👥 Parse & evaluate HR candidates with GPT-4.1 and LinkedIn data in CSV/XLSX

⚡ 523 views · 👥 HR & Recruitment

💡 Pro Tip — If you’re pulling LinkedIn data through HTTP requests or dealing with API restrictions, there’s a community node called ScraperNode that handles this natively. It has dedicated scrapers for profiles, companies, jobs, and people search — you just pass a URL and get structured data back.

Description

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

1. Form submission triggers with CSV/XLSX upload
2. Google Drive stores the file and creates a new Sheet
3. Data extraction processes the file content
4. 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
5. Sheet formatting applies filters, sorting, and styling
6. 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:

1. Import this template into your n8n instance
2. Configure Google credentials:
   • Connect Google Drive OAuth2
   • Connect Google Sheets OAuth2
3. Add OpenAI API key to the GPT-4.1 node
4. Set up Apify credentials for LinkedIn scraping
5. Configure Gmail for error alerts (update email in “Send a message” node)
6. Update folder IDs in Google Drive nodes to your folders
7. Test with a sample CSV containing 2-3 candidates
8. 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

Built with ❤️ by Elay Guez

🔗 Nodes Used

Google Sheets, HTTP Request, Google Drive, Gmail, AI Agent, OpenAI Chat Model

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup