llm-router

What This Skill Does

The OpenClaw LLM Router skill serves as a unified gateway for autonomous agents to interact with over 70 state-of-the-art AI models through a single, OpenAI-compatible API interface. Instead of managing dozens of individual API keys for OpenAI, Anthropic, Google, and others, this skill centralizes model access, authentication, and billing. By abstracting the provider layer, it enables developers to treat diverse models as interchangeable components, allowing for seamless model swapping, performance benchmarking, and complex multi-model workflows within their agentic architecture.

Installation

To integrate the LLM Router into your local OpenClaw environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/0xjordansg-yolo/openclaw-aisa-llm-gateway

Once installed, you must configure your environment variable to authenticate requests. Obtain an API key from the AIsa portal and set it locally using:

export AISA_API_KEY="your-key-here"

This configuration ensures that all subsequent calls made by the agent are routed correctly through the gateway.

Use Cases

This skill is designed for high-performance agent workflows. Common use cases include:

• Cost-Effective Routing: Automatically route low-complexity tasks to cheaper models like gpt-4o-mini or gemini-1.5-flash, while reserving premium, high-reasoning models like o1 or claude-3-5-sonnet for complex architectural or logic-heavy tasks.
• Resilience Engineering: Implement automatic fallback strategies. If a request to your primary model times out or returns a failure, the agent can be programmed to retry the request using a different provider (e.g., failing over from GPT-4 to Claude).
• Model Comparison: Execute parallel prompts across multiple families to verify output consistency or evaluate the accuracy of different reasoning engines for specialized coding tasks.

Example Prompts

1. "Use gpt-4o to analyze the attached research paper, then summarize the key findings in three bullet points."
2. "Compare the output of deepseek-r1 and o3-mini regarding the efficiency of this sorting algorithm, explaining which is more effective for high-data scenarios."
3. "If gpt-4-turbo is unavailable, please fallback to claude-3-5-sonnet to rewrite the provided marketing copy for better engagement."

Tips & Limitations

• Token Accounting: Since this skill aggregates multiple providers, monitor your usage via the AIsa dashboard to ensure billing accuracy.
• Latency Considerations: While the gateway is highly optimized, routing through a middleware layer may introduce negligible latency compared to direct provider access. For latency-critical applications, select models hosted in geographic regions closest to your agent's deployment environment.
• Compatibility: Ensure your specific agentic frameworks are configured to support the standard OpenAI chat completions payload, as this is the primary format accepted by the LLM Router.