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

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Source Top GitHub Contributors by Language & Location

Detail

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