paper-xray

Analyze academic papers into structured Markdown reports with bidirectional links.

1|Updated Mar 15, 2026
One-click install
npx skills add https://github.com/gudo7208/paper-xray --skill paper-xray
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: paper-xray
Source: https://github.com/gudo7208/paper-xray/tree/main
Command: npx skills add https://github.com/gudo7208/paper-xray --skill paper-xray

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Academic research often requires structured, repeatable analysis of papers and organization of insights. This Skill automates deep analysis, batch processing, relevance triage, and topic surveys, turning scattered papers into a connected knowledge graph with bidirectional links.

Core Features & Use Cases

  • Deep single-paper deconstruction: problem/motivation, method, experiments, contributions, and critique.
  • Batch parallel analysis: analyze multiple papers with cross-paper synthesis and consolidated notes.
  • Quick triage: rapid relevance scoring to prioritize reading without producing full notes.
  • Topic-mode surveys: auto-scan a topic landscape and generate an organized survey with citations and knowledge network.
  • Auto-archiving: outputs integrate into the workspace with bidirectional links and index maintenance.

Quick Start

Provide a paper name, arXiv ID, DOI, or URL to start a single-paper analysis.

Frequently Asked Questions about paper-xray

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate academic paper analysis and generate structured Markdown reports?

Automated academic paper analysis extracts deep structural knowledge from papers and produces structured Markdown reports with bidirectional links. You simply provide a paper name, arXiv ID, DOI, or URL to initiate the single-paper deconstruction process.

Can I do batch parallel analysis on multiple arXiv papers to cross-synthesize findings?

Batch parallel analysis processes multiple papers simultaneously to generate cross-paper synthesis and consolidated notes. This allows you to triage relevance quickly and scan a topic landscape across arXiv sources without manual reading.

What is the best way to conduct a topic survey and build a knowledge graph from arXiv papers?

Conducting a topic survey is best handled by auto-scanning a topic landscape to generate an organized survey with citations. This process turns scattered papers into a connected knowledge graph with bidirectional links and automated workspace archiving.

How do I quickly triage relevance for academic papers before committing to a full read?

Quick triage relevance scoring rapidly evaluates academic papers to prioritize your reading list. This automated process scores relevance without producing full notes, saving time during literature reviews and batch processing.

Does automated paper analysis produce knowledge extraction with bidirectional links?

Automated paper analysis produces deep knowledge extraction complete with bidirectional links. Outputs integrate into the workspace with automated archiving and index maintenance, creating a connected knowledge network.

What are the limitations of automated deep analysis for academic papers?

Automated deep analysis limitations depend on the source accessibility of arXiv IDs, DOIs, or URLs provided. While it excels at structural deconstruction and topic surveys, complex mathematical proofs or highly nuanced critiques may still require manual expert review.