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Image Breaker

核心功能:提取网页、PDF、图片等内容,按规范结构生成带标签的结构化Markdown笔记,本地存储并自动同步至Obsidian。典型场景:用户分享实验室报告URL、学术PDF、内容截图,需整理成可检索的有序笔记。输入为URL、PDF、图片或直接粘贴的内容,输出为带元数据的Markdown文件,同步至Obsidian并返回存储路径。

biohackerrrrrr
biohackerrrrrr
热度 51.74
最近更新 2026-05-11 17:29:11
分类:效率依赖:联网浏览搜索 / 读写文件 / 代码执行 / 第三方 API / 内部调用大模型应用场景:摘要总结 / 笔记整理 / 文件转换 / 研究

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add image-breaker
Metadata
name
image-breaker
description
Extract and break down content from web documents, PDFs, images, and URLs into structured markdown notes stored locally and synced to Obsidian. Use when the user shares a URL, PDF, screenshot, or document and wants the content converted to organized notes with proper tagging and categorization.

Image Breaker

Convert documents, PDFs, images, and web content into structured markdown notes saved to workspace and synced to Obsidian.

Workflow

1. Extract Content

For URLs/PDFs:

Use web_fetch to extract content

For images:

Use image tool to analyze and extract text

For already-analyzed content:

User may paste content directly or you've already extracted it

2. Structure the Content

Convert raw content into organized markdown:

Sections to create:

  • Overview - What is this document/content about?
  • Key Points - Bullet list of main takeaways
  • Detailed Breakdown - Organized subsections with headers
  • Reference Ranges/Standards (if applicable) - Tables for numerical data
  • Action Items (if applicable) - What to do with this information
  • Source - Original URL or document name

Formatting guidelines:

  • Use tables for numerical data (reference ranges, standards, comparisons)
  • Use bullet lists for key points
  • Use headers (##, ###) for organization
  • Include code blocks for technical content
  • Bold important terms on first mention

3. Save and Sync

Create the markdown note with proper frontmatter and save to workspace:

# Prepare frontmatter
date = "2026-02-10"
tags = ["research", "bloodwork", "nmr"]  # Auto-assigned based on content
title = "NMR Lipid Panel Reference Ranges"

# Build full markdown content
content = f"""---
date: {date}
tags:
  - {tag1}
  - {tag2}
  - {tag3}
source: {original_url_or_source}
type: image-breaker-note
---

# {title}

## Overview
[Brief description of what this document is]

## Key Points
- Point 1
- Point 2
- Point 3

## [Main Section]
[Detailed content with subsections]

## Reference
- **Source:** [URL or document name]
- **Extracted:** {date}
"""

# Save to workspace
output_dir = "research/image-breaker-notes"  # Default
# or user-specified: "research/bloodwork", "content/references", etc.

# Write file
filepath = f"{output_dir}/{date}-{slugified-title}.md"
write(filepath, content)

# Sync to Obsidian (using obsidian-sync skill)
exec: python3 skills/obsidian-sync/scripts/sync_to_obsidian.py {filepath} /Users/biohacker/Desktop/Connections ImageBreaker

Tag Assignment

Auto-assign 3 most relevant tags based on content:

Common tags:

  • research - Academic papers, studies, references
  • bloodwork - Lab results, biomarkers, panels
  • nmr - NMR lipid panels specifically
  • cholesterol - Cholesterol and lipid-related
  • peptides - BPC-157, TB-500, etc.
  • supplements - Vitamins, minerals, compounds
  • protocols - Treatment/optimization protocols
  • founders - Business/entrepreneur health content
  • longevity - Anti-aging, healthspan
  • performance - Cognitive/physical optimization
  • training - Exercise, workouts
  • toku - Nattokinase, Toku Flow related

Prioritize specific tags over generic ones.

Output Directories

Default: research/image-breaker-notes/

Content-specific alternatives:

  • Research documents → research/papers/ or research/protocols/
  • Lab results → research/bloodwork/
  • Marketing materials → content/references/
  • Training content → research/training/
  • Business documents → projects/business-docs/

Choose the most appropriate directory based on content type.

Example Usage

User provides Labcorp NMR document URL:

  1. Extract content using web_fetch
  2. Structure into markdown with:
    • Overview of what NMR measures
    • Key reference ranges table
    • Interpretation guide
    • Comparison to standard lipids
  3. Assign tags: bloodwork, nmr, research
  4. Save to research/image-breaker-notes/2026-02-10-nmr-lipid-panel-reference.md
  5. Sync to Obsidian vault at ImageBreaker/2026-02-10-nmr-lipid-panel-reference.md
  6. Report to user with file path and Obsidian link

Best Practices

  • Always extract content first - Use web_fetch or image tool before structuring
  • Create comprehensive notes - Include context, not just raw data
  • Use tables for data - Reference ranges, comparisons, standards
  • Tag intelligently - Maximum 3 tags, most specific/relevant
  • Choose output directory wisely - Match content type to workspace organization
  • Auto-sync by default - User wants notes in Obsidian for cross-referencing
  • Report file location - Give user both workspace and Obsidian paths

Output Message Template

After completing the workflow:

✅ **Document broken down and saved**

📝 **Title:** [Note Title]
📂 **Location:** research/image-breaker-notes/2026-02-10-note-title.md
🔗 **Obsidian:** ImageBreaker/2026-02-10-note-title.md
🏷️  **Tags:** tag1, tag2, tag3

**Sections created:**
- Overview
- Key Points  
- [Main sections listed]
- Reference

The note is now in your Obsidian vault for tagging and cross-referencing.

Integration with Other Skills

Obsidian Sync: Automatically called after note creation
Paper Fetcher: If user provides DOI, use paper-fetcher first, then break down the PDF
Research Automation: Can batch-process multiple documents from research runs