Paper Analyzer

Academic Paper Analyzer – In-Depth Analysis of Academic Papers

Core Capabilities

• MinerU Cloud API for high-precision PDF parsing
• Automatic extraction of images, tables, and LaTeX formulas
• Multiple writing styles: storytelling / academic / concise
• Optional formula explanations: insert formula images with detailed symbol explanations
• Optional code analysis: combine explanations with GitHub open-source code
• Output Markdown + HTML (base64-embedded images)

Prerequisites

MinerU API Token

1. Visit https://mineru.net and register an account
2. Obtain an API Token
3. Set an environment variable (recommended):

``bash export MINERU_TOKEN="your_token_here" ``

Dependency Installation

pip install requests markdown

Workflow

Step 1: PDF Parsing (Using MinerU API)

python scripts/mineru_api.py  

Or pass the token directly:

python scripts/mineru_api.py paper.pdf ./output YOUR_TOKEN

Output:

• output_dir/*.md – Markdown files (including formulas and tables)
• output_dir/images/ – High-quality extracted images

Step 2: Extract Paper Metadata

python scripts/extract_paper_info.py /*.md paper_info.json

Step 3: Style Selection (Ask the User)

Before generating the article, you must ask the user to choose the following options:

1. Writing Style (Required)

| Style | Characteristics | Use Cases | |------|-----------------|-----------| | storytelling | Starts from intuition, uses metaphors and examples, narrative-driven | Blogs, tech columns, popular science | | academic | Professional terminology, rigorous expression, preserves original concepts | Academic reports, surveys, research group sharing | | concise | Straight to the point, tables and lists, high information density | Quick reads, paper overviews, technical research |

2. Formula Option (Optional)

| Option | Description | |------|-------------| | with-formulas | Insert formula images and explain symbol meanings in detail | | no-formulas (default) | Pure text description, no formula images |

3. Code Option (Optional, only if the paper has GitHub)

| Option | Description | |------|-------------| | with-code | Clone the repository, include key source code, and explain it alongside the paper | | no-code (default) | No code analysis |

Step 4: Intelligent Article Generation

(...)

API Limits

• Maximum file size: 200MB
• Maximum pages per file: 600
• Supports PDF, DOC, PPT, images, and more

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: proyecto26
• Source: proyecto26/sherlock-ai-plugin
• License: MIT

Install and usage instructions live in the source repository linked above.