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Prompts AlphaXiv Single-Paper Lookup and Summarizer

agent research skill risk: low

AlphaXiv Single-Paper Lookup and Summarizer

The prompt instructs an AI to perform quick single-paper lookups on arXiv using AlphaXiv for LLM-optimized summaries, with tiered fallback from overview to full markdown to LaTeX s…

  • External action: low

SKILL 1 file

SKILL.md
---
name: auto-claude-code-research-in-sleep-alphaxiv
description: "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}`

> 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)

Fetch the structured overview from `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 404 — paper not yet processed) or the content is insufficient, proceed to Step 3.

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

Fetch the full paper markdown from `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.

#### Suggest Follow-Up Skills

```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
```

## Update Research Wiki (if active)

**Required when `research-wiki/` exists in the project**; skip silently
otherwise. When the wiki dir exists, resolve `$WIKI_SCRIPT` per the
canonical chain at
[`shared-references/wiki-helper-resolution.md`](../shared-references/wiki-helper-resolution.md)
(Variant B — warn-and-skip), then ingest the single paper that was read:

```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 $2; exit}' .aris/installed-skills.txt 2>/dev/null)}"
  WIKI_SCRIPT=".aris/tools/research_wiki.py"
  [ -f "$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 <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.

## 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.

INPUTS

ARGUMENTS REQUIRED

user-supplied paper ID, URL, or command arguments

e.g. 2401.12345

PAPER_ID REQUIRED

extracted bare arXiv ID without version suffix

e.g. 2401.12345

REQUIRED CONTEXT

  • arXiv paper ID or URL in $ARGUMENTS

OPTIONAL CONTEXT

  • depth directive (overview|abs|src)

ROLES & RULES

  1. Do NOT use this skill for topic discovery, broad literature search, or multi-paper surveys
  2. Strip version suffixes (v1, v2, ...) for API calls
  3. If the overview answers the user's question, stop here
  4. Do NOT read the entire source tree by default
  5. Temporary source artifacts live under /tmp. Do not rely on persistence
  6. If the user only asks for one specific detail, answer it directly — skip the full template
  7. Required when research-wiki/ exists in the project; skip silently otherwise
  8. Overview first: overview is the fastest path and must always be tried before deeper tiers
  9. Minimal reads: At src tier, read only the files that answer the question
  10. Cross-platform: When downloading and extracting the source archive, prefer cross-platform approaches
  11. No PDF parsing: This skill reads structured markdown and LaTeX source, not raw PDFs
  12. Rate limiting: If HTTP 429 occurs, wait 5 seconds and retry once
  13. Complementary, not competing: Do not re-implement functionality of /arxiv or /deepxiv

EXPECTED OUTPUT

Format
markdown
Schema
markdown_sections · Paper Title, arXiv, Source depth, Summary, Key Points, Answer to Your Question
Constraints
  • use default answer shape with paper title, arXiv link, source depth, 2-3 sentence summary, key points, and direct answer if question provided
  • suggest follow-up skills when appropriate
  • conditionally run wiki ingest script if research-wiki/ directory exists

SUCCESS CRITERIA

  • Extract paper ID from multiple URL/ID formats
  • Try overview tier first before escalating
  • Read only necessary LaTeX files at src tier
  • Return structured markdown summary or direct answer
  • Suggest follow-up skills when appropriate
  • Ingest into research-wiki when present

FAILURE MODES

  • May escalate to deeper tiers unnecessarily
  • May read entire LaTeX source tree instead of selective files
  • May fail to locate WIKI_SCRIPT when wiki is present

EXAMPLES

Includes input format examples, override directives with depth flags, default markdown answer template, follow-up skill suggestions, and wiki integration code snippet.

CAVEATS

Dependencies
  • $ARGUMENTS
  • research-wiki/ directory (optional)
  • shared-references/wiki-helper-resolution.md
  • shared-references/integration-contract.md
Missing context
  • Exact runtime environment or shell assumptions for the wiki script block
  • How to handle cases where the user provides multiple paper IDs in one call
Ambiguities
  • Definition of when overview or markdown content is 'insufficient' to escalate tiers is subjective and not quantified.
  • Argument parsing rules for optional '- depth:' directives and version stripping are described at high level without exact regex or logic.

QUALITY

OVERALL
0.83
CLARITY
0.78
SPECIFICITY
0.88
REUSABILITY
0.82
COMPLETENESS
0.85

IMPROVEMENT SUGGESTIONS

  • Add explicit, testable criteria (e.g., length thresholds or missing sections) for escalating from overview to abs/src tiers.
  • Extract the long wiki-ingest code block into a referenced helper file to improve prompt readability while keeping the logic intact.

USAGE

Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.

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