A professional integration for managing content monetization, audience segments, and membership rules through the Membrane framework.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install poool
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 poool using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Poool is a leading subscription and membership platform designed for online publishers and content creators. It provides the tools necessary to build audience relationships and monetize content via sophisticated paywalls and registration walls. By integrating Poool with Openclaw Skills, developers can leverage an AI-driven workflow to manage complex subscription data and audience interactions without manually handling API authentication.
This skill utilizes the Membrane framework to bridge the gap between AI agents and Poool's capabilities. It focuses on reducing token consumption and enhancing security by managing credentials server-side. Whether you are managing user segments, rules, or A/B tests, this Openclaw Skills compatible tool streamlines the entire process through high-level action abstractions.
Install the required CLI globally to enable interaction with Openclaw Skills:
npm install -g @membranehq/cli@latest
Log in to your tenant and specify your agent type to optimize tooling:
membrane login --tenant --clientName=openclaw
Establish the API connection without handling raw secret keys:
membrane connect --connectorKey poool
| Data Component | Description |
|---|---|
| Audiences | Metadata and records for individual users and subscriber groups. |
| Rules | Logic-based triggers for paywalls and registration walls. |
| Segments | Categorized user groups based on behavior or subscription status. |
| Experiences | Frontend configurations for how users interact with walls. |
| A/B Tests | Experimental data comparing different monetization strategies. |
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