Search and incrementally retrieve academic paper content with staged output.
npx skills add https://github.com/Shallow-W/llm-wiki --skill deepxiv-shallow-w
Please help me install this Agent Skill. Skill: deepxiv Source: https://github.com/Shallow-W/llm-wiki/tree/main/.claude/skills/deepxiv Command: npx skills add https://github.com/Shallow-W/llm-wiki --skill deepxiv-shallow-w
It helps you find relevant academic papers and read only the right amount at the right time, reducing token waste and time spent downloading or scanning full papers.
Use the deepxiv skill to fetch a brief summary for an arXiv paper by asking: deepxiv 2409.05591 - brief.
High-intent search queries and answers about installing and using this skill.
You can read arXiv papers progressively by searching and retrieving content in stages: search, brief, head, and single section. This layered approach matches reading depth to your specific question, reducing token waste and time spent downloading full papers.
Discover trending academic papers by using the trending research retrieval mode. It allows you to configure a specific time window to find popular research, providing JSON-formatted fallbacks to ensure you get metadata even if primary sources are unavailable.
Yes, you can retrieve academic paper metadata by performing a Semantic Scholar integration using a specific paper ID. This enriches your search results with detailed metadata when available, helping you evaluate papers before reading.
Yes, DeepXiv supports optional wiki ingestion. If a research-wiki directory is present, it can ingest meaningfully read papers (brief, head, section, or full) to keep your research notes updated automatically.
You can search arXiv by topic or specific paper ID to get a brief summary by requesting the brief output stage. For example, querying an arXiv ID directly fetches a concise summary, matching your reading depth to the immediate requirement.
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