Neo Smart Router

What This Skill Does

The Neo Smart Router is a highly optimized, rule-based dispatching engine for the OpenClaw platform. It acts as a specialized traffic controller for incoming requests, employing a sophisticated three-layer architecture to ensure that your text content is processed using the most efficient compression strategy without wasting unnecessary LLM tokens. By using a "Fast Sniffing" layer, the tool automatically categorizes your input—whether it is technical documentation, project logs, philosophical theories, or daily conversation—and routes it to one of three optimized modes: ⚡️ Lingdong (Dynamic), 📋 Structural, or 🧠 Depth (Lossless). This allows users to maintain high-quality communication while minimizing the resource footprint of every interaction.

Installation

To install this skill into your OpenClaw agent, use the command-line interface within your terminal. Ensure your agent environment is properly authenticated, then execute the following command:

clawhub install openclaw/skills/skills/largetool/neo-smart-router

Once the command finishes, the router will automatically register its trigger keywords (/compress, /4d, and 开始压缩) into your agent's available toolset.

Use Cases

• Project Management: Automatically compress long, messy project logs or meeting minutes into structured "Structural Mode" summaries to keep your team aligned.
• Technical Documentation: Condense complex architecture files or system logs into readable formats that retain key data points while discarding fluff.
• Daily Communication: Use "Dynamic Mode" to keep casual chats or emotive reflections concise and to the point, ensuring faster response times.
• Knowledge Management: Use "Depth Mode" for deep-dive research or complex theoretical study, ensuring no critical semantic data is lost during the compression process.

Example Prompts

1. "/compress Please refine these meeting notes: [Paste long text here]"
2. "/4d Here is the architecture doc for the project, make it concise."
3. "开始压缩 既然你认为这个信念有问题，请详细说明为什么并提出替代方案。"

Tips & Limitations

• Token Efficiency: Because the router uses a regex-based rule-matching engine rather than an LLM for classification, classification time is near-instant and carries zero additional token costs.
• Rule Updates: The behavior is defined by sniff-rules.json. If you find the router consistently misclassifies your documents, you can tune the keywords list in the configuration file to better match your specific usage patterns.
• Limitation: The current version is optimized for mixed-content text. Highly cryptic or unstructured poetic prose may default to the 'Depth' mode as a safety fallback to ensure integrity.