AI-Powered Resume & GitHub Analysis for Smart Hiring
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This workflow automates the entire candidate intake and assessment process, from receiving resumes via Gmail to generating a comprehensive profile. It leverages AI for resume parsing and deep GitHub analysis to provide rich, structured candidate data, streamlining your hiring pipeline.
About This Workflow
This n8n workflow is a powerful solution for modern talent acquisition teams, transforming manual resume screening into an automated, intelligent process. It begins by monitoring your Gmail inbox for new resume submissions, then uses AI to meticulously parse each document, extracting crucial candidate details like contact information, skills, and work history via VLM Run. Subsequently, it performs an in-depth analysis of the candidate's GitHub profile, if available, identifying programming languages, frameworks, and activity patterns. The collected data is then systematically organized, saved to Google Sheets for easy management, broadcasted to your team via Slack for real-time awareness, and a professional acknowledgment email is sent to the candidate, ensuring a seamless experience for all involved.
Key Features
- Automated Resume Intake: Monitors your Gmail inbox every minute for new emails containing attachments, automatically triggering the processing workflow and downloading resume files (PDF/DOCX).
- AI Resume Parsing (VLM Run): Leverages advanced AI to extract structured candidate data, including contact information, skills, work history, education, and social profiles, eliminating manual data entry.
- Deep GitHub Profile Analysis: Intelligently analyzes candidates' GitHub profiles for account age, follower metrics, repository activity, language distribution, framework detection, and trending skills.
- Multi-Channel Data Output: Centralizes candidate data by saving detailed profiles to Google Sheets, sends instant, rich notifications to your team via Slack, and automates personalized acknowledgment emails.
- Intelligent Data Handling: Smartly handles scenarios where GitHub profiles are missing and automatically calculates experience, ranks technologies, and identifies key skills.
How To Use
- Configure Gmail Trigger: Connect your Gmail account to the "Monitor Gmail for Resumes" node. Ensure the
options.downloadAttachmentsparameter is set totrueto enable resume file processing. - Set up VLM Run: Provide your VLM Run API credentials to the "Parse Resume with VLM Run" node. Verify that the
fileparameter correctly references the incoming attachment (e.g.,attachment_0). - Integrate GitHub Logic (If Applicable): The "Check for Github Profile" node uses an
Ifcondition to check for a GitHub URL. Ensure theExtract GitHub Usernamecode node is correctly configured to parse the username from the URL for subsequent GitHub API calls (additional GitHub nodes for full analysis are implied but not fully shown). - Connect Output Channels: Configure your Google Sheets node to append the extracted candidate data to your desired spreadsheet. Set up your Slack node with a webhook to send real-time notifications to your team, customizing the message content as needed.
- Personalize Acknowledgment: In the "Send Acknowledgement Email" node, update the
senderName,subject, andmessageto align with your brand's communication style. Ensure thesendToparameter dynamically pulls the candidate's email address from the parsed resume data. - Activate Workflow: Once all credentials are securely added and configurations are complete, activate the workflow to begin automated, intelligent resume processing and candidate profiling.
Apps Used
Workflow JSON
{
"id": "33a86b6e-d7f5-4642-8db4-812dabf46733",
"name": "AI-Powered Resume & GitHub Analysis for Smart Hiring",
"nodes": 11,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 33a86b6e-d7f5...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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