Does this skill require an AlphaXiv account?

No, the skill uses public endpoints on AlphaXiv.org that do not require any authentication or API keys.

What happens if a specific paper report is not found?

The skill includes error handling that checks for high-level reports first, then full-text markdown. If neither is available, it provides the direct arXiv PDF link.

How does AlphaXiv Paper Lookup improve research analysis?

It converts complex, unstructured PDFs into LLM-optimized markdown reports, allowing Claude to process and explain research content with much higher accuracy and speed.

Can Claude extract specific sections like equations or tables?

Yes, by fetching the full-text markdown version of the paper through this skill, Claude can more reliably identify and explain specific technical sections compared to reading raw PDF text.

AlphaXiv Paper Lookup

Name: AlphaXiv Paper Lookup
Author: christyjacob4

bychristyjacob4

•

Ciencia de Datos y ML

Retrieves structured, machine-readable summaries and full-text markdown of research papers from AlphaXiv.org for efficient analysis.

The AlphaXiv Paper Lookup skill empowers Claude to efficiently digest and analyze scientific research papers by bypassing traditional PDF reading in favor of optimized markdown reports from AlphaXiv. It automatically extracts paper IDs from arXiv or AlphaXiv URLs and fetches either high-level AI-generated summaries or complete paper text. This allows for faster literature reviews, deeper technical analysis, and more accurate explanations of complex research without the latency or formatting issues typically associated with raw PDF processing.

Características Principales

01Public endpoint integration requiring zero authentication

02Retrieval of structured, LLM-optimized research summaries

03Fallback mechanism for deep-dive technical section analysis

04Access to full paper content in clean, parseable markdown format

051 GitHub stars

06Automatic paper ID extraction from various URL and string formats

Casos de Uso

01Rapidly reviewing multiple papers without downloading or converting PDFs

02Summarizing recent machine learning breakthroughs from arXiv links

03Analyzing specific equations or methodologies within technical research

Características Principales

01Public endpoint integration requiring zero authentication

02Retrieval of structured, LLM-optimized research summaries

03Fallback mechanism for deep-dive technical section analysis

04Access to full paper content in clean, parseable markdown format

051 GitHub stars

06Automatic paper ID extraction from various URL and string formats

Casos de Uso

01Rapidly reviewing multiple papers without downloading or converting PDFs

02Summarizing recent machine learning breakthroughs from arXiv links

03Analyzing specific equations or methodologies within technical research