AI-Powered HR Candidate Evaluation Agent with LinkedIn Data Enrichment in CSV/XLSX Format
๐ฏ Overview
Transform your manual hiring process into an intelligent evaluation system that saves 15-20 minutes per candidate! This workflow automates the entire candidate assessment pipeline - from CSV/XLSX upload to AI-powered scoring with LinkedIn insights.
When you upload a candidate list, this workflow automatically:
- ๐ Converts your file into a formatted Google Sheet with RTL support
- ๐ Researches each candidate's recent LinkedIn posts via Apify
- ๐ค Evaluates candidates using GPT-4.1 with context-aware scoring (0-100)
- ๐ฌ Generates professional Hebrew explanations for each score
- ๐ Auto-sorts by score and applies professional formatting
- โ ๏ธ Sends error alerts to keep everything running smoothly
Cost per candidate: ~$0.05 | Time saved: 15-20 minutes each
๐ฅ Who's it for?
- HR teams drowning in candidate applications
- Recruitment agencies needing consistent evaluation criteria
- Hiring managers seeking data-driven candidate insights
- Companies looking to scale their team
- Anyone tired of manual spreadsheet juggling
โก How it works
- Form submission triggers with CSV/XLSX upload
- Google Drive stores the file and creates a new Sheet
- Data extraction processes the file content
- AI Agent loops through each candidate:
- Fetches up to 3 recent LinkedIn posts via Apify
- Analyzes qualifications against job requirements
- Generates evaluation score and Hebrew explanation
- Sheet formatting applies filters, sorting, and styling
- Error handling notifies admin of any issues
๐ ๏ธ Setup Instructions
Time to deploy: 15 minutes
Requirements:
- Google account (Drive + Sheets access)
- OpenAI API key (GPT-4.1 access)
- Apify API key (for LinkedIn scraping)
- Gmail account (for error notifications)
Step-by-step:
- Import this template into your n8n instance
- Configure Google credentials:
- Connect Google Drive OAuth2
- Connect Google Sheets OAuth2
- Add OpenAI API key to the GPT-4.1 node
- Set up Apify credentials for LinkedIn scraping
- Configure Gmail for error alerts (update email in "Send a message" node)
- Update folder IDs in Google Drive nodes to your folders
- Test with a sample CSV containing 2-3 candidates
- Activate and share the form URL with your team!
๐ Input File Format
Your CSV/XLSX should include these columns (Hebrew):
- ืฉื ืคืจืื (First name)
- ืฉื ืืฉืคืื (Last name)
- ืืฉืืื ืืื ืงืืืื (LinkedIn URL)
- Your custom evaluation questions
๐จ Customization Options
Easy tweaks:
- Scoring criteria : Modify the AI agent's system message
- Language : Switch from Hebrew to any language
- Scoring rubric : Adjust the 50/25/15/10 weighting
- LinkedIn posts : Change from 3 posts to more/fewer
- Sheet styling : Customize colors and formatting
Advanced modifications:
- Add integration with your ATS (Greenhouse, Lever, etc.)
- Connect to Slack for real-time notifications
- Add multiple evaluation agents for different roles
- Implement multi-language support
- Add candidate email automation
๐ก Pro Tips
- Better LinkedIn data : Ensure candidates provide complete LinkedIn URLs (not just usernames)
- Consistent scoring : Run batches of similar roles together for normalized scoring
- Cost optimization : Adjust Apify settings to fetch only essential data
- Scale smartly : Process in batches of min 10-20 for optimal performance
โ ๏ธ Important Notes
- LinkedIn scraping respects Apify's rate limits
- Scores are relative within each batch - don't compare across different job roles
- The workflow handles both CSV and XLSX formats automatically
- Error notifications help you catch issues before they cascade
๐ Expected Results
After implementation, expect:
- Data-driven evaluation across candidates
- Professional explanation for hiring decisions
- Happy recruiters who can focus on human connection
Built with โค๏ธ by Elay Guez