ATS Resume Analyzer

Industry-grade ATS (Applicant Tracking System) resume analyzer powered by Claude AI. Upload a resume (PDF, DOCX, or TXT), optionally paste a job description, and get an instant detailed compatibility report — the same way modern Fortune 500 recruiting systems evaluate candidates.

• ATS score (0–100) with honest category breakdown
• Keyword analysis — matched vs. missing vs. recommended additions
• Action verb audit — strong vs. weak verbs with suggestions
• Quantification check — finds metrics, flags bullets without numbers
• Formatted recommendations — prioritized, actionable, with examples
• Seniority & interview likelihood estimates
• Red flags detection — gaps, short stints, missing contact info
• Supports PDF (text-based), DOCX, and TXT

Sign up at console.anthropic.com and create an API key.

git add .
git commit -m "ATS Resume Analyzer"
git push

1. Go to vercel.com/new
2. Import your GitHub repository
3. In Environment Variables, add:
   • ANTHROPIC_API_KEY = your key from step 1
4. Click Deploy

Vercel auto-detects public/index.html (frontend) and api/analyze.py (serverless function).

# Install dependencies
pip install -r requirements.txt

# Create .env file
cp .env.example .env
# Edit .env and add your ANTHROPIC_API_KEY

# Run the server
python api/analyze.py
# Visit http://localhost:5000

.
├── public/
│   └── index.html          # Frontend (served at /)
├── api/
│   └── analyze.py          # Flask serverless function (/api/analyze)
├── analyzers/              # Legacy local modules (not used by web app)
├── utils/                  # Legacy local modules
├── requirements.txt
├── vercel.json
└── .env.example

• Frontend: Vanilla HTML/CSS/JS (no dependencies, instant load)
• Backend: Flask on Vercel Python serverless runtime
• AI Engine: Claude claude-sonnet-4-6 via Anthropic API
• PDF Parsing: pdfplumber
• DOCX Parsing: python-docx