MCPInstall

deepxiv

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.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/wanshuiyin/auto-claude-code-research-in-sleep --skill deepxiv
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads deepxiv automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

DeepXiv Paper Search & Progressive Reading

Search topic or paper ID: $ARGUMENTS

Role & Positioning

DeepXiv is the progressive-reading literature source:

SkillSourceBest for
/arxivarXiv APIBatch search, PDF download, metadata
/deepxivDeepXiv SDKProgressive section-level reading
/semantic-scholarS2 APIPublished venue metadata, citation counts
/alphaxivwww.alphaxiv.orgInstant 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 per shared-references/integration-contract.md §2 (Policy D1 — primary + fallback cascade). If unresolved (canonical chain exhausted), fall back to the raw deepxiv CLI (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: 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 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:

  1. search
  2. paper-brief
  3. paper-head
  4. paper-section
  5. 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 deepxiv commands when available.
  • DeepXiv is optional. If unavailable, give the install command and suggest /arxiv or /research-lit "topic" - sources: web.
  • Use section-level reads to save tokens.
  • Treat DeepXiv as complementary to /arxiv and /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.

FAQ

What does the deepxiv skill do?

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.

How do I install deepxiv?

Run npx skills add https://github.com/wanshuiyin/auto-claude-code-research-in-sleep --skill deepxiv in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/deepxiv/ (personal) or .claude/skills/deepxiv/ (project).

Which AI agents can use deepxiv?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is deepxiv safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains deepxiv?

It is published by wanshuiyin in wanshuiyin/auto-claude-code-research-in-sleep. It has 481 recorded installs.

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