xiaolongxia-assistant

What This Skill Does

The xiaolongxia-assistant acts as your dedicated OpenClaw plugin engineering companion. Its primary mission is to streamline the development lifecycle of OpenClaw extensions, taking you from a conceptual idea to a functional, distributable plugin in minimal time. The skill evaluates your project requirements to determine whether you should implement a simple Prompt-based Skill or a fully-featured Node.js-based Plugin. Once the architecture is decided, it automatically scaffolds the necessary boilerplate, including package.json, openclaw.plugin.json, and core source files, ensuring all dependencies and metadata follow best practices.

Installation

To integrate this assistant into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/boleyn/claw-skills

Use Cases

• Rapid Prototyping: Quickly bootstrap a new plugin when you need external API integration or custom tool execution.
• Architecture Guidance: Receive expert advice on choosing between lightweight prompt-skills and heavy-duty programmatic plugins.
• Debugging Lifecycle: Troubleshoot deployment issues or runtime errors in local development environments using standardized diagnostic steps.
• Publishing Workflow: Generate automated build and release manifests to ensure your plugins meet OpenClaw ecosystem standards.

Example Prompts

1. "I want to build a tool that fetches stock prices and displays them in the chat. Should I make a Skill or a Plugin? Please generate the skeleton."
2. "My plugin is throwing a 403 error during local debugging. Help me troubleshoot the manifest and environment configuration."
3. "I have finished my logic. How do I generate the production build and what is the command to publish it to the registry?"

Tips & Limitations

• Best Practices: Always check the openclaw.plugin.json schema after generation to ensure your plugin capabilities are explicitly defined.
• Environment: Ensure you have Node.js 18+ installed to run the generated plugin skeletons effectively.
• Limitations: The assistant focuses on scaffolding and orchestration; it does not replace the need to write the core functional logic of your specific tools. Always verify code execution permissions within your local container settings.