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.

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: 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: 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 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 ${ARIS REPO: ...} as is so an already set env var is preserved. The helper handles metadata fetch, slug, dedup, page creation, index rebuild, and log append — do not handwrite papers/<slug .md . See [ shared references/integration contract.md ](../shared references/integration contract.md). If wiki was not present at read time (or the helper was unreachable), the user can backfill via python3 "$WIKI SCRIPT" sync research wiki/ arxiv ids <id after resolving $WIKI SCRIPT as above. Suggest Follow Up Skills (after Step 6 completes) 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: 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.