---
id: wanshuiyin/Auto-claude-code-research-in-sleep/alphaxiv
version: "60e76608"
license: MIT
install: manual
updated: 2026-07-22
---

# alphaxiv — AlphaXiv delivers instant, machine-readable summaries of individual papers from arXiv, optimized for language models. When the overview isn't enough, it cascades to full markdown and LaTeX source inspection for deeper details. Ideal for explaining a specific paper—not for broad literature discovery.

Publisher: wanshuiyin · Stars: 13939 · Updated: 2026-07-22

Install (manual): `git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep`

## SKILL.md

# AlphaXiv Paper Lookup

Lookup paper: $ARGUMENTS

> Quick single-paper reader with tiered source fallback (overview → full markdown → LaTeX source). Powered by [AlphaXiv](https://alphaxiv.org).

## Role & Positioning

This skill is the **quick single-paper reader** that returns LLM-optimized summaries:

| 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** |

**Do NOT use this skill for** topic discovery, broad literature search, or multi-paper surveys — use `/research-lit` or `/arxiv` instead.

## Constants

- **OVERVIEW_URL** = `https://alphaxiv.org/overview/{PAPER_ID}.md`
- **ABS_URL** = `https://alphaxiv.org/abs/{PAPER_ID}.md`
- **ARXIV_SRC_URL** = `https://arxiv.org/src/{PAPER_ID}`
- **ALPHAXIV_UA** = `Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36` — any modern browser UA works; update the version numbers if AlphaXiv starts blocking this value again

> Overrides (append to arguments):
> - `/alphaxiv 2401.12345` — quick overview
> - `/alphaxiv "https://arxiv.org/abs/2401.12345"` — auto-extract ID
> - `/alphaxiv 2401.12345 - depth: src` — force LaTeX source inspection
> - `/alphaxiv 2401.12345 - depth: abs` — force full markdown

## Workflow

### Step 1: Parse Arguments & Extract Paper ID

Parse `$ARGUMENTS` to extract a bare arXiv paper ID. Accept these input formats:

- `https://arxiv.org/abs/2401.12345` or `https://arxiv.org/abs/2401.12345v2`
- `https://arxiv.org/pdf/2401.12345`
- `https://alphaxiv.org/overview/2401.12345`
- `https://alphaxiv.org/abs/2401.12345`
- `2401.12345` or `2401.12345v2`

Strip version suffixes (`v1`, `v2`, ...) for API calls. Store as `PAPER_ID`.

Parse optional directives:
- **`- depth: overview|abs|src`**: force a specific tier instead of cascading

### Step 2: Fetch AlphaXiv Overview (Tier 1 — Fastest)

Use `curl` with `{ALPHAXIV_UA}` to fetch the AlphaXiv overview. AlphaXiv may return 403 for non-browser User-Agents; setting a standard browser UA reduces false positives from bot-detection:

```bash
curl -sL --max-time 15 -A "{ALPHAXIV_UA}" "https://alphaxiv.org/overview/{PAPER_ID}.md"
```

This returns a **structured, LLM-optimized report** designed for machine consumption. Use this as the default and preferred source.

If the overview answers the user's question, **stop here**. Do not fetch deeper tiers unnecessarily.

If the request fails (HTTP 4xx — 403 bot-block or 404 not-yet-processed) or returns empty content, proceed to Step 3.

### Step 3: Fetch Full AlphaXiv Markdown (Tier 2 — More Detail)

Use `curl` with `{ALPHAXIV_UA}` to fetch the full paper markdown:

```bash
curl -sL --max-time 15 -A "{ALPHAXIV_UA}" "https://alphaxiv.org/abs/{PAPER_ID}.md"
```

This provides the full paper body as markdown. Use when the user needs:
- Specific methodology details
- Detailed experimental results
- Particular sections not covered in the overview

If this still does not answer the question, proceed to Step 4.

### Step 4: Fetch arXiv LaTeX Source (Tier 3 — Deepest)

When the overview and full markdown are both insufficient (e.g., the user asks about equations, proofs, appendix details, or implementation specifics), download the paper's LaTeX source from `https://arxiv.org/src/{PAPER_ID}`.

The source is a `.tar.gz` archive. Download it to a temporary directory, extract it, and list the `.tex` files inside.

Then inspect **only** the files needed to answer the question. Prioritize:

1. Top-level `*.tex` files (usually the main document)
2. Files referenced by `\input{}` or `\include{}`
3. Appendices, tables, or sections directly related to the user's question

**Do NOT read the entire source tree by default.** Read selectively.

Temporary source artifacts live under `/tmp`. Do not rely on persistence.

### Step 5: Present Results

#### Default Answer Shape

```markdown
## [Paper Title]

- **arXiv**: [PAPER_ID] — https://arxiv.org/abs/[PAPER_ID]
- **Source depth**: overview | abs | src

### Summary
[2-3 sentence summary]

### Key Points
- [point 1]
- [point 2]
- [point 3]

### Answer to Your Question
[Direct answer if the user asked a specific question]
```

If the user only asks for one specific detail, answer it directly — skip the full template.

**After presenting the summary, you MUST proceed to Step 6 before ending the turn.**

### Step 6: Research Wiki Ingest

**You MUST always run the bash block below — it checks for `research-wiki/` internally and exits silently when absent.** Do NOT skip this step based on your own directory check; the bash block handles that for you.

Substitute only `<paper_arxiv_id>` and `<thesis>`; keep `${ARIS_REPO:-...}` as-is so an already-set env var is preserved.

```bash
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; paper 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=""
  }
  [ -n "$WIKI_SCRIPT" ] && python3 "$WIKI_SCRIPT" ingest_paper research-wiki/ \
      --arxiv-id "<paper_arxiv_id>" \
      [--thesis "<one-line thesis from the Tier 1 overview>"]
fi
```

The helper handles metadata fetch, slug, dedup, page creation, index
rebuild, and log append — **do not handwrite `papers/<slug>.md`**. See
[`shared-references/integration-contract.md`](../shared-references/integration-contract.md).
If wiki was not present at read time (or the helper was unreachable),
the user can backfill via
`python3 "$WIKI_SCRIPT" sync research-wiki/ --arxiv-ids <id>` after
resolving `$WIKI_SCRIPT` as above.

#### Suggest Follow-Up Skills (after Step 6 completes)

```text
/arxiv "PAPER_ID" - download          - download the PDF to local library
/deepxiv "PAPER_ID" - section: Methods  - read a specific section progressively
/research-lit "related topic"        - multi-source literature survey
/novelty-check "idea from paper"     - verify novelty against this paper's area
```

## Key Rules

- **Overview first**: `overview` is the fastest path and must always be tried before deeper tiers. Only escalate when needed.
- **Minimal reads**: At `src` tier, read only the files that answer the question. Full-tree reads waste tokens.
- **Cross-platform**: When downloading and extracting the source archive, prefer cross-platform approaches (e.g., Python stdlib) over platform-specific commands to ensure Windows/WSL compatibility.
- **No PDF parsing**: This skill reads structured markdown and LaTeX source, not raw PDFs. For PDF content, suggest `/arxiv` with download.
- **Rate limiting**: arXiv source download may rate-limit. If HTTP 429 occurs, wait 5 seconds and retry once. If still blocked, report the error and suggest `/deepxiv` as alternative.
- **Complementary, not competing**: This skill complements `/arxiv` (search + download) and `/deepxiv` (progressive reading). Do not re-implement their functionality.

## Integration with Other Skills

### As enrichment in `/research-lit`

`/research-lit` can use this skill's Tier 1 (overview) as a fast enrichment step between search and deep analysis. After finding arXiv papers in Step 1, fetch AlphaXiv overviews to quickly assess relevance before committing to full-text reads:

```
Step 1: Search → list of arXiv IDs
Step 1.5: AlphaXiv overview for top 5-8 papers (this skill, Tier 1 only)
Step 2: Deep analysis only for papers that pass the relevance filter
```

This saves significant tokens by filtering out marginally relevant papers before deep reading.

### As follow-up from other skills

After `/research-lit`, `/novelty-check`, or `/idea-discovery` surface a specific paper, users can invoke `/alphaxiv PAPER_ID` for a fast deep-dive without re-running the full survey.


[View on SkillFed](https://skillfed.io/wanshuiyin/Auto-claude-code-research-in-sleep/alphaxiv) · [View on GitHub](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep)