Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
日本語の概要は準備中です。原文の説明を表示しています。
Quick single-paper lookup via AlphaXiv LLM-optimized summaries with tiered source fallback. Use when user says "explain this paper", "summarize paper", pastes an arXiv/AlphaXiv URL, or provides a bare arXiv ID for quick understanding - not for broad literature search.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Lookup paper: $ARGUMENTS
Quick single-paper reader with tiered source fallback (overview → full markdown → LaTeX source). Powered by AlphaXiv.
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 | www.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.
https://www.alphaxiv.org/overview/{PAPER_ID}.mdhttps://www.alphaxiv.org/abs/{PAPER_ID}.mdhttps://arxiv.org/src/{PAPER_ID}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 againOverrides (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
Parse $ARGUMENTS to extract a bare arXiv paper ID. Accept these input formats:
https://arxiv.org/abs/2401.12345 or https://arxiv.org/abs/2401.12345v2https://arxiv.org/pdf/2401.12345https://alphaxiv.org/overview/2401.12345 or https://www.alphaxiv.org/overview/2401.12345https://alphaxiv.org/abs/2401.12345 or https://www.alphaxiv.org/abs/2401.123452401.12345 or 2401.12345v2Strip version suffixes (v1, v2, ...) for API calls. Store as PAPER_ID.
Parse optional directives:
- depth: overview|abs|src: force a specific tier instead of cascadingUse 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://www.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.
Use curl with {ALPHAXIV_UA} to fetch the full paper markdown:
curl -sL --max-time 15 -A "{ALPHAXIV_UA}" "https://www.alphaxiv.org/abs/{PAPER_ID}.md"
This provides the full paper body as markdown. Use when the user needs:
If this still does not answer the question, proceed to Step 4.
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:
*.tex files (usually the main document)\input{} or \include{}Do NOT read the entire source tree by default. Read selectively.
Temporary source artifacts live under /tmp. Do not rely on persistence.
## [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.
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 ${ARIS_REPO:-...} as-is so an already-set env var is preserved.
if [ -d research-wiki/ ]; then
cd "$(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.
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.
/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
overview is the fastest path and must always be tried before deeper tiers. Only escalate when needed.src tier, read only the files that answer the question. Full-tree reads waste tokens./arxiv with download./deepxiv as alternative./arxiv (search + download) and /deepxiv (progressive reading). Do not re-implement their functionality./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.
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.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Use when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission.
日本語の概要は準備中です。原文の説明を表示しています。
Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental data.
日本語の概要は準備中です。原文の説明を表示しています。
Search, download, and summarize academic papers from arXiv. Use when user says "search arxiv", "download paper", "fetch arxiv", "arxiv search", "get paper pdf", or wants to find and save papers from arXiv to the local paper library.
日本語の概要は準備中です。原文の説明を表示しています。
Autonomously improve a generated paper via Gemini review through gemini-review MCP → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.
日本語の概要は準備中です。原文の説明を表示しています。
Autonomously improve a generated paper via GPT-6-Astra xhigh review → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.
日本語の概要は準備中です。原文の説明を表示しています。