An AI-powered web application that instantly analyzes your resume and gives you an ATS (Applicant Tracking System) compatibility score — helping you land more interviews.
Many companies use Applicant Tracking Systems (ATS) to automatically filter resumes before a human ever reads them. If your resume is not optimized, it gets rejected — even if you are highly qualified.
ATS Resume Score Checker solves this by:
- Parsing your uploaded resume
- Comparing it against the job description you provide
- Generating an ATS score with detailed feedback
- Highlighting missing keywords and formatting issues
| Feature | Description |
|---|---|
| 📄 Resume Upload | Supports PDF, DOCX, and TXT formats |
| 🔍 ATS Score | Calculates compatibility score (0–100%) |
| 🧠 Keyword Analysis | Identifies missing and matched keywords |
| 📊 Section Detection | Checks for key resume sections (Skills, Education, Experience) |
| 💡 Smart Suggestions | Provides actionable tips to improve your resume |
| ⚡ Fast & Free | No login required, instant results |
Upload your resume → Paste the job description → Get your ATS Score instantly!
ATS Score: 78/100
✅ Matched Keywords: Python, Machine Learning, REST API, Git
❌ Missing Keywords: Docker, Kubernetes, CI/CD
⚠️ Suggestions: Add a Summary section, use bullet points in Experience
- Frontend: HTML5 / CSS3 / JavaScript (React or Vanilla — update as per your stack)
- Backend: Python (Flask / FastAPI / Streamlit)
- NLP / AI: Keyword extraction, cosine similarity scoring, NLP-based parsing
- File Parsing: PyMuPDF / pdfplumber / python-docx
- Deployment: Streamlit Cloud / Render / Vercel / Railway
RESUME-BUILDING-APPLICATION/
├── app.py # Main application entry point
├── scorer/
│ ├── ats_scorer.py # Core ATS scoring logic
│ ├── parser.py # Resume and JD parser
│ └── keywords.py # Keyword extraction module
├── frontend/
│ ├── index.html # Main UI
│ ├── style.css # Styling
│ └── script.js # Frontend logic
├── uploads/ # Temporary resume storage
├── requirements.txt # Python dependencies
└── README.md # Project documentation
Update this structure to match your actual project layout.
- Python 3.8+
- pip
- Git
# 1. Clone the repository
git clone https://github.com/DHANUSHGCODE/RESUME-BUILDING-APPLICATION.git
cd RESUME-BUILDING-APPLICATION
# 2. Create a virtual environment (recommended)
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# 3. Install dependencies
pip install -r requirements.txt
# 4. Run the application
python app.py
# or for Streamlit:
streamlit run app.pyOpen your browser and visit: http://localhost:5000 (or the Streamlit URL shown in terminal)
Add screenshots of your application UI here.
| Upload Screen | ATS Score Result |
|---|---|
| (screenshot) | (screenshot) |
- Resume upload and parsing (PDF, DOCX, TXT)
- ATS keyword matching and scoring
- Section detection and formatting checks
- AI-powered resume rewriting suggestions
- LinkedIn profile score analysis
- Multi-language resume support
- Downloadable PDF score report
- Job board integration (LinkedIn, Naukri, Indeed)
Contributions are welcome! Here's how to get started:
- Fork this repository
- Create a new feature branch:
git checkout -b feature/your-feature-name - Commit your changes:
git commit -m 'Add: your feature description' - Push to the branch:
git push origin feature/your-feature-name - Open a Pull Request
Please follow clean code practices and add comments where necessary.
This project is licensed under the MIT License — see the LICENSE file for details.
Dhanush G
B.Tech Computer Science Engineering | Full Stack & AI/ML Enthusiast
📍 Bangalore, India
⭐ If you found this project helpful, please give it a star — it means a lot!