caidish/klayoutclaw/image
Claude Code and agent skill by caidish/klayoutclaw
- community
Checking that the SKILL.md file is still in the repository.
Load a reference image (microscope photo, optical image, SEM) into KLayout as a background overlay for design alignment. Use this skill whenever the user wants to load an image, add a background image, overlay a microscope photo, import a reference picture, align to a photo, or trace over an image. Also trigger when the user says "load this image", "use this photo as reference", "overlay the microscope image", or needs to position/scale/remove background images.
Install
npx vskill@latest install caidish/klayoutclaw/imageSKILL.md
KLayout Image Overlay
Load reference images (JPG, PNG, BMP) into KLayout as background overlays for aligning device geometry to real microscope photos.
Prerequisites
- KLayout running with KlayoutClaw plugin (v0.5+)
- A layout must be open (use
create_layoutfirst if needed)
Scripts
add_image.py — Load an image as background overlay
filepath— Path to image file (JPG, PNG, BMP)--pixel-size— Microns per pixel (default: 1.0)--scale-bar— Derive pixel size from a scale bar:<length_um> <length_pixels>. Takes priority over--pixel-size.--x,--y— Position offset in microns (default: 0, 0)--center— Center the image at the given position (default: image corner at position)
Example — set pixel size directly:
Example — derive pixel size from a 20 um scale bar that spans 153 pixels:
Example — load and center at a specific position:
list_images.py — List all background images in the view
Prints a table of all loaded images with their ID, filename, position, and visibility.
remove_image.py — Remove a background image
image_id— Numeric ID of the image to remove (fromlist_images.py)all— Remove all background images
Workflow
- Load a microscope image as reference background
- Use geometry scripts to draw device features (contacts, gates, mesa) on top
- Adjust pixel-size to match the image's physical scale (check the scale bar)
- Use
list_images.pyto see loaded images,remove_image.pyto clean up
Estimating pixel-size
If the image has a scale bar of length S microns spanning P pixels:
For example, a 20 um scale bar that spans 200 pixels gives pixel-size = 0.1.
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/image/SKILL.md
Popularity
- Repository stars
- 39
- Repository forks
- 7
- 7-day trend score
- 23
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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