A comprehensive AI-powered facial transformation suite for analysis, editing, and stylistic modification of portrait images.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install acedatacloud-face-transform
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 acedatacloud-face-transform using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Face Transform is a sophisticated toolkit within the Openclaw Skills ecosystem designed to provide developers with professional-grade facial manipulation capabilities. By leveraging the AceDataCloud API, this skill enables AI agents to perform complex visual tasks such as landmark detection, gender swapping, and age progression through simple programmatic interfaces.
The skill excels at turning static portraits into dynamic assets. Whether you need to detect over 90 precise keypoints for biometric analysis or apply artistic filters like cartoonization, Face Transform offers a synchronous, high-performance solution. It bridges the gap between raw image data and actionable facial intelligence, making it an essential component for modern AI-driven creative workflows.
To integrate Face Transform into your environment, ensure you have your API token ready from AceDataCloud. Configure your environment as follows:
# Set your authentication token
export ACEDATACLOUD_API_TOKEN="your-token-here"
# Test the connection with a face analysis request
curl -X POST https://api.acedata.cloud/face/analyze \
-H "Authorization: Bearer $ACEDATACLOUD_API_TOKEN" \
-H "Content-Type: application/json" \
-d '{"image_url": "https://example.com/portrait.jpg"}'
The skill utilizes a structured JSON schema for both inputs and outputs to ensure compatibility across various Openclaw Skills implementations.
| Data Type | Fields | Description |
|---|---|---|
| Input | image_url, target_image_url |
Source and destination image links |
| Keypoints | nose, mouth, left_eye, contour |
Arrays of {x, y} coordinate objects |
| Results | image_url |
The resulting transformed or beautified image |
| Meta | liveness_score |
Confidence metric for liveness detection |
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