
DeepXiv Paper Search
FreeProgressively read and search open-access academic papers.
Free · Opens the source repo
What DeepXiv Paper Search does
DeepXiv is a skill designed for users who need a more efficient way to navigate and read academic literature. This tool allows you to search for papers by topic or ID and progressively read through them without the need to download full documents upfront. By leveraging the DeepXiv SDK, users can access specific sections of papers, get brief summaries, or view trending research topics over a selected timeframe. This feature is particularly useful for researchers, students, and professionals who want to quickly assess the relevance of papers before committing to a full read.
The workflow of DeepXiv is structured to facilitate a step-by-step exploration of academic papers. Users can start with a general search, then drill down to brief summaries or specific sections of interest. This progressive reading approach helps in managing the overwhelming amount of information available in academic literature. The tool is designed to present results in a clear format, making it easy to identify key details such as citations and publication years, which are essential for effective literature review.
DeepXiv is particularly beneficial when you want to stay updated with the latest trends in your field or when you are conducting a literature review. The ability to filter results based on trending topics and specific sections allows for a more targeted approach to research. Additionally, the integration with Semantic Scholar provides users with enhanced metadata, enriching the research experience further.
Overall, DeepXiv is a valuable resource for anyone engaged in academic research who wants to streamline their reading process and improve their literature retrieval capabilities.
When to use it
Use DeepXiv when you need to quickly assess multiple academic papers and prefer to read specific sections rather than full documents.
When not to use it
This tool may not be suitable if you require comprehensive analysis or full-text access to papers right away, as it focuses on progressive reading.
What you can build with it
Quick Literature Review
Use DeepXiv to quickly search for papers on a specific topic and read brief summaries to gauge relevance.
Accessing Trending Research
Stay updated with the latest trends by fetching trending papers in your field over the last two weeks.
Section-Specific Reading
If you only need information from a specific part of a paper, use DeepXiv to read just that section without downloading the entire document.
How to install DeepXiv Paper Search
View source1. Install with the skills CLI
npx skills add wanshuiyin/auto-claude-code-research-in-sleep/deepxiv --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by wanshuiyinDeepXiv 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), fall back to the rawdeepxivCLI (documented per command below). - MAX_RESULTS = 10 — Default number of results to return.
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
Setup
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.
Workflow
Step 1: Parse Arguments
Parse $ARGUMENTS for:
- Query or ID: a paper topic, arXiv ID, or Semantic Scholar ID
- max: N: overrideMAX_RESULTS- brief: fetch paper brief- head: fetch metadata and section map- section: NAME: fetch one named section- trendingor querytrending: fetch trending papers- days: 7|14|30: trending time window- web: run DeepXiv web search- sc: fetch Semantic Scholar metadata by ID
If the main argument looks like an arXiv ID and no explicit mode is given, default to - brief.
Step 2: Locate the Adapter
Resolve $DEEPXIV_FETCHER via the canonical strict-safe chain (see
shared-references/integration-contract.md §2).
Policy D1 cascade: the resolved adapter is preferred; if unresolved
(canonical chain exhausted), fall back to raw deepxiv CLI commands
documented in Step 3.
cd "$(git rev-parse --show-toplevel 2>/dev/null || pwd)" || exit 1
if [ -z "${ARIS_REPO:-}" ] && [ -f .aris/installed-skills.txt ]; then
ARIS_REPO=$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null) || true
fi
if [ -z "${ARIS_REPO:-}" ] && [ -f "$HOME/.aris/repo" ]; then
ARIS_REPO=$(cat "$HOME/.aris/repo" 2>/dev/null) || true
fi
DEEPXIV_FETCHER=".aris/tools/deepxiv_fetch.py"
[ -f "$DEEPXIV_FETCHER" ] || DEEPXIV_FETCHER="tools/deepxiv_fetch.py"
[ -f "$DEEPXIV_FETCHER" ] || { [ -n "${ARIS_REPO:-}" ] && DEEPXIV_FETCHER="$ARIS_REPO/tools/deepxiv_fetch.py"; }
[ -f "$DEEPXIV_FETCHER" ] || DEEPXIV_FETCHER=""
# Smoke test (optional — adapter resolution shown to user). The cascade
# in Step 3 below branches purely on `[ -n "$DEEPXIV_FETCHER" ]`; a
# resolved-but-non-functional adapter is not currently auto-demoted.
if [ -n "$DEEPXIV_FETCHER" ]; then
echo "DeepXiv adapter resolved at: $DEEPXIV_FETCHER" >&2
else
echo "DeepXiv adapter unresolved (canonical chain exhausted); raw deepxiv CLI fallback will be used." >&2
fi
Step 3: Execute the Minimal Command
Search papers
python3 "$DEEPXIV_FETCHER" search "QUERY" --max MAX_RESULTS
Fallback:
deepxiv search "QUERY" --limit MAX_RESULTS --format json
Brief summary
python3 "$DEEPXIV_FETCHER" paper-brief ARXIV_ID
Fallback:
deepxiv paper ARXIV_ID --brief --format json
Section map
python3 "$DEEPXIV_FETCHER" paper-head ARXIV_ID
Fallback:
deepxiv paper ARXIV_ID --head --format json
Specific section
python3 "$DEEPXIV_FETCHER" paper-section ARXIV_ID "SECTION_NAME"
Fallback:
deepxiv paper ARXIV_ID --section "SECTION_NAME" --format json
Trending
python3 "$DEEPXIV_FETCHER" trending --days 7 --max MAX_RESULTS
Fallback:
deepxiv trending --days 7 --limit MAX_RESULTS --output json
Web search
python3 "$DEEPXIV_FETCHER" wsearch "QUERY"
Fallback:
deepxiv wsearch "QUERY" --output json
Semantic Scholar metadata
python3 "$DEEPXIV_FETCHER" sc "SEMANTIC_SCHOLAR_ID"
Fallback:
deepxiv sc "SEMANTIC_SCHOLAR_ID" --output json
Step 4: Present Results
When searching, present a compact table:
| # | ID | Title | Year | Citations | Notes |
|---|----|-------|------|-----------|-------|
When reading a paper, show:
- title
- arXiv ID
- authors
- venue/date if available
- TLDR or abstract summary
- suggested next step:
brief→head→section
Step 5: Escalate Depth Only When Needed
Use this progression:
searchpaper-briefpaper-headpaper-section- full paper only if necessary
Do not jump to full-paper reads when a brief or one section answers the question.
Step 6: Update Research Wiki (if active)
Required when research-wiki/ exists in the project; skip silently
otherwise. When the wiki dir exists, resolve $WIKI_SCRIPT per the
canonical chain at
shared-references/wiki-helper-resolution.md
(Variant B — warn-and-skip). Ingest papers that were meaningfully
read (brief / head / section / full) during this invocation — mere
search hits without a depth read do not need ingestion:
if [ -d research-wiki/ ]; then
cd "$(git rev-parse --show-toplevel 2>/dev/null || pwd)" || exit 1
ARIS_REPO="${ARIS_REPO:-$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null)}"
if [ -z "${ARIS_REPO:-}" ] && [ -f "$HOME/.aris/repo" ]; then
ARIS_REPO=$(cat "$HOME/.aris/repo" 2>/dev/null) || true
fi
WIKI_SCRIPT=".aris/tools/research_wiki.py"
[ -f "$WIKI_SCRIPT" ] || WIKI_SCRIPT="tools/research_wiki.py"
[ -f "$WIKI_SCRIPT" ] || { [ -n "${ARIS_REPO:-}" ] && WIKI_SCRIPT="$ARIS_REPO/tools/research_wiki.py"; }
[ -f "$WIKI_SCRIPT" ] || {
echo "WARN: research_wiki.py not found; depth-read summary delivered, wiki ingest skipped. Fix: bash tools/install_aris.sh or smart_update.sh (refreshes ~/.aris/repo), export ARIS_REPO, or cp <ARIS-repo>/tools/research_wiki.py tools/." >&2
WIKI_SCRIPT=""
}
if [ -n "$WIKI_SCRIPT" ]; then
for each arxiv_id the user asked this skill to read in depth:
python3 "$WIKI_SCRIPT" ingest_paper research-wiki/ \
--arxiv-id "<arxiv_id>"
fi
fi
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 "$WIKI_SCRIPT" sync research-wiki/ --arxiv-ids <id1>,<id2>,...
after resolving $WIKI_SCRIPT as above.
Key Rules
- Prefer the adapter script over raw
deepxivcommands when available. - DeepXiv is optional. If unavailable, give the install command and suggest
/arxivor/research-lit "topic" - sources: web. - Use section-level reads to save tokens.
- Treat DeepXiv as complementary to
/arxivand/semantic-scholar, not a replacement. - If the result overlaps with a published venue paper from Semantic Scholar, keep the richer venue metadata in the final summary.
Frequently asked questions about DeepXiv Paper Search
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