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Deepxiv

wanshuiyin/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.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
14221
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --skill deepxiv

The instruction itself

12 sections, as written by the author

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 inspect papers incrementally instead of loading the full text immediately.

Constants

  • DEEPXIV_FETCHER — canonical name deepxiv_fetch.py, resolved per

shared-references/integration-contract.md §2

(Codex-side chain: $ARIS_REPO/tools/tools/~/.codex/skills/deepxiv/).

Policy D1 — if unresolved (canonical chain exhausted), fall back to raw deepxiv CLI.

  • MAX_RESULTS = 10 — Default number of search results.

> Overrides (append to arguments):

> - /deepxiv "agent memory" - max: 5

> - /deepxiv "2409.05591" - brief

> - /deepxiv "2409.05591" - head

> - /deepxiv "2409.05591" - section: Introduction

> - /deepxiv "trending" - days: 14 - max: 10

> - /deepxiv "karpathy" - web

> - /deepxiv "258001" - sc

Setup

DeepXiv is optional:

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:

  • a paper topic, arXiv ID, or Semantic Scholar ID
  • - max: N
  • - brief
  • - head
  • - section: NAME
  • - trending
  • - days: 7|14|30
  • - web
  • - sc

If the input looks like an arXiv ID and no explicit mode is provided, default to brief.

Step 2: Locate the Adapter

Resolve $DEEPXIV_FETCHER via the canonical strict-safe Codex chain

(see shared-references/integration-contract.md §2):

if [ -z "${ARIS_REPO:-}" ] && [ -f .aris/installed-skills-codex.txt ]; then
    ARIS_REPO=$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills-codex.txt 2>/dev/null) || true
fi
DEEPXIV_FETCHER=""
[ -n "${ARIS_REPO:-}" ] && [ -f "$ARIS_REPO/tools/deepxiv_fetch.py" ] && DEEPXIV_FETCHER="$ARIS_REPO/tools/deepxiv_fetch.py"
[ -z "$DEEPXIV_FETCHER" ] && [ -f tools/deepxiv_fetch.py ] && DEEPXIV_FETCHER="tools/deepxiv_fetch.py"
[ -z "$DEEPXIV_FETCHER" ] && [ -f ~/.codex/skills/deepxiv/deepxiv_fetch.py ] && DEEPXIV_FETCHER="$HOME/.codex/skills/deepxiv/deepxiv_fetch.py"

# Smoke test (optional): 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

If the adapter is unresolved, fall back to raw deepxiv commands.

Step 3: Execute the Minimal Command

[ -n "$DEEPXIV_FETCHER" ] && python3 "$DEEPXIV_FETCHER" search "QUERY" --max MAX_RESULTS
[ -n "$DEEPXIV_FETCHER" ] && python3 "$DEEPXIV_FETCHER" paper-brief ARXIV_ID
[ -n "$DEEPXIV_FETCHER" ] && python3 "$DEEPXIV_FETCHER" paper-head ARXIV_ID
[ -n "$DEEPXIV_FETCHER" ] && python3 "$DEEPXIV_FETCHER" paper-section ARXIV_ID "SECTION_NAME"
[ -n "$DEEPXIV_FETCHER" ] && python3 "$DEEPXIV_FETCHER" trending --days 7 --max MAX_RESULTS
[ -n "$DEEPXIV_FETCHER" ] && python3 "$DEEPXIV_FETCHER" wsearch "QUERY"
[ -n "$DEEPXIV_FETCHER" ] && python3 "$DEEPXIV_FETCHER" sc "SEMANTIC_SCHOLAR_ID"

Fallbacks:

deepxiv search "QUERY" --limit MAX_RESULTS --format json
deepxiv paper ARXIV_ID --brief --format json
deepxiv paper ARXIV_ID --head --format json
deepxiv paper ARXIV_ID --section "SECTION_NAME" --format json
deepxiv trending --days 7 --limit MAX_RESULTS --output json
deepxiv wsearch "QUERY" --output json
deepxiv sc "SEMANTIC_SCHOLAR_ID" --output json

Step 4: Present Results

For search results, present a compact literature table. For paper reads, summarize the title, authors, date, TLDR, and the next recommended depth step.

Step 5: Escalate Depth Only When Needed

Use the progression:

  • search
  • paper-brief
  • paper-head
  • paper-section

Only read the full paper when the user explicitly needs it.

Step 6: Update Research Wiki (if active)

If the project has an active research wiki and the user is building a literature set, add DeepXiv findings as source-backed entries with arXiv/Semantic Scholar IDs, retrieved sections, and the recommended next depth step.

Follow shared-references/integration-contract.md. If the wiki path or schema is unclear, ask before writing.

Key Rules

  • Prefer the adapter script over raw deepxiv commands when available.
  • If DeepXiv is missing, give the install command and suggest /arxiv or /research-lit "topic" - sources: web.
  • Use DeepXiv as an additive source, not a replacement for existing ARIS literature tooling.
  • If the result overlaps with a published venue paper from Semantic Scholar, keep the richer venue metadata in the final summary.

How to use it

Copy the folder

Take wanshuiyin/auto-claude-code-research-in-sleep-deepxiv from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference pip. Without those the skill loads but fails at the first command.