From r/ObsidianMD 📅 • 📊 52 upvotes • ⭐ 9/10 • 🚀 high
*Analysis generated: Dec 14, 2025*
🔗 Source: View on Reddit
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Summary

The user describes an automated academic literature review workflow. It involves daily retrieval of articles from dozens of RSS feeds, an LLM agent (GPT-4o-mini, ~$2/year) that scores abstracts for relevance based on user interests, weekly GitHub Actions to curate a list of top articles into a Markdown file, and local scripts to pull this into Obsidian. In Obsidian, a dedicated workspace helps manage the curated reading list, integrating with Zotero for reading and annotation. This system saves at least an hour a week and provides highly relevant article suggestions.

Key Insights

1. Leveraging LLMs (even small, cheap ones like GPT-4o-mini) for intelligent filtering and scoring of information (e.g., academic abstracts) can significantly reduce manual effort.
2. Combining cloud automation (GitHub Actions) with local scripts and Obsidian creates a powerful, hands-off system for information curation.
3. A dedicated Obsidian workspace with integrated tools (Zotero) and dynamic content (curated reading lists) enhances a specific workflow like academic literature review.
4. Openly sharing complex workflows and code (GitHub repo) benefits the wider community and encourages collaboration.
5. Automation of initial information sifting can save significant time, even if the final reading and annotation is manual.

Enhancement Suggestions

No enhancement suggestions available

Analysis

This post outlines a highly innovative and practical solution for a common academic problem: managing information overload. The combination of RSS feeds, LLMs for intelligent filtering, GitHub Actions for automation, and Obsidian for organization is well-designed and cost-effective. It offers a tangible time-saving benefit and is openly shared for others to adopt.
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*Curated by AI for Paul’s Vault Members*