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Auto-claude-code-research-in-sleep 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.

install
source · Clone the upstream repo
git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/deepxiv" ~/.claude/skills/wanshuiyin-auto-claude-code-research-in-sleep-deepxiv && rm -rf "$T"
manifest: skills/deepxiv/SKILL.md
source content

DeepXiv Paper Search & Progressive Reading

Search topic or paper ID: $ARGUMENTS

Role & Positioning

DeepXiv is the progressive-reading literature source:

SkillBest 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.

Constants

  • FETCH_SCRIPT — 
    tools/deepxiv_fetch.py
    relative to the current project. If unavailable, fall back to the raw 
    deepxiv
    CLI.
  • 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

Prefer the ARIS adapter:

python3 tools/deepxiv_fetch.py --help

If 

tools/deepxiv_fetch.py
is not available, fall back to raw 
deepxiv
commands.

Step 3: Execute the Minimal Command

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

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.

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.