A command-line tool that uses AI to apply exaggerated anime-style facial expressions to portrait photos while preserving original details.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ai-ahegao-ai-cli-skill
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install ai-ahegao-ai-cli-skill using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The WeShop AI Ahegao skill is a specialized image transformation tool designed to modify portrait photography into stylized anime-inspired expressions. As part of the Openclaw Skills ecosystem, it provides a bridge between standard photo assets and stylized artistic outputs by leveraging advanced facial modification algorithms.
This skill is particularly valuable for creators and developers looking to automate the application of specific facial expressions without manually editing images. It maintains the integrity of the original subject's pose, hair, and outfit, focusing exclusively on the facial transformation to ensure a consistent look and feel across processed assets.
To get started with this skill, ensure you have the weshop-cli installed globally via npm. You will also need an API key from the official WeShop portal.
npm install -g weshop-cli
# Set your API key as an environment variable
export WESHOP_API_KEY='your_api_key_here'
# Verify installation
weshop --version
The skill produces a structured JSON output following each execution to facilitate automation within Openclaw Skills workflows.
| Attribute | Type | Description |
|---|---|---|
| agent | string | Identifies the specific tool used (ai-ahegao-ai) |
| executionId | string | Unique identifier for the specific API task |
| status | string | Indicates success or failure of the transformation |
| imageCount | integer | Number of images generated in the request |
| image[n].url | string | The remote URL where the processed image is hosted |
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