Model-Selector

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name: Semantic Model Orchestrator description: A powerful model routing skill that analyzes query intent and cost-efficiency to select the optimal LLM (Elite/Balanced/Basic) before execution. version: 1.0.0 author: Ray tags: [llm-ops, routing, efficiency, selection]

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Semantic Model Orchestrator

This skill provides an intelligent middle layer for AI agents to decide which model tier should handle a specific task. By using semantic analysis, it categorized queries into Elite, Balanced, or Basic levels.

Features

Semantic Intent Recognition: Uses vector embeddings to detect query complexity.

Cost-Efficiency Orchestration: Routes queries to Elite, Balanced, or Basic models.

ClawHub Optimized: Default tiers for Claude 3.5 Sonnet, GPT-4o-mini, and DeepSeek.

Rolling Adjustment: Built-in logic to refine intent keywords from user history.

Multi-Provider Support: Supports OpenAI, Anthropic, Gemini, and DeepSeek.

Model Tiers

Elite: anthropic/claude-3-5-sonnet-latest

Balanced: openai/gpt-4o-mini

Basic: deepseek/deepseek-chat

Usage

Add this skill to your agent's capability list. The agent will call the get_optimal_model tool before making main LLM calls to optimize performance and budget.

Example Tool Call

result = router.analyze_and_route("Design a high-scalable microservices architecture for a fintech app.")
Returns: {"tier": "ELITE", "suggested_model": "anthropic/claude-3-5-sonnet-latest"}

Add this skill to your agent's capability list. The agent will call the get_optimal_model tool before making main LLM calls to optimize performance and budget.

Example Tool Call

result = router.analyze_and_route("Design a high-scalable microservices architecture for a fintech app.")
Returns: {"tier": "ELITE", "suggested_model": "anthropic/claude-3-5-sonnet-latest"}