Resume Parser & Skill Extractor

Parse PDF resumes to extract contact info, technical skills, experience years, and education. Optional job description matching score for candidate screening. Perfect for HR teams and recruiting platforms.

Features

• Contact Information Extraction: Automatically detects candidate name, email, and phone number from resume text
• Technical Skills Detection: Identifies 80+ tech keywords across 9 categories (languages, frontend, backend, database, cloud, devops, mobile, AI/ML, tools)
• Experience Estimation: Estimates years of professional experience from date patterns in resume
• Education Extraction: Detects Bachelor's, Master's, PhD, and Associate degrees with fields of study
• Job Description Matching: Optional skill match scoring against provided job description (0-100%)
• PDF Metadata: Extracts page count and word count for resume assessment
• Comprehensive Disclaimer: Includes GDPR/CCPA compliance notice for responsible use

Extracted Fields

Field	Type	Description
resumeUrl	string	Input PDF URL
candidateName	string	Extracted candidate full name
email	string	Email address (normalized to lowercase)
phone	string	Phone number in original format
skills	object	Skills grouped by category (languages, frontend, backend, etc.)
allSkillsList	array	Flat list of all detected skills
skillCount	integer	Total number of unique skills found
estimatedExperienceYears	integer	Years since first detected work date
education	array	Array of degrees with level and field
pageCount	integer	Number of pages in PDF
wordCount	integer	Total words in resume text
jobFitScore	integer	Match percentage (0-100%) if job description provided
jobFitScoreNote	string	Explanation of job fit calculation
disclaimer	string	Legal/compliance disclaimer text

Input

{
  "resumeUrl": "https://example.com/resume.pdf",
  "jobDescription": "We're looking for a React developer with 5+ years experience..."
}

Parameter	Type	Required	Description
resumeUrl	string	YES	Direct URL to PDF resume file
jobDescription	string	NO	Job description text for skill matching (0-100% score calculated if provided)

Output

Actor pushes one item per resume to the default dataset with all extracted fields.

Example Output:

{
  "resumeUrl": "https://example.com/resume.pdf",
  "candidateName": "John Smith",
  "email": "john@example.com",
  "phone": "+1 555-123-4567",
  "skills": {
    "languages": ["javascript", "typescript", "python"],
    "frontend": ["react", "nextjs"],
    "backend": ["nodejs", "express"],
    "database": ["postgresql"]
  },
  "allSkillsList": ["javascript", "typescript", "python", "react", "nextjs", "nodejs", "express", "postgresql"],
  "skillCount": 8,
  "estimatedExperienceYears": 6,
  "education": [
    { "level": "Bachelor", "field": "Computer Science" }
  ],
  "pageCount": 2,
  "wordCount": 847,
  "jobFitScore": 75,
  "jobFitScoreNote": "75% of JD tech keywords found in resume",
  "disclaimer": "..."
}

Pricing

$0.10 per resume parsed (Pay-per-event model)

Billing event: resume-parsed

Usage Example

curl -X POST https://api.apify.com/v2/acts/{actor-id}/runs \
  -H "Authorization: Bearer {api-token}" \
  -H "Content-Type: application/json" \
  -d '{
    "resumeUrl": "https://example.com/resume.pdf",
    "jobDescription": "Senior Full Stack Engineer with 7+ years experience in React and Node.js"
  }'

Supported Skill Categories

• Languages: JavaScript, TypeScript, Python, Java, C++, C#, Go, Rust, Ruby, PHP, Swift, Kotlin, Scala, R, MATLAB, Perl, Haskell, Elixir, Dart, Lua
• Frontend: React, Vue, Angular, Svelte, Next.js, Nuxt.js, HTML, CSS, Sass, Tailwind, Bootstrap, Webpack, Vite, Redux, Mobx, GraphQL
• Backend: Node.js, Express, FastAPI, Django, Flask, Spring, Rails, Laravel, ASP.NET, Nest.js, Hapi, Koa, Gin, Echo, Fiber
• Database: PostgreSQL, MySQL, MongoDB, Redis, Elasticsearch, SQLite, Oracle, MSSQL, DynamoDB, Cassandra, Neo4j, Firebase, Supabase
• Cloud: AWS, Azure, GCP, Google Cloud, Heroku, Vercel, Netlify, Cloudflare, DigitalOcean, Linode
• DevOps: Docker, Kubernetes, Terraform, Ansible, Jenkins, GitHub Actions, GitLab CI, CircleCI, Helm, Prometheus, Grafana
• Mobile: React Native, Flutter, Swift, Kotlin, iOS, Android, Expo
• AI/ML: PyTorch, TensorFlow, Scikit-learn, Keras, Pandas, NumPy, OpenCV, Hugging Face, LangChain, OpenAI, LLM, Machine Learning, Deep Learning, NLP, Computer Vision
• Tools: Git, Jira, Confluence, Slack, Figma, Postman, Swagger, Linux, Bash, Vim

Limitations

• Scanned/Image PDFs: Not supported. Actor requires machine-readable text-based PDFs. Scanned resumes will return minimal results.
• Encrypted PDFs: Password-protected PDFs cannot be parsed.
• Non-English Resumes: Skill detection optimized for English keywords. Other languages have limited accuracy.
• Uncommon Formats: Highly non-standard resume layouts may have extraction accuracy issues.
• Manual Review Required: Results should always be reviewed by human recruiters. Automated parsing is not error-proof.

Disclaimer

IMPORTANT LEGAL & COMPLIANCE NOTICE

This tool extracts information from PDF resume files using open source text parsing libraries. Extraction accuracy depends on the PDF structure, formatting, and encoding. Scanned or image-based PDFs will have very limited accuracy. Results may miss information or contain errors. This tool is intended to assist human reviewers, not replace them. Do not make final hiring decisions based solely on automated parsing results.

Data Protection & Privacy Compliance: The operator is not responsible for hiring outcomes, data accuracy, or privacy compliance. Ensure all resume processing complies with applicable employment laws and data protection regulations:

• GDPR (EU): Obtain explicit consent before processing personal data
• CCPA (California): Provide privacy notices and honor data access/deletion requests
• ADA (USA): Ensure fair assessment of candidates with disabilities
• Other jurisdictions: Verify local employment and data protection laws

Responsible Use:

• Obtain candidate consent before parsing their resume
• Use results only to supplement human review, not replace it
• Maintain secure storage of extracted personal data
• Implement data retention and deletion policies
• Do not use for discriminatory screening

License

This actor uses pdf-parse (MIT License) for PDF parsing.