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AI Resume Relevance Scorer

An intelligent n8n workflow that scores resumes against job descriptions using AI, providing detailed reasoning without the keyword bias of traditional ATS systems.

Problem Statement

Traditional ATS (Applicant Tracking Systems) checkers have significant limitations:

  • They rely heavily on specific ATS keywords, which may not reflect actual job fit
  • Resume parsing often fails to maintain context and formatting
  • Scoring explanations are vague or non-existent
  • They don't compare resumes directly against the actual job description

Solution

This n8n workflow solves these problems by:

  • Using AI (Google Gemini) to intelligently compare resumes against job descriptions
  • Providing detailed, transparent scoring with clear reasoning
  • Evaluating based on actual relevance rather than keyword matching
  • Automatically storing results in Google Sheets for easy tracking

Features

  • Automated Processing: Monitors Google Drive folder for new resume uploads
  • AI-Powered Analysis: Uses Google Gemini to evaluate resume-JD fit
  • Comprehensive Scoring:
    • Skills match: 40%
    • Experience relevance: 30%
    • Education fit: 20%
    • Keywords & tools: 10%
  • Detailed Reasoning: Provides clear explanation for each score
  • Data Extraction: Automatically extracts candidate name, email, and mobile
  • Results Tracking: Stores all results in Google Sheets with timestamps
  • PDF Support: Handles PDF resumes and job descriptions

Workflow Architecture

1. Google Drive Trigger → Monitors folder for new resumes
2. File Validation → Checks if uploaded file is PDF
3. Download Resume → Fetches the resume file
4. Download JD → Fetches the job description
5. Extract Text → Converts PDFs to text
6. Merge Data → Combines resume and JD text
7. AI Agent → Analyzes and scores using Google Gemini
8. Parse Results → Extracts structured data
9. Save to Sheet → Stores results in Google Sheets

Setup Instructions

Prerequisites

  1. n8n instance (self-hosted or n8n cloud)
  2. Google Drive account
  3. Google Sheets account
  4. Google Gemini API key

Installation Steps

  1. Import the Workflow

    • Download workflow/Automated Resume Relevance Scoring Workflow (1).json
    • In n8n, go to Workflows → Import from File
    • Select the downloaded JSON file
  2. Configure Google Drive

    • Create a folder in Google Drive for resume uploads (e.g., "AI Resume")
    • Note the folder ID from the URL
    • Upload your job description PDF to Google Drive
    • Note the file ID from the URL
  3. Configure Credentials

  4. Update Workflow Nodes

    • Google Drive Trigger: Update folderToWatch with your folder ID
    • Download JD: Update fileId with your job description file ID
    • Append row in sheet: Update documentId with your Google Sheet ID
  5. Create Results Spreadsheet

    • Create a new Google Sheet
    • Add column headers: candidate_name, mobile, email, relevance_score, reasoning, resume_file, processed_date
    • Note the spreadsheet ID from the URL
  6. Activate the Workflow

    • Click "Active" toggle in n8n
    • The workflow will now monitor for new resumes

Usage

  1. Upload a resume PDF to your designated Google Drive folder
  2. The workflow automatically triggers and processes the resume
  3. Results appear in your Google Sheet within seconds
  4. Review candidate details, scores, and detailed reasoning

Scoring Breakdown

Category Weight Description
Skills Match 40% Alignment of technical and soft skills with JD requirements
Experience Relevance 30% Years and type of experience matching job needs
Education Fit 20% Educational background alignment with requirements
Keywords & Tools 10% Specific tools, technologies, and industry terms

Customization

Modify Scoring Criteria

Edit the prompt in the "AI Agent" node to adjust scoring weights or add new criteria.

Change AI Model

Replace "Google Gemini Chat Model" with other supported models (OpenAI, Anthropic, etc.)

Add Notifications

Add nodes after "Append row in sheet" to send email/Slack notifications

Example Output

Candidate Name: John Doe
Mobile: +1-234-567-8900
Email: john.doe@email.com
Relevance Score: 87/100

Reasoning:
- Strong skills match (35/40): Proficient in Python, SQL, and AWS
- Excellent experience (28/30): 5+ years in data engineering roles
- Education aligned (18/20): Master's in Computer Science
- Good keyword presence (6/10): Missing some specific tools mentioned in JD

Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

License

This project is open source and available under the MIT License.

Acknowledgments

Contact

For questions or suggestions, please open an issue on GitHub.


Note: Make sure to keep your API keys and credentials secure. Never commit them to version control.

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AI-powered resume scoring workflow that compares resumes against job descriptions without ATS keyword bias

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