Fetch LLM-optimized summaries of arXiv papers with LaTeX source fallback.
npx skills add https://github.com/TabithaFanny/ThesisX --skill alphaxiv-tabithafanny
Please help me install this Agent Skill. Skill: alphaxiv Source: https://github.com/TabithaFanny/ThesisX/tree/main/skills_imported/aris/skills/alphaxiv Command: npx skills add https://github.com/TabithaFanny/ThesisX --skill alphaxiv-tabithafanny
This Skill provides instant access to summaries and LaTeX source code of papers published on arXiv, simplifying paper retrieval and deep access.
To access the summary of a paper with arXiv ID 12345, use: /alphaxiv 12345
High-intent search queries and answers about installing and using this skill.
You can retrieve an LLM-optimized arXiv paper summary by providing the specific paper ID. This instantly presents the document's core research findings and abstract details without needing to read the full text.
Yes, this tool provides direct access to the LaTeX source of arXiv documents as a fallback for deeper content retrieval. This allows you to extract detailed equations, appendices, and specific formatting that standard summaries omit.
This arXiv summary tool requires the Python requests library to handle HTTP requests. It also requires an environment that supports markdown rendering to properly display the fetched paper summaries and LaTeX content.
The best way to look up arXiv research papers for academic discussion is to query the document by its arXiv ID. This fetches an optimized summary alongside LaTeX source access for detailed reference.
Automated summaries for arXiv documents may omit complex equations or detailed appendices. When this occurs, the tool falls back to providing the raw LaTeX source, ensuring you still access the deeply technical content required.
Mang30Retrieve LLM-optimized paper explanations from AlphaXiv with tiered fallback.
mvillmowExtract LaTeX equations from research papers and map components to code.
dogekikiFetch tiered summaries of academic papers from AlphaXiv and arXiv.
google-deepmindSearch arXiv with structured queries and retrieve paper metadata and full text.
