Install
$ agentstack add skill-wanshuiyin-auto-claude-code-research-in-sleep-alphaxiv ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
AlphaXiv Paper Lookup
Lookup paper: $ARGUMENTS
> Quick single-paper reader with tiered source fallback (overview → full markdown → LaTeX source). Powered by AlphaXiv.
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 - ARXIVSRCURL =
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/2401.12345orhttps://arxiv.org/abs/2401.12345v2https://arxiv.org/pdf/2401.12345https://alphaxiv.org/overview/2401.12345https://alphaxiv.org/abs/2401.123452401.12345or2401.12345v2
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:
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:
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:
- Top-level
*.texfiles (usually the main document) - Files referenced by
\input{}or\include{} - 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
## [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 ` and ; keep ${ARIS_REPO:-...}` as-is so an already-set env var is preserved.
if [ -d research-wiki/ ]; then
cd "$(git rev-parse --show-toplevel 2>/dev/null || pwd)" || exit 1
ARIS_REPO="${ARIS_REPO:-$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null)}"
WIKI_SCRIPT=".aris/tools/research_wiki.py"
[ -f "$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, export ARIS_REPO, or cp /tools/research_wiki.py tools/." >&2
WIKI_SCRIPT=""
}
[ -n "$WIKI_SCRIPT" ] && python3 "$WIKI_SCRIPT" ingest_paper research-wiki/ \
--arxiv-id "" \
[--thesis ""]
fi
The helper handles metadata fetch, slug, dedup, page creation, index rebuild, and log append — do not handwrite papers/.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 after resolving $WIKI_SCRIPT as above.
Suggest Follow-Up Skills (after Step 6 completes)
/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:
overviewis the fastest path and must always be tried before deeper tiers. Only escalate when needed. - Minimal reads: At
srctier, 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
/arxivwith 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
/deepxivas 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.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: wanshuiyin
- Source: wanshuiyin/Auto-claude-code-research-in-sleep
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.