Summarize individual arXiv papers using tiered AlphaXiv and LaTeX sources.
npx skills add https://github.com/goupup-ai/miccai25 --skill alphaxiv-goupup-ai
Please help me install this Agent Skill. Skill: alphaxiv Source: https://github.com/goupup-ai/miccai25/tree/main/ARIS/skills/alphaxiv Command: npx skills add https://github.com/goupup-ai/miccai25 --skill alphaxiv-goupup-ai
Manually reading full arXiv papers to extract key takeaways is time-consuming, especially when you only need a quick understanding of a single paper's core contributions and findings.
Use the alphaxiv skill to get a quick LLM-optimized summary of the arXiv paper with ID 2401.12345.
High-intent search queries and answers about installing and using this skill.
To summarize arXiv papers without reading the full text, provide the paper ID or URL to retrieve an LLM-optimized overview of its core contributions, methodology, and experimental results. This eliminates time-consuming manual PDF processing.
Extracting core findings using an arXiv ID utilizes a tiered source fallback system fetching AlphaXiv overviews, full markdown, and LaTeX source. This matches detail levels to query specificity and provides a 2-3 sentence summary of contributions in seconds.
Yes, flexible input handling accepts bare arXiv IDs, arXiv URLs, AlphaXiv links, and versioned paper links. The system automatically extracts the correct paper identifier to fetch your research summary without requiring manual formatting.
The tool implements a tiered source fallback system that can process both full paper markdown and LaTeX source. It starts with a fast AlphaXiv overview and only escalates to markdown or LaTeX source if deeper details are needed.
You should not use automated summaries when your literature review requires exhaustive manual verification of nuanced mathematical proofs or exhaustive experimental data sets. The tiered fallback system provides markdown and LaTeX source, but rapid comprehension of single papers is its primary focus.
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