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paper-analyzer

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.

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proyecto26/sherlock-ai-plugin
Works withGitHub
See how to install

Files included (15)

  • SKILL.md2.9 KB
  • cover-prompt-simple.txt766 B
  • cover-prompt.md1.2 KB
  • requirements.txt32 B
  • scripts/convert_pdf.py5.2 KB
  • scripts/extract_paper_info.py3.7 KB
  • scripts/generate_html.py4.0 KB
  • scripts/mineru_api.py9.8 KB
  • styles/academic.md1.4 KB
  • styles/concise.md1.3 KB
  • styles/no-code.md377 B
  • styles/no-formulas.md742 B
  • styles/storytelling.md1.4 KB
  • styles/with-code.md945 B
  • styles/with-formulas.md633 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

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): 
    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)

StyleCharacteristicsUse Cases
storytellingStarts from intuition, uses metaphors and examples, narrative-drivenBlogs, tech columns, popular science
academicProfessional terminology, rigorous expression, preserves original conceptsAcademic reports, surveys, research group sharing
conciseStraight to the point, tables and lists, high information densityQuick reads, paper overviews, technical research

2. Formula Option (Optional)

OptionDescription
with-formulasInsert 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)

OptionDescription
with-codeClone 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

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