deepxiv
Search and progressively read open-access academic papers through DeepXiv
Install / Use
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill deepxivInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Education & ResearchSupported Platforms
Our assessment of deepxiv
deepxiv scores 93/100 on our quality scale, 20th of 139 Education & Research skills we index (top 15%).
Its SKILL.md is 8.0 KB long, well organised into 15 sections with 18 code examples: a thorough specification that gives an agent plenty to work with.
With 16,644 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 7 days ago, so deepxiv is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
deepxiv compared with similar skills
All 4 of these similar skills score higher than deepxiv; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| deepxiv (this skill)by wanshuiyin | 93 | 16.6k | 7d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.5k | 10d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 73.8k | today | CLAUDE.md |
| last30days-skillby mvanhorn | 100 | 62.8k | 3d ago | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 83.7k | today | MCP Server |
Frequently asked questions
- How do I install deepxiv?
- Run
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill deepxiv. The install tabs above show the steps for each supported agent. - Which AI agents does deepxiv work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is deepxiv safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is deepxiv still maintained?
- The repository was last updated 7 days ago, so deepxiv is actively maintained.
Skill content
View source on GitHubname: deepxiv description: 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. argument-hint: "[query-or-paper-id]" allowed-tools: Bash(*), Read, Write
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), 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.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
