A specialized skill for managing and retrieving realistic AI-generated person headshots for design and development purposes.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install generated-photos-integration
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install generated-photos-integration using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Generated Photos?
Generated Photos is a powerful integration designed to provide high-quality, AI-generated headshots of diverse individuals. This skill allows developers and designers to bypass the complexities of traditional stock photography by generating realistic faces that can be filtered by age, gender, and ethnicity.
By leveraging the Membrane framework, this Openclaw Skills contribution ensures that AI agents can programmatically access a vast library of synthetic media. It is particularly valuable for creating inclusive user interfaces, realistic mockups, and dynamic profile data without the legal hurdles of using real human likenesses.
Generated Photos Use Cases
- Populating UI mockups and prototypes with diverse, high-quality user avatars.
- Automating the generation of profile pictures for testing environments and staging databases.
- Researching and filtering specific demographic headshots for marketing and design projects.
- Enhancing AI agent capabilities to provide visual personae in chat or creative applications.
How Generated Photos Works
- The agent initializes the skill using the Membrane CLI and authenticates via a secure tenant-based login.
- A connection to the Generated Photos API is established and verified, with Membrane managing all OAuth or API key persistence.
- The agent searches for specific actions (like getting a random face or listing faces) using natural language intent.
- Parameters such as age, ethnicity, or gender are passed to the action to refine the image search results.
- The skill returns a structured response containing image URLs and metadata, which the agent can then display or process.
Generated Photos Setup
To begin using this integration with Openclaw Skills, install the Membrane CLI and authenticate your environment:
npm install -g @membranehq/cli@latest
membrane login --tenant --clientName=openclaw
Ensure the connection to Generated Photos is active:
membrane connection ensure "https://generated.photos/" --json
Generated Photos Data Schema & Taxonomy
The skill organizes data primarily around the Person entity and its associated Image metadata. Use the following table to understand the response structure:
| Object | Fields | Description |
|---|---|---|
| Person | id, age, gender, ethnicity | Core demographic data for the generated individual. |
| Image | url, thumb_url, meta | Links to the hosted AI image and its technical specifications. |
| Search Result | faces[], total, page | A collection of face objects returned from a list query. |
Generated Photos Advanced Features
- Direct Proxy Requests: Use
membrane requestto access the full Generated Photos API surface beyond pre-built actions. - Automated Credential Refresh: Background handling of authentication tokens so agents never lose access during long-running tasks.
- Natural Language Action Discovery: Find the exact endpoint needed by describing your goal rather than memorizing API documentation.
- Multi-Agent Support: Compatible with various agent types including openclaw, claude, and windsurf for cross-platform tool usage.
SKILL.md
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