AI-Powered HR Candidate Evaluation Agent with LinkedIn Data Enrichment in CSV/XLSX Format
🎯 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:
- 📊 Converts your file into a formatted Google Sheet with RTL support
 
- 🔍 Researches each candidate's recent LinkedIn posts via Apify
 
- 🤖 Evaluates candidates using GPT-4.1 with context-aware scoring (0-100)
 
- 💬 Generates professional Hebrew explanations for each score
 
- 📈 Auto-sorts by score and applies professional formatting
 
- ⚠️ Sends error alerts to keep everything running smoothly
 
Cost per candidate: ~$0.05 | Time saved: 15-20 minutes each
👥 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
 
⚡ 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
 
🛠️ 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!
 
📋 Input File Format
Your CSV/XLSX should include these columns (Hebrew):
- שם פרטי (First name)
 
- שם משפחה (Last name)
 
- חשבון לינקדאין (LinkedIn URL)
 
- Your custom evaluation questions
 
🎨 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
 
💡 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
 
⚠️ 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
 
📊 Expected Results
After implementation, expect:
- Data-driven evaluation across candidates
 
- Professional explanation for hiring decisions
 
- Happy recruiters who can focus on human connection