A precision utility designed to surgically extract pure photographs from Instagram mobile screenshots by detecting dark mode interface signatures.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ig-cropper
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ig-cropper using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is IG Cropper?
IG Cropper is a specialized automation tool tailored for designers, architects, and visual researchers who rely on Instagram for inspiration. It solves the common problem of cluttered mobile screenshots by identifying the specific RGB signature of Instagram's dark mode to isolate the core imagery. As part of the wider ecosystem of Openclaw Skills, this tool ensures that your reference archives remain aesthetically consistent and free from distracting UI elements like status bars and navigation icons.
By focusing on the technical signature of the platform's interface, IG Cropper provides a reliable way to build high-quality visual libraries. It prioritizes the integrity of the original photograph, making it an essential utility for anyone looking to streamline their creative research workflow using Openclaw Skills.
IG Cropper Use Cases
- Creating clean mood boards for architectural and interior design projects.
- Automating the extraction of visual assets from mobile screenshots for research papers.
- Building distraction-free reference libraries for professional design teams.
- Integrating automated image curation into personal Openclaw Skills workflows.
How IG Cropper Works
- The utility loads the target Instagram dark mode screenshot using the Pillow image processing library.
- It executes a row-by-row scan of the image to identify the specific interface background color: RGB (12, 15, 20).
- The algorithm identifies the largest continuous block of non-background pixels, which represents the actual photograph.
- It calculates the precise coordinates of the image frame and crops the screenshot to produce a clean, standalone file.
IG Cropper Setup
To get started with this tool in your Openclaw Skills environment, ensure you have Python 3 and the Pillow library installed:
pip install pillow
Execute the script via the command line by providing the input screenshot and the desired output path:
python3 scripts/ig_crop.py input_screenshot.png output_pure_photo.png
IG Cropper Data Schema & Taxonomy
The skill follows a straightforward input-output data model optimized for visual asset management:
| Attribute | Specification |
|---|---|
| Input Format | Instagram Mobile Screenshot (Dark Mode) |
| Signature Color | RGB (12, 15, 20) |
| Output Format | Cleaned PNG/JPG photograph |
| Processing | Non-destructive pixel extraction |
IG Cropper Advanced Features
- Adaptive coordinate detection that handles various scroll depths automatically.
- Preservation of architectural textures by avoiding destructive AI in-painting.
- Lightweight Python implementation for easy integration into complex Openclaw Skills automation pipelines.
- Precision cropping that maintains the original resolution of the captured photo.
SKILL.md
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