Search Semantic Scholar for academic papers ranked by vault relevance.
npx skills add https://github.com/tuan3w/obsidian-vault-agent --skill paper-discover
Please help me install this Agent Skill. Skill: paper-discover Source: https://github.com/tuan3w/obsidian-vault-agent/tree/main/skills/paper-discover Command: npx skills add https://github.com/tuan3w/obsidian-vault-agent --skill paper-discover
This Skill helps you discover academic papers relevant to a topic, an existing vault note, or an uncovered research gap—so you stop guessing what to read next.
Run paper discovery for your research question by asking: find papers about scaling laws for LLMs.
High-intent search queries and answers about installing and using this skill.
To find relevant academic papers, this Skill queries Semantic Scholar with your research topic and returns a ranked list of matching literature. It prioritizes results by relevance to your specific query.
Yes, you can find similar papers using a DOI or paper ID. The Skill uses your existing vault note or DOI to generate similar-paper recommendations while checking your vault to avoid redundant duplicates.
To identify research gaps in your knowledge base, this Skill checks your vault for current coverage and surfaces uncovered topics. It then recommends literature to fill those specific missing areas.
Yes, this paper search tool requires Python 3 to run, as it depends on Python scripts to execute Semantic Scholar API queries and process the relevance ranking logic within your vault.
Duplicate paper detection works by checking your existing vault notes before returning search results. It ranks new literature against your current vault knowledge to prevent redundant entries and avoid repeating covered topics.
No, the Skill will not automatically create notes for found papers. It only generates properly formatted paper notes for your vault after you explicitly review and approve the recommended search results.
Clay-HHKConvert DOIs, PMIDs, and arXiv IDs into validated BibTeX entries.
u9401066Generate structured Markdown notes from academic literature and PDFs.
shreed27Generate vector embeddings and perform semantic search against collections.
neflibata-fengSearch Google Scholar and PubMed, extract metadata, and validate BibTeX entries.
