Image Breaker
/install image-breaker
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, referencesbloodwork- Lab results, biomarkers, panelsnmr- NMR lipid panels specificallycholesterol- Cholesterol and lipid-relatedpeptides- BPC-157, TB-500, etc.supplements- Vitamins, minerals, compoundsprotocols- Treatment/optimization protocolsfounders- Business/entrepreneur health contentlongevity- Anti-aging, healthspanperformance- Cognitive/physical optimizationtraining- Exercise, workoutstoku- Nattokinase, Toku Flow related
Prioritize specific tags over generic ones.
Output Directories
Default: research/image-breaker-notes/
Content-specific alternatives:
- Research documents →
research/papers/orresearch/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:
- Extract content using
web_fetch - Structure into markdown with:
- Overview of what NMR measures
- Key reference ranges table
- Interpretation guide
- Comparison to standard lipids
- Assign tags:
bloodwork,nmr,research - Save to
research/image-breaker-notes/2026-02-10-nmr-lipid-panel-reference.md - Sync to Obsidian vault at
ImageBreaker/2026-02-10-nmr-lipid-panel-reference.md - 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
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install image-breaker - 安装完成后,直接呼叫该 Skill 的名称或使用
/image-breaker触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Image Breaker 是什么?
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... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 267 次。
如何安装 Image Breaker?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install image-breaker」即可一键安装,无需额外配置。
Image Breaker 是免费的吗?
是的,Image Breaker 完全免费(开源免费),可自由下载、安装和使用。
Image Breaker 支持哪些平台?
Image Breaker 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Image Breaker?
由 biohackerrrrrr(@biohackerrrrrr)开发并维护,当前版本 v1.0.0。