🚀 Interview Scorecard

A modern lightweight web app to create, run, and export interview questionnaires with scoring, recruiter notes, domain-based evaluation, and CSV recap export.

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✨ Overview

Interview Scorecard helps recruiters, hiring managers, and tech leads structure interviews with a reusable questionnaire system.

It provides:

• a questionnaire editor
• a live interview scoring interface
• a domain-based summary
• a weak point overview
• a CSV export for HR or hiring follow-up

This project is built with plain HTML, CSS, and JavaScript, with no framework and no build step.

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🧩 Features

• 📂 Load questionnaires from JSON files
• 🛠️ Create and edit questionnaires directly in the browser
• 📝 Add recruiter notes during interviews
• ✅ Score each answer with a simple rating system
• 📊 View:
  • total score
  • completion rate
  • global level
  • levels by domain
  • weak points
• 📤 Export interview results to CSV
• 💾 Persist questionnaire state in localStorage
• 👀 Live preview in editor mode
• 🌙 Clean dark UI
• 📱 Responsive layout

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📸 Main Capabilities

Interview mode

Run a questionnaire during a candidate interview and evaluate each answer in real time.

Editor mode

Create or update a questionnaire structure with:

• sections
• questions
• expected answers
• labels
• descriptions

Export

Generate:

• a JSON questionnaire file
• a CSV interview summary ready to share with HR or managers

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🗂️ Project Structure

.
├── index.html     # Main application layout
├── styles.css     # UI styling and responsive layout
└── app.js         # Application logic, editor, scoring, export

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⚙️ Tech Stack

• HTML5
• CSS3
• Vanilla JavaScript

No dependencies. No bundler. No framework. No backend required.

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▶️ Getting Started

Run locally

You can open the project directly in your browser:

open index.html

Or serve it locally with a lightweight HTTP server:

python3 -m http.server 8000

Then open:

http://localhost:8000

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🧪 Questionnaire Format

The app uses a JSON-based questionnaire structure.

Example

{
  "meta": {
    "title": "Linux Systems & DevOps Engineer Interview",
    "subtitle": "Evaluation questionnaire for recruiter or tech lead",
    "maxScorePerQuestion": 2
  },
  "grading": {
    "labels": {
      "2": "Correct",
      "1": "Partial",
      "0": "Incorrect"
    },
    "globalLevels": [
      { "min": 85, "label": "Very strong" },
      { "min": 70, "label": "Good" },
      { "min": 50, "label": "Average / needs improvement" },
      { "min": 0, "label": "Insufficient" }
    ]
  },
  "sections": [
    {
      "id": "section-linux",
      "title": "Linux",
      "description": "Core Linux administration questions",
      "questions": [
        {
          "id": "q-linux-1",
          "label": "Linux fundamentals",
          "text": "Explain the difference between a process and a thread.",
          "expectedAnswer": [
            "A process has its own memory space",
            "Threads share the same process memory",
            "Threads are lighter than processes"
          ]
        }
      ]
    }
  ]
}

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🧠 How It Works

1. Load or create a questionnaire

You can either:

• import an existing JSON questionnaire
• create a new one from the built-in editor

2. Run the interview

For each question, the interviewer can:

• assign a score
• add notes
• review expected answers

3. Review the summary

The app computes:

• total score
• completion ratio
• overall level
• levels by domain
• weak areas

4. Export results

Export a CSV summary including:

• questionnaire metadata
• overall evaluation
• domain breakdown
• question-by-question notes

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💾 Local Persistence

The current questionnaire is automatically saved in the browser using localStorage.

Stored keys:

app.interview.config
app.interview.filename

This allows you to reopen the app and continue working from the latest saved state.

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📤 Exported Data

Questionnaire export

The editor exports the full questionnaire as a formatted JSON file.

Interview export

The interview view exports a CSV file containing:

• questionnaire title and subtitle
• export timestamp
• overall score
• overall level
• per-domain summary
• detailed recap of each question
• recruiter notes

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🎨 UI Highlights

• modern dark theme
• sticky summary sidebar
• clear score visualization
• section-level scoring
• weak point detection
• editor live preview
• responsive layout for smaller screens

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🔍 Current Scope

This project is ideal for:

• technical interviews
• recruiter screening
• hiring scorecards
• structured candidate evaluations
• internal interview templates

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🛣️ Possible Improvements

• candidate profile section
• interviewer name / interview metadata
• autosave indicator
• questionnaire validation
• duplicate section / question actions
• import/export history
• multi-language support
• PDF export
• separate interview session storage
• weighted scoring per section
• authentication and backend persistence

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📄 License

You can release this project under the MIT License if you want to keep it open and reusable.

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🤝 Contributing

Contributions, improvements, and UI enhancements are welcome.

You can contribute by:

• improving the questionnaire editor
• enhancing exports
• adding validation
• refining the user experience
• extending the scoring model