skills/deepxiv/SKILL.md
Search and progressively read open-access academic papers through DeepXiv. Use when the user wants layered paper access, section-level reading, trending papers, or DeepXiv-backed literature retrieval.
npx skillsauth add shaun-z/auto-claude-code-research-in-sleep deepxivInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Search topic or paper ID: $ARGUMENTS
DeepXiv is the progressive-reading literature source:
| Skill | Best for |
|------|----------|
| /arxiv | Direct preprint search and PDF download |
| /semantic-scholar | Published venue metadata, citation counts, DOI links |
| /deepxiv | Layered reading: search → brief → head → section, plus trending and web search |
Use DeepXiv when you want to avoid loading full papers too early.
tools/deepxiv_fetch.py relative to the current project. If unavailable, fall back to the raw deepxiv CLI.Overrides (append to arguments):
/deepxiv "agent memory" - max: 5— top 5 results/deepxiv "2409.05591" - brief— quick paper summary/deepxiv "2409.05591" - head— metadata + section overview/deepxiv "2409.05591" - section: Introduction— read one section only/deepxiv "trending" - days: 14 - max: 10— trending papers/deepxiv "karpathy" - web— DeepXiv web search/deepxiv "258001" - sc— Semantic Scholar metadata by ID
DeepXiv is optional. If the CLI is not installed, tell the user:
pip install deepxiv-sdk
On first use, deepxiv auto-registers a free token and stores it in ~/.env.
Parse $ARGUMENTS for:
- max: N: override MAX_RESULTS- brief: fetch paper brief- head: fetch metadata and section map- section: NAME: fetch one named section- trending or query trending: fetch trending papers- days: 7|14|30: trending time window- web: run DeepXiv web search- sc: fetch Semantic Scholar metadata by IDIf the main argument looks like an arXiv ID and no explicit mode is given, default to - brief.
Prefer the ARIS adapter:
python3 tools/deepxiv_fetch.py --help
If tools/deepxiv_fetch.py is not available, fall back to raw deepxiv commands.
Search papers
python3 tools/deepxiv_fetch.py search "QUERY" --max MAX_RESULTS
Fallback:
deepxiv search "QUERY" --limit MAX_RESULTS --format json
Brief summary
python3 tools/deepxiv_fetch.py paper-brief ARXIV_ID
Fallback:
deepxiv paper ARXIV_ID --brief --format json
Section map
python3 tools/deepxiv_fetch.py paper-head ARXIV_ID
Fallback:
deepxiv paper ARXIV_ID --head --format json
Specific section
python3 tools/deepxiv_fetch.py paper-section ARXIV_ID "SECTION_NAME"
Fallback:
deepxiv paper ARXIV_ID --section "SECTION_NAME" --format json
Trending
python3 tools/deepxiv_fetch.py trending --days 7 --max MAX_RESULTS
Fallback:
deepxiv trending --days 7 --limit MAX_RESULTS --output json
Web search
python3 tools/deepxiv_fetch.py wsearch "QUERY"
Fallback:
deepxiv wsearch "QUERY" --output json
Semantic Scholar metadata
python3 tools/deepxiv_fetch.py sc "SEMANTIC_SCHOLAR_ID"
Fallback:
deepxiv sc "SEMANTIC_SCHOLAR_ID" --output json
When searching, present a compact table:
| # | ID | Title | Year | Citations | Notes |
|---|----|-------|------|-----------|-------|
When reading a paper, show:
brief → head → sectionUse this progression:
searchpaper-briefpaper-headpaper-sectionDo not jump to full-paper reads when a brief or one section answers the question.
Required when research-wiki/ exists in the project; skip silently
otherwise. Ingest papers that were meaningfully read (brief / head /
section / full) during this invocation — mere search hits without a
depth read do not need ingestion:
if [ -d research-wiki/ ]:
for each arxiv_id the user asked this skill to read in depth:
python3 tools/research_wiki.py ingest_paper research-wiki/ \
--arxiv-id "<arxiv_id>"
The helper handles metadata / slug / dedup / page / index / log in one
call — do not handwrite papers/<slug>.md. See
shared-references/integration-contract.md.
Backfill missed ingests with
python3 tools/research_wiki.py sync research-wiki/ --arxiv-ids <id1>,<id2>,....
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