Transform academic papers into in-depth technical articles with multiple writing style options. Use the MinerU Cloud API for high-precision PDF parsing, automatically extracting images, tables, and formulas. Optional formula explanations and GitHub code analysis, generating Markdown and HTML formats.
apm install @proyecto26/paper-analyzer[](https://apm-p1ls2dz87-atlamors-projects.vercel.app/packages/@proyecto26/paper-analyzer)---
name: paper-analyzer
description: |
Transform academic papers into in-depth technical articles with multiple writing style options.
Use the MinerU Cloud API for high-precision PDF parsing, automatically extracting images, tables, and formulas.
Optional formula explanations and GitHub code analysis, generating Markdown and HTML formats.
---
# 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
```bash
pip install requests markdown
```
## Workflow
### Step 1: PDF Parsing (Using MinerU API)
```bash
python scripts/mineru_api.py <pdf_path> <output_dir>
```
Or pass the token directly:
```bash
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
```bash
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