development with full IntelliSense
  • Tailwind CSS: Utility-first CSS framework for rapid styling
  • Vite: Fast build tool and development server
  • Lucide React: Beautiful, consistent icon library

API Integration

  • Wikipedia REST API: Article content and metadata
  • Wikipedia Action API: Search functionality and article parsing
  • CORS Handling: Proper cross-origin request management

Code Organization

src/
├── components/          # Reusable UI components
│   ├── ArticleInput.tsx    # Search and URL input
│   ├── AnalysisResults.tsx # Main results display
│   ├── ScoreCard.tsx       # Individual metric cards
│   ├── SuggestionsList.tsx # Improvement recommendations
│   └── RecentAnalyses.tsx  # Analysis history
├── services/           # Business logic and API calls
│   ├── wikipediaApi.ts    # Wikipedia API integration
│   └── qualityAnalyzer.ts # Article analysis algorithms
├── types/              # TypeScript type definitions
│   └── index.ts           # Shared interfaces
└── App.tsx             # Main application component

🔧 Configuration

Environment Variables

No environment variables required for basic functionality. All APIs used are public and don't require authentication.

Customization Options

  • Scoring Weights: Modify weights in qualityAnalyzer.ts
  • UI Theme: Adjust colors in tailwind.config.js
  • API Endpoints: Configure in wikipediaApi.ts

🧪 Testing

# Run linting
npm run lint

# Type checking
npx tsc --noEmit

# Build test
npm run build

📱 Browser Support

  • Chrome 90+
  • Firefox 88+
  • Safari 14+
  • Edge 90+

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

Development Guidelines

  • Follow TypeScript best practices
  • Use semantic commit messages
  • Ensure responsive design
  • Add proper error handling
  • Write clear, self-documenting code

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

  • Wikipedia API for providing comprehensive article data
  • Tailwind CSS for the excellent utility-first framework
  • Lucide React for beautiful, consistent icons
  • The Wikipedia editing community for inspiration

📞 Support

For questions, issues, or contributions:

  • Create an issue on GitHub
  • Contact the development team
  • Check the documentation wiki

Made with ❤️ for the Wikipedia community

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