Automates layered DeepXiv paper discovery and progressive reading workflows.
npx skills add https://github.com/jkfee/Auto-Research --skill deepxiv-jkfee
Please help me install this Agent Skill. Skill: deepxiv Source: https://github.com/jkfee/Auto-Research/tree/main/skills/deepxiv Command: npx skills add https://github.com/jkfee/Auto-Research --skill deepxiv-jkfee
Researchers often face information overload when searching for open-access papers and deciding how deeply to read each result; DeepXiv provides a structured, progressive reading workflow to surface relevant papers and progressively reveal content as needed.
Tell DeepXiv to search for a topic, then read a brief summary and the Introduction section of the top result.
High-intent search queries and answers about installing and using this skill.
Progressive reading of open-access papers minimizes data load by using layered views like brief, head, and section reads to surface relevant content only as needed. You start with a search, skim the brief, then drill into specific sections.
Finding trending arxiv papers is handled through web-backed retrieval that surfaces current publications and pulls metadata using optional Semantic Scholar integration. This automates discovery and brings current research directly into your reading workflow.
Automated layered academic-paper discovery applies progressive reading commands to search, skim, and extract specific sections. This structured workflow reveals content sequentially, ensuring you only load the text necessary for quick evaluation.
A Python adapter or the deepxiv CLI is required to execute the literature reading workflow. Optional Semantic Scholar integration is supported to enhance web-backed metadata retrieval during your paper discovery process.
Reading just the Introduction section is fully supported through the section read functionality. This layered approach allows you to evaluate a paper's relevance quickly without loading the entire document into your context.
Progressive reading for open-access literature is limited to papers accessible through supported retrieval channels and Semantic Scholar. It does not bypass paywalls or extract text from sources lacking open-access metadata or compatible web-backed endpoints.
lightrain-aRetrieve and read open-access academic paper sections by query or arXiv ID.
sjtuytcFind and analyze academic papers to create structured literature reviews and summaries.
goupup-aiSearch arXiv and Semantic Scholar papers and read sections without full document loads.
aiyinluyaSearch academic papers across ArXiv, Semantic Scholar, PubMed, and Wikipedia.
