Style Transfer
ListedThis Skill transforms images into different artistic styles, offering creative visual variations and enhancing design possibilities.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add eachlabs/skills --skill style-transfer -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
eachlabs
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.
No undeclared network calls: failed
Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: eachsense-agent.core.eachlabs.run.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
Hosts contacted
eachsense-agent.core.eachlabs.runundeclaredWhat it found (3 of 17)
- skills/style-transfer/SKILL.md:25contacts eachsense-agent.core.eachlabs.run
curl -X POST https://eachsense-agent.core.eachlabs.run/v1/chat/completions \ - skills/style-transfer/SKILL.md:56contacts eachsense-agent.core.eachlabs.run
curl -X POST https://eachsense-agent.core.eachlabs.run/v1/chat/completions \ - skills/style-transfer/SKILL.md:74contacts eachsense-agent.core.eachlabs.run
curl -X POST https://eachsense-agent.core.eachlabs.run/v1/chat/completions \
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned eachlabs/skills at a881258627.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- a881258627
- Manifest
- skills/style-transfer/SKILL.md
- Scanned
- 2 files, 784 lines
About this skill
What it does
The style-transfer skill allows you to apply artistic styles from one image to another. It can transform photographs into paintings, sketches, or other stylized representations by transferring the visual characteristics of a style image onto your input image. This enables creative manipulation and aesthetic enhancement of images using AI.
When to use it
- Artistic Creation: Generate unique artwork based on existing photos by applying various artistic styles.
- Image Enhancement: Give ordinary photographs an interesting or professional look for social media or presentations.
- Experimentation: Explore different visual aesthetics and see how a style image can transform the appearance of another.
- Creative Prototyping: Quickly visualize design concepts by applying stylistic elements to mockups or prototypes.
Key capabilities
- Style transfer from reference images
- Application of artistic styles
- Image manipulation based on visual characteristics
Example prompts
- "Apply the style of Van Gogh's 'Starry Night' to this photo."
- "Transform this image into a watercolor painting."
- "Make this picture look like a pencil sketch."
Tips & gotchas
The quality of the output depends heavily on the chosen style image; experiment with different styles for best results. Complex or noisy images may produce less predictable outcomes.