Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Applies AI-based age transformation to portrait photos via the each::sense API. Supports aging, de-aging, baby-to-adult prediction, and multi-step age timelines. Results preserve subject identity while adjusting visible aging characteristics.
Uses a conversational prompt interface with session continuity, so transformations can be refined iteratively without re-uploading the source image.
When to use it
- Visualizing how a baby might look as an adult
- De-aging an actor for a film flashback scene
- Generating age-progression images for missing persons cases
- Creating before/after aging visuals for a skincare campaign
- Previewing personal appearance at 70+ years old
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Age this portrait to look 65 years old
- 1Accepts the source portrait URL and target age from the user
- 2Constructs a prompt specifying target age, aging features, and identity preservation
- 3Sends POST request to sense.eachlabs.run/chat with the image URL and prompt
- 4Streams the response and extracts the output image URL
A photorealistic portrait of the subject appearing 65 years old with wrinkles, gray hair, and mature skin texture
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.