How do I install the Proyecto26 Sherlock AI Plugin Paper Analyzer skill?

Run npx skillmds@latest add tomevault-io/proyecto26-sherlock-ai-plugin-paper-analyzer in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Proyecto26 Sherlock AI Plugin Paper Analyzer skill do?

Academic Paper Analyzer – In-Depth Analysis of Academic Papers It is listed under Coding & Dev Tools on SkillMD.

Is Proyecto26 Sherlock AI Plugin Paper Analyzer safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Proyecto26 Sherlock AI Plugin Paper Analyzer?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Proyecto26 Sherlock AI Plugin Paper Analyzer free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Proyecto26 Sherlock AI Plugin Paper Analyzer?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Proyecto26 Sherlock AI Plugin Paper Analyzer by tomevault-io

Name: Proyecto26 Sherlock AI Plugin Paper Analyzer
Author: tomevault-io

File contents

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

Converted and distributed by TomeVault — claim your Tome and manage your conversions.

---name: proyecto26-sherlock-ai-plugin-paper-analyzerdescription: Academic Paper Analyzer – In-Depth Analysis of Academic Papers---# 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 Token1. Visit https://mineru.net and register an account2. Obtain an API Token3. Set an environment variable (recommended): ```bash export MINERU_TOKEN="your_token_here" ```### Dependency Installation```bashpip install requests markdown```## Workflow### Step 1: PDF Parsing (Using MinerU API)```bashpython scripts/mineru_api.py <pdf_path> <output_dir>```Or pass the token directly:```bashpython 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```bashpython 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---> Converted and distributed by [TomeVault](https://tomevault.io/claim/proyecto26) — claim your Tome and manage your conversions.

Frequently asked questions

Proyecto26 Sherlock AI Plugin Paper Analyzer