Runtime Revolution Technical Interview Agent

An intelligent multi-technology interview platform designed to facilitate structured technical interviews across Ruby on Rails, Node.js, React, and Python. Features AI-powered insights, comprehensive feedback, and automatic candidate assessment.

🌟 Features

📚 Multi-Technology Support

• Ruby on Rails: 20 questions (6 Junior, 9 Mid, 5 Senior)
• Node.js: 20 questions (3 Junior, 11 Mid, 6 Senior)
• React: 12 questions (2 Junior, 6 Mid, 4 Senior)
• Python: 20 questions (4 Junior, 10 Mid, 6 Senior)
• Questions automatically sorted by difficulty level
• Technology selection on home page

🎯 Advanced Question System

• Sub-Questions Support: Break down complex topics into multiple scorable parts
  • Individual scoring for each sub-question
  • Automatic average calculation for parent question
  • Visual indicators (tree icon 🌳) for questions with sub-questions
• Code Examples: Each question includes relevant code snippets
• Level Badges: Visual indicators for Junior, Mid, and Senior questions
• Dynamic Question Addition: Add new questions during interviews

💬 Interactive Interview Process

• Clean Sidebar Navigation: Question list with status indicators
  • ✓ Green checkmark for answered questions
  • ⚠️ Orange checkmark for "without knowledge" (0%)
  • 🌳 Tree icon for questions with sub-questions
  • Selected question highlighted with green background
• Dual Panel Layout:
  • Left: Question, expected answer, and code examples
  • Right: Scoring, comments, and evaluation tools
• Scoring Options:
  • 0-100% slider for regular questions
  • Individual scoring for sub-questions
  • "Without Knowledge" button (automatically sets 0% with feedback)
• Code Editor Integration:
  • Generate unique shareable links for candidates
  • 20-character hash format: XXXXX-XXXXX-XXXXX-XXXXX
  • Auto-save every 10 seconds
  • Visual auto-save indicators
  • Image support in code editor
• Comments & Feedback: Add detailed notes for each response

📝 Comprehensive General Feedback

• Open-Text Feedback Form covering:
  • Communication skills and soft skills
  • Technical level and experience
  • Autonomy and work style
  • Project experience
  • Learning and growth mindset
  • Leadership skills
  • Client management
  • Strengths and areas for improvement
  • Runtime Revolution fit
  • Hiring decision and recommended level
  • General interview summary
• Required Field Validation: Must provide feedback to finish interview
• AI-Powered Transformation: Converts notes into professional Q&A format
• Regeneration Options:
  • Retry button on failure
  • Regenerate button for new AI interpretations
  • Remove individual Q&A items

🤖 AI-Powered Insights (OpenAI GPT-4)

• General Feedback Analysis: Transforms free-form notes into structured Q&A
• Technical Assessment:
  • Areas for improvement identification
  • Strengths analysis
  • Specific learning resources
• Professional Assessment:
  • Soft skills evaluation
  • Runtime Revolution culture fit
  • Career development path suggestions
  • Overall hiring recommendation
• Configurable: API key stored in environment variables

📊 Intelligent Reporting

• 8-Level Assessment System:
  • Perfect Senior (100%)
  • Solid Senior (≥90%)
  • Beginning Senior (≥75%)
  • Mid Going to Senior (≥60%)
  • Solid Mid-Level (≥80% mid)
  • Beginner Mid-Level (≥60% mid)
  • Junior Going to Mid-Level (≥70% junior)
  • Junior Developer (entry level)
• Flexible Assessment: Based only on answered questions (works with any number)
• Visual Statistics:
  • Average score across all responses
  • Questions answered count
  • Level breakdown (Junior/Mid/Senior performance)
• General Feedback Display:
  • AI-transformed Q&A format
  • Removable items
  • Regeneration capability
• Export Options: Download complete report as text file
• Sub-Questions Breakdown: Detailed view of all sub-question scores

🎨 Modern UI/UX

• Clean OpenAI-Inspired Design:
  • Lots of whitespace
  • Subtle borders
  • Minimal color palette
• Responsive Layout: Works on desktop and tablet
• Material-UI Components: Professional and polished
• Real-Time Updates: Instant feedback on all actions
• Visual Progress Tracking: Progress bar and status indicators

🚀 Getting Started

Prerequisites

• Node.js (v20.18.0 or higher)
• Yarn (v1.22.0 or higher)

Installation

1. Navigate to project directory:

cd interviews-agent

2. Install dependencies:

yarn install

3. Configure OpenAI API (Required for AI features):

# Create .env file
echo "VITE_OPENAI_API_KEY=your_openai_api_key_here" > .env

Important: AI features (general feedback transformation and AI insights) require an OpenAI API key. Get one at https://platform.openai.com/api-keys

4. Start development server:

yarn dev

5. Open browser at http://localhost:5173

📖 Usage Guide

1. Select Technology

• Choose from Ruby on Rails, Node.js, React, or Python
• Each technology has its own curated question set
• Technology-specific assessment criteria

2. Conduct Interview

• Navigate questions using the sidebar
• View question details, expected answers, and code examples
• Score responses with the slider (0-100%)
• For questions with sub-questions:
  • Score each sub-question individually
  • Parent score calculated automatically
• Use "Without Knowledge" for topics candidate doesn't know
• Add comments and feedback for each question
• Generate code editor links for practical exercises:
  • Click "Generate Code Editor Link"
  • Share 20-character hash link with candidate
  • Code auto-saves every 10 seconds
  • Submitted code appears in final report

3. Provide General Feedback

• Click "General Feedback" button in sidebar
• Fill in qualitative observations about:
  • Communication and soft skills
  • Technical abilities and experience
  • Autonomy and work style
  • Leadership and client management
  • Overall fit and hiring recommendation
• At least one field required to finish interview
• Free-form text for maximum flexibility

4. Review Report

The comprehensive report includes:

• Candidate Level Assessment: Automatic 8-level evaluation
• Performance Statistics: Average score, questions answered, level breakdown
• General Interview Feedback:
  • AI-transformed Q&A format
  • Remove unwanted items
  • Regenerate for different interpretations
• AI-Powered Insights: Technical + professional analysis
• Detailed Question Responses: All answers with scores and comments
• Sub-Questions Breakdown: Individual sub-question performance
• Code Submissions: Candidate's code for each exercise
• Export Option: Download complete report

5. Start New Interview

• Click "Start New Interview" to return to home page
• Select same or different technology
• All previous data cleared

🎓 Assessment Criteria

The system evaluates candidates based on:

• Questions Answered: Only answered questions count (flexible system)
• Level Performance:
  • Junior questions (fundamentals)
  • Mid questions (practical application)
  • Senior questions (advanced concepts, architecture)
• Weighted Scoring: Higher weight on matching level questions
• Holistic View: Technical scores + general feedback

8-Level System:

1. Perfect Senior - 100% on all questions
2. Solid Senior - ≥90% senior, ≥85% mid/junior
3. Beginning Senior - ≥75% senior, ≥75% mid/junior
4. Mid Going to Senior - ≥60% senior, ≥70% mid/junior
5. Solid Mid-Level - ≥80% mid, ≥75% junior
6. Beginner Mid-Level - ≥60% mid, ≥70% junior
7. Junior Going to Mid - ≥70% junior, ≥50% mid
8. Junior Developer - Entry level understanding

🛠️ Technology Stack

• Frontend: React 18+ with Vite 7
• UI Framework: Material-UI (MUI) v6
• Styling: Emotion CSS-in-JS
• Icons: Material-UI Icons
• AI: OpenAI GPT-4
• Package Manager: Yarn
• Build Tool: Vite

📁 Project Structure

interviews-agent/
├── src/
│   ├── components/
│   │   ├── HomePage.jsx              # Technology selection
│   │   ├── InterviewPage.jsx         # Main interview UI
│   │   ├── ReportPage.jsx            # Results and assessment
│   │   ├── AddQuestionDialog.jsx     # Dynamic question addition
│   │   ├── GeneralFeedbackDialog.jsx # Feedback collection form
│   │   ├── CodeEditor.jsx            # Shareable code editor
│   │   └── AIInsights.jsx            # OpenAI integration
│   ├── data/
│   │   ├── questions_rails.js        # Ruby on Rails questions
│   │   ├── questions_node.js         # Node.js questions
│   │   ├── questions_react.js        # React questions
│   │   └── questions_python.js       # Python questions
│   ├── App.jsx                       # Main app component
│   ├── main.jsx                      # Entry point
│   └── index.css                     # Global styles
├── .env                              # Environment variables (gitignored)
├── .env.example                      # Environment template
├── package.json
├── vite.config.js
└── README.md

🔧 Customization

Adding Questions

Edit the appropriate question file in src/data/:

{
  id: 21,
  category: "Advanced Topic",
  level: "senior",
  title: "Short Title",
  question: "Your question here?",
  correctAnswer: "Expected answer...",
  codeExample: `// Code example here
const example = 'code';`,
  image: "https://example.com/image.png", // Optional
  hasSubQuestions: true, // Optional
  subQuestions: [ // Optional
    {
      id: 2101,
      question: "Sub-question 1?",
      correctAnswer: "Answer...",
      codeExample: `// Sub-question code`
    }
  ]
}

Modifying Assessment

Edit getCandidateLevel() in src/components/ReportPage.jsx to adjust:

• Level thresholds
• Descriptions
• Required question counts
• Weighted scoring logic

Styling

Modify theme in src/App.jsx:

const theme = createTheme({
  palette: {
    primary: { main: '#10a37f' },
    secondary: { main: '#8661c5' },
    },
  typography: {
    fontFamily: '"Inter", "Segoe UI", sans-serif',
  },
});

📦 Build & Deploy

Production Build

yarn build

Preview Build

yarn preview

Deploy

Deploy the dist/ folder to your hosting service (Vercel, Netlify, etc.)

🔐 Environment Variables

# Required for AI features
VITE_OPENAI_API_KEY=sk-proj-...

# Optional: Add custom configuration
VITE_APP_TITLE=Interview Agent

📝 License

MIT License - Feel free to use for your interview processes

🤝 Contributing

Contributions welcome! Please:

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Submit a pull request

💡 Tips for Interviewers

1. Prepare: Review questions before the interview
2. Adapt: Use "Add Question" to ask follow-ups
3. Document: Use comments field extensively
4. General Feedback: Fill immediately after interview while fresh
5. Code Exercises: Share editor links for practical assessment
6. Review AI Insights: Use as additional perspective, not sole decision
7. Export Reports: Save for future reference and comparison

🐛 Troubleshooting

AI Features Not Working

• Check .env file exists with valid VITE_OPENAI_API_KEY
• Restart dev server after adding .env
• Verify API key at https://platform.openai.com/api-keys

Code Editor Links Not Working

• Ensure localStorage is enabled in browser
• Check that hash format is 20 characters (XXXXX-XXXXX-XXXXX-XXXXX)
• Clear browser cache if issues persist

Auto-Save Not Working

• Check browser console for errors
• Verify localStorage has space available
• Ensure code field is not empty (only saves with content)

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Built for Runtime Revolution Technical Interviews 🚀

For support or questions, contact your development team.