Retrieve search results, briefs, heads, and sections for arXiv and Semantic Scholar IDs.
npx skills add https://github.com/duypham2801/ThS_LLM --skill deepxiv-duypham2801
Please help me install this Agent Skill. Skill: deepxiv Source: https://github.com/duypham2801/ThS_LLM/tree/main/.claude/skills/deepxiv Command: npx skills add https://github.com/duypham2801/ThS_LLM --skill deepxiv-duypham2801
DeepXiv helps you discover and understand academic literature without downloading and reading full papers all at once, so you can move from uncertainty to targeted section-level insight faster.
Ask DeepXiv to find and summarize a paper by arXiv ID: "Use /deepxiv 2409.05591 - brief".
High-intent search queries and answers about installing and using this skill.
Progressive reading allows efficient academic paper comprehension by retrieving search results, briefs, heads, and specific sections for arXiv and Semantic Scholar IDs. You escalate reading depth only when needed, moving from brief summaries to targeted section-level extraction to control content consumption and save tokens.
Finding trending research papers is done using the trending mode flag. This discovery mode retrieves currently trending papers, allowing you to monitor research trends and perform literature discovery without manually querying or loading full documents.
To extract a specific section, provide the arXiv ID along with the section mode flag. This retrieves targeted section-level insight from the paper, enabling focus on specific parts of the document rather than loading the entire full paper at once.
Yes, Semantic Scholar IDs are supported using the sc mode flag. This retrieves paper briefs and metadata by ID, streamlining literature review workflows and targeted reading where full-paper loading is inefficient.
DeepXiv requires the DeepXiv SDK or CLI availability to function. It applies to literature review and trend monitoring workflows, supporting mode flags like brief, head, section, trending, web, and sc, and prefers an optional adapter fetcher with a fallback cascade.
Layered literature access is limited when full-paper loading is inefficient, focusing on brief, head, and section retrieval rather than complete text. It is not suitable when comprehensive full-text analysis is required, as it prioritizes token-efficient research workflows and progressive comprehension over exhaustive document parsing.
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raja21068Retrieve open-access academic papers by topic or ID with progressive reading depths.
WanLanglinSearch web and academic sources, saving queries and citations to sources/.
aiyinluyaSearch academic papers across ArXiv, Semantic Scholar, PubMed, and Wikipedia.
