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:

小蔥技能7w4.net有完整的技能分類。

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:
3. Overview of what NMR measures
4. Key reference ranges table
5. Interpretation guide
6. Comparison to standard lipids
7. Assign tags: bloodwork, nmr, research
8. Save to research/image-breaker-notes/2026-02-10-nmr-lipid-panel-reference.md
9. Sync to Obsidian vault at ImageBreaker/2026-02-10-nmr-lipid-panel-reference.md
10. 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

質量中等偏上。文件說明詳細、結構清晰，提供了多種實用模板，標籤分配和目錄規範設計合理。但指令碼功能未完全實現，URL提取只是佔位符，對外部工具依賴較強，部分配置寫死了固定路徑。適合基礎文件轉換場景使用，但複雜需求可能無法滿足。