DeepXiv Paper Search & Progressive Reading

Search topic or paper ID: $ARGUMENTS

Role & Positioning

DeepXiv is the progressive-reading literature source:

Skill	Best 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:

bash

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:

bash

python3 tools/deepxiv_fetch.py --help

tools/deepxiv_fetch.py

is not available, fall back to raw

deepxiv

commands.

Step 3: Execute the Minimal Command

Search papers

bash

python3 tools/deepxiv_fetch.py search "QUERY" --max MAX_RESULTS

Fallback:

bash

deepxiv search "QUERY" --limit MAX_RESULTS --format json

Brief summary

bash

python3 tools/deepxiv_fetch.py paper-brief ARXIV_ID

Fallback:

bash

deepxiv paper ARXIV_ID --brief --format json

Section map

bash

python3 tools/deepxiv_fetch.py paper-head ARXIV_ID

Fallback:

bash

deepxiv paper ARXIV_ID --head --format json

Specific section

bash

python3 tools/deepxiv_fetch.py paper-section ARXIV_ID "SECTION_NAME"

Fallback:

bash

deepxiv paper ARXIV_ID --section "SECTION_NAME" --format json

Trending

bash

python3 tools/deepxiv_fetch.py trending --days 7 --max MAX_RESULTS

Fallback:

bash

deepxiv trending --days 7 --limit MAX_RESULTS --output json

Web search

bash

python3 tools/deepxiv_fetch.py wsearch "QUERY"

Fallback:

bash

deepxiv wsearch "QUERY" --output json

Semantic Scholar metadata

bash

python3 tools/deepxiv_fetch.py sc "SEMANTIC_SCHOLAR_ID"

Fallback:

bash

deepxiv sc "SEMANTIC_SCHOLAR_ID" --output json

Step 4: Present Results

When searching, present a compact table:

text

| # | 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:

```
search
```
```
paper-brief
```
```
paper-head
```
```
paper-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. 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/ ]:
    for each arxiv_id the user asked this skill to read in depth:
        python3 tools/research_wiki.py ingest_paper research-wiki/ \
            --arxiv-id "<arxiv_id>"

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 tools/research_wiki.py sync research-wiki/ --arxiv-ids <id1>,<id2>,...

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.

deepxiv

NPX Install

Tags

SKILL.md Content

DeepXiv Paper Search & Progressive Reading

Role & Positioning

Constants

Setup

Workflow

Step 1: Parse Arguments

Step 2: Locate the Adapter

Step 3: Execute the Minimal Command

Step 4: Present Results

Step 5: Escalate Depth Only When Needed

Step 6: Update Research Wiki (if active)

Key Rules