model-intel

What This Skill Does

The Model Intel skill acts as a comprehensive analytical bridge between OpenClaw and the OpenRouter API ecosystem. It provides real-time, granular intelligence on over 200+ Large Language Models. Instead of guessing which model fits your current budget or technical requirement, Model Intel allows the agent to fetch live data on pricing, context window limits, and specific capabilities. Whether you are building an automated pipeline that needs the most cost-effective reasoning engine or a user looking for the fastest model for image analysis, this skill provides the metadata necessary for data-driven decisions.

Installation

To integrate this intelligence suite into your OpenClaw environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/aiwithabidi/model-intel

Ensure your environment has appropriate network permissions to reach the OpenRouter API endpoints, as the tool relies on external API calls to keep the model database synchronized with the latest provider updates.

Use Cases

• Budget Optimization: Automatically query the lowest-cost models for high-volume tasks.
• Technical Auditing: Verify current context lengths for models like Claude 3.5 or GPT-4o before processing long-form documentation.
• Capability Matching: Use the best command to retrieve the current industry leaders for specific domains such as coding, vision, or logical reasoning.
• Competitive Comparison: Perform side-by-side evaluations of different models to justify infrastructure changes or model migration within your AI stack.

Example Prompts

1. "OpenClaw, compare the current pricing of Claude-3.5-Sonnet against GPT-4o and tell me which is cheaper for a 100k token context window."
2. "I need a fast model for a simple classification task, what does the model-intel skill suggest for high-speed, low-cost inference?"
3. "Search for the best vision models currently available on OpenRouter that support complex image analysis."

Tips & Limitations

• API Dependencies: This skill fetches live data; if OpenRouter is unreachable, the skill may return cached or stale data depending on the implementation version.
• Interpretation: While the skill provides data, 'best' is often subjective; use the tool to filter candidates, then test with your specific prompt inputs.
• Data Freshness: Always run the list command if you haven't queried the tool in a few days to ensure you are seeing the most recent arrivals in the LLM landscape.