agentleFS
ImmortalqxImmortalqx/my_codex_skills/alphaxiv/SKILL.md

alphaxiv

Skill54 starsChanged 5 months agoMITView on GitHub

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.

5 other projects use a version of this, 4 of them edited.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

7 rules. 5 are common, 1 is distinctive, and 1 is very specific to this project.

  • 5

    Common

    Most of the 5 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Common:

    If the overview answers the user's question, stop here.

    line 46
  2. Distinctive:

    If the request fails (HTTP 404 — paper not yet processed) or the content is insufficient, proceed to Step 3.

    line 48
  3. Common:

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

    line 56
  4. Very specific:

    When the overview and full markdown are both insufficient (e.g., the user asks about equations, proofs, appendix details, or implementation …

    line 60
  5. Common:

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

    line 70
  6. Common:

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

    line 96
  7. Common:

    Cross-platform: When downloading and extracting the source archive, prefer cross-platform approaches (e.g., Python stdlib) over …

    line 102

“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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 a quick single-paper reader for one known arXiv paper. It is best when the user provides a bare arXiv ID, an arXiv URL, a PDF URL, or an AlphaXiv URL and wants a concise explanation without running a broad literature survey.

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

## [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.

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. If the user needs PDF-specific content, report that this standalone skill does not parse PDFs.
  • Rate limiting: arXiv source download may rate-limit. If HTTP 429 occurs, wait 5 seconds and retry once. If still blocked, report the error clearly.

Standalone Scope

The only external dependency is public network access to AlphaXiv and arXiv.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.