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Source Top GitHub Talent by Language & Location with Gemini AI and BrowserAct

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Created by: Madame AI Team | Kai || madame-ai

Madame AI Team | Kai

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Last update 19 days ago

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Source Top GitHub Contributors

AI-Powered Top GitHub Talent Sourcing (by Language & Location) to Google Sheet

This n8n template is a powerful talent sourcing engine that finds, analyzes, and scores GitHub contributors using a custom AI formula.

This workflow is ideal for technical recruiters, hiring managers, and team leads who want to build a pipeline of qualified candidates based on specific technical skills and location.

Self-Hosted Only

This Workflow uses a community contribution and is designed and tested for self-hosted n8n instances only.

How it works

  • The workflow runs on a Schedule Trigger (e.g., hourly) to constantly find new candidates.
  • A BrowserAct node ("Run a workflow task") initiates a scraping job on GitHub based on your criteria (e.g., "Python" developers in "Berlin").
  • A second BrowserAct node ("Get details") waits for the scraping to complete. If the job fails, a Slack alert is sent.
  • A Code node processes the raw scraped data, splitting the list of developers into individual items.
  • An AI Agent, powered by Google Gemini, analyzes each profile. It scores their resume/summary and calculates a final weighted FinalScore based on their followers, repositories, and resume quality.
  • The structured and scored candidate data is then saved to a Google Sheet, using the "Name" column to prevent duplicates.
  • A final Slack message is sent to notify you that the GitHub contributors list has been successfully updated.

Requirements

  • BrowserAct API account for web scraping
  • BrowserAct "Source Top GitHub Contributors by Language & Location" Template
  • BrowserAct n8n Community Node -> (n8n Nodes BrowserAct)
  • Gemini account for the AI Agent
  • Google Sheets credentials for saving leads
  • Slack credentials for sending notifications

Need Help?

Workflow Guidance and Showcase