paper-analyzer

Extract 12 structured reading elements from academic papers into Excel.

265|23|Updated Feb 7, 2026
One-click install
npx skills add https://github.com/yipng05-max/-skills --skill paper-analyzer-yipng05-max
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: paper-analyzer
Source: https://github.com/yipng05-max/-skills/tree/main/paper-analyzer
Command: npx skills add https://github.com/yipng05-max/-skills --skill paper-analyzer-yipng05-max

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openpyxl, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps you turn a research paper into structured, comparable notes by extracting 12 predefined reading elements and exporting them to an Excel file, saving you from manual outlining and cross-paper comparison.

Core Features & Use Cases

  • 12-element structured paper analysis: Extracts background, research question type, conclusions, literature synthesis and critique, methods, theoretical framework, consistency/inconsistency findings, contributions, limitations, and future prospects.
  • PDF/Word-friendly reading flow: Reads user-provided local paper files and falls back to text extraction for PDFs when direct reading is insufficient.
  • Excel output for single and multi-paper workflows: Saves results into the same folder as the analyzed paper, supporting both one-paper and N-paper comparison exports.

Quick Start

Use the paper-analyzer skill to analyze the attached paper file and save the 12-element Excel breakdown to the paper’s folder.

Frequently Asked Questions about paper-analyzer

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

FAQPage Schema
How do I extract structured elements from academic papers for a literature review?

Paper analysis extracts 12 predefined reading elements like background, methods, and conclusions from academic papers, exporting the structured breakdown to Excel for systematic literature review and cross-paper comparison.

Can I parse local PDF files and export the reading notes to Excel?

Yes, you can parse local PDF or Word documents. The skill reads the paper file, applies text extraction fallback for PDFs, and uses an export script to generate a deterministic Excel file saved in the same folder.

What is the best way to compare multiple research papers systematically?

The best way to compare multiple research papers is using a 12-element schema extraction. This maps content to structured fields like theoretical framework and limitations, exporting N-paper workflows into a single Excel file for comparison.

Do I need Python openpyxl to export structured paper analysis results?

Yes, openpyxl is required. The skill depends on the openpyxl library to execute the included export script and generate the deterministic Excel output containing your 12 structured reading elements.

What specific research methods and framework elements does this paper analysis extract?

Paper analysis extracts 12 elements: background, research question type, conclusions, literature synthesis, methods, theoretical framework, consistency findings, contributions, limitations, and future prospects from academic documents.

Are there limitations when parsing PDFs for academic reading elements?

A limitation is that direct PDF reading may be insufficient, requiring a fallback to text extraction. If the PDF lacks selectable text or has complex formatting, parsing the 12 structured reading elements may be less accurate.