A specialized model routing and provider configuration tool designed to simplify access to global and Chinese LLMs via AIsa.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install llm-router
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 llm-router 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 LLM Router?
The LLM Router is a technical skill built to streamline model routing, provider setup, and access to Chinese Large Language Models (LLMs). By functioning as a central hub for configuration, it allows developers to manage diverse provider paths and routing workflows without manual complexity. Integrating this tool into your Openclaw Skills library ensures that your AI agents can fluently switch between models and providers, including specialized AIsa-hosted model workflows and high-performance Chinese-specific runtimes.
LLM Router Use Cases
- Establishing a dedicated AIsa provider path for custom workflows.
- Investigating supported models and routing options for specific analytical tasks.
- Preparing a localized runtime for seamless Chinese LLM access.
- Centralizing provider configuration for multi-model AI environments.
How LLM Router Works
- The system verifies the environment for the required AISA_API_KEY to ensure authenticated access.
- Users invoke the Python client located in the scripts directory to interact with the routing logic.
- The skill analyzes the request to determine if a specific model (such as Qwen) or a general provider path is needed.
- It configures the runtime environment and selects the optimal routing path based on the user's intent.
- The routed model becomes available for operations, providing direct access to the requested LLM features.
LLM Router Setup
To get started with this skill, ensure you have Python 3 installed. You will need to export your AIsa credentials to your environment.
export AISA_API_KEY="your_key_here"
python3 scripts/llm_router_client.py --help
Always use repo-relative paths for scripts and prefer explicit CLI authentication flags when interacting with the client.
LLM Router Data Schema & Taxonomy
The LLM Router organizes its data through environment variables and local script execution. The following schema defines the core data components:
| Component | Type | Description |
|---|---|---|
| AISA_API_KEY | Environment Variable | Required key for authenticating with AIsa-backed APIs. |
| scripts/ | Directory | Contains the core Python implementation for model routing. |
| model_routing_table | Logic | Internal mapping of supported models and provider paths. |
| routing_options | Metadata | Dynamic list of available configurations for Chinese-specific LLMs. |
LLM Router Advanced Features
- Specialized support for Chinese long-form analysis through routed Chinese LLMs.
- Compatibility with multiple AI coding agents including openclaw, claude-code, and hermes.
- Explicit CLI auth flag integration for secure, non-interactive environments.
- Automated setup guidance for AIsa-hosted model workflows.
SKILL.md
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