Skill

paper-analyzer

Transforms academic PDFs into technical articles via MinerU Cloud API parsing of images, tables, formulas. Supports storytelling/academic/concise styles, optional formula explanations, GitHub code analysis. Outputs Markdown/HTML.

Python

Markdown

Github

documentation

npx claudepluginhub proyecto26/sherlock-ai-plugin --plugin sherlock-ai-plugin

Tool Access

This skill uses the workspace's default tool permissions.

Preview

- **MinerU Cloud API** for high-precision PDF parsing

Supporting Assets

cover-prompt-simple.txtcover-prompt.mdrequirements.txtscripts/convert_pdf.pyscripts/extract_paper_info.pyscripts/generate_html.pyscripts/mineru_api.pystyles/academic.mdstyles/concise.mdstyles/no-code.mdstyles/no-formulas.mdstyles/storytelling.mdstyles/with-code.mdstyles/with-formulas.md

SKILL.md

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Stats

Stars18

Forks1

Last CommitFeb 3, 2026

Used By2 plugins

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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

Visit https://mineru.net and register an account
Obtain an API Token
Set an environment variable (recommended):
```
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 <pdf_path> <output_dir>

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 <output_dir>/*.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