Ai Resume Processing And Github Analysis With Vlm Run 5306 – n8n Workflows – Free Template

What This Workflow Does

This workflow automates the analysis of job candidates by processing resumes from Gmail and performing deep intelligence gathering on their GitHub profiles. It combines resume data extraction with comprehensive GitHub repository analysis to create a complete candidate assessment.

• Automatically extracts and processes resume documents from Gmail attachments
• Analyzes GitHub profile metrics including account age, followers, and activity
• Detects technology stacks across 30+ programming frameworks
• Evaluates repository quality through stars, forks, and recent contributions
• Organizes findings in Google Sheets for easy review
• Sends summarized insights to Slack for team collaboration

How It Works

The workflow begins when an email with a resume attachment arrives in Gmail. A trigger initiates the automated process which then follows these steps:

• Gmail trigger detects incoming emails with resume attachments
• VLM Run processes the resume document using computer vision to extract candidate information
• The extracted data determines if GitHub analysis should proceed
• HTTP requests fetch GitHub profile data and repository information from the GitHub API
• Code nodes process and analyze the technology stack and contribution patterns
• Results are merged and stored in a Google Sheet for centralized tracking
• Slack notification sends a summary to your recruitment team for immediate review

Use Cases

• Technical Recruiting: Automatically assess engineering candidates by analyzing their real-world coding experience and project contributions stored on GitHub
• Developer Onboarding: Create technology skill profiles for new hires to guide training and project assignments based on their expertise
• Open Source Contribution Tracking: Identify candidates who actively contribute to open source projects and evaluate the quality of their contributions
• Team Skill Mapping: Build a comprehensive database of team member skills and expertise to identify knowledge gaps and training opportunities
• Competitive Analysis: Analyze competitor team compositions by researching publicly available GitHub profiles to understand technology choices

Nodes Used

• Gmail Trigger: Monitors incoming emails and detects resume attachments
• Gmail: Retrieves and downloads resume documents from email messages
• VLM Run: Uses vision language models to extract text and data from resume images or documents
• If: Conditionally routes the workflow based on extracted resume data
• Code: Processes GitHub data and analyzes technology patterns using JavaScript
• HTTP Request: Queries the GitHub API for profile and repository information
• Merge: Combines resume data with GitHub analysis results
• Google Sheets: Stores candidate profiles and analysis results in a spreadsheet
• Slack: Sends notifications with candidate summaries to your team channel
• Sticky Note: Provides workflow documentation and instructions

Prerequisites

• Active Gmail account with resume inbox access
• GitHub API personal access token for profile and repository data retrieval
• Google Sheets document created for storing candidate analysis results
• Slack workspace with API credentials and designated channel for notifications
• VLM Run integration configured in your n8n instance
• Candidates should have public GitHub profiles for analysis

Difficulty Level

Intermediate to Advanced. This workflow requires configuration of multiple external services including Gmail, GitHub API, Google Sheets, and Slack. Understanding of API authentication, conditional logic, and data transformation is recommended. The VLM Run node adds complexity but provides powerful document analysis capabilities.

This workflow template is shared under the n8n fair-code license. Free to use and modify.