Automatic research, summarization, and distribution (n8n + LLM + GitHub)
An automated workflow has been implemented for monitoring trending GitHub repositories and generating structured digests.
The system includes:
• Daily execution on schedule (Schedule Trigger)
• Analysis of push activity for 24h / 30d
• Filtering of already processed repositories
• Retrieval of README and metadata via GitHub API
• AI summarization and description generation (LLM)
• Automatic translation into English
• Formatting Markdown → HTML
• Automatic email distribution
• Creation of files in GitHub
The workflow operates as an autonomous trend selection system: from raw data collection to a ready AI digest with multilingual support.
The system includes:
• Daily execution on schedule (Schedule Trigger)
• Analysis of push activity for 24h / 30d
• Filtering of already processed repositories
• Retrieval of README and metadata via GitHub API
• AI summarization and description generation (LLM)
• Automatic translation into English
• Formatting Markdown → HTML
• Automatic email distribution
• Creation of files in GitHub
The workflow operates as an autonomous trend selection system: from raw data collection to a ready AI digest with multilingual support.