deepxiv
DeepXiv enables layered exploration of open-access research papers, letting you search by topic or ID and read specific sections without loading entire documents. It supports trending paper discovery, web search, and integrates with Semantic Scholar metadata for citation context.
DeepXiv lets you search and progressively read academic papers section by section.
AI-generated summary based on this skill's SKILL.md
Install
wanshuiyin/Auto-claude-code-research-in-sleep/deepxiv · repository language: Python
git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep
cp -r Auto-claude-code-research-in-sleep/skills/deepxiv ~/.claude/skills/deepxivFrequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
How do I search arxiv papers on machine learning with DeepXiv?
DeepXiv lets you search arxiv papers by topic—enter your query like 'machine learning' and browse results with metadata and summaries. You can filter by time window to find recent papers, then open specific papers by ID to read progressively without loading the full document at once.
Can I read a specific section of a research paper instead of the full text?
Yes. DeepXiv supports section-level access, so you can retrieve just the introduction, methods, results, or conclusion from a paper. This saves tokens and time by letting you read only the parts you need rather than loading the entire document.
What does DeepXiv's trending papers feature show?
DeepXiv's trending papers discovery lets you find popular open-access research by topic or time window—such as papers trending in the last 2 weeks or this month. Results include metadata and brief summaries so you can quickly assess relevance before diving deeper.
How does DeepXiv retrieve paper metadata and summaries?
DeepXiv pulls paper metadata and brief summaries without requiring full-text loads, often integrating with Semantic Scholar for citation context. This lightweight approach lets you look up arxiv IDs, get abstracts and section listings, and decide which papers to read in detail.
Can DeepXiv search for papers by author name?
Yes. DeepXiv supports author-based searches—you can search for papers by researchers like Karpathy. Combined with topic and time-window filters, this helps you locate specific researchers' work within the open-access literature.
What integrations does DeepXiv offer for literature search?
DeepXiv integrates with Semantic Scholar and arxiv for comprehensive literature discovery. This combination enables web search for AI papers, metadata enrichment, and citation tracking alongside arxiv's native search and trending features.
SKILL.md
rendered from the published skill — quoted content, verbatim
DeepXiv Paper Search & Progressive Reading
Search topic or paper ID: $ARGUMENTS
Role & Positioning
DeepXiv is the progressive-reading literature source:
| Skill | Source | Best for |
|---|---|---|
/arxiv |
arXiv API | Batch search, PDF download, metadata |
/deepxiv |
DeepXiv SDK | Progressive section-level reading |
/semantic-scholar |
S2 API | Published venue metadata, citation counts |
/alphaxiv |
alphaxiv.org | Instant LLM-optimized summary of one paper, with LaTeX source fallback |
Use DeepXiv when you want to avoid loading full papers too early.
Constants
- DEEPXIV_FETCHER — canonical name
deepxiv_fetch.py, resolved pershared-references/integration-contract.md§2 (Policy D1 — primary + fallback cascade). If unresolved (canonical chain exhausted),
(truncated - see the full file via the links below)
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skills/deepxiv/SKILL.md