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Model-Selector

为 AI Agent 提供模型选择中间层:通过语义分析判断查询复杂度与成本效率,把任务分为 Elite、Balanced、Basic 三档并给出建议模型,支持 OpenAI、Anthropic、Gemini、DeepSeek 多提供方,并可根据历史查询回写滚动调整意图关键词。

rayray1218
rayray1218
热度 70.16
最近更新 2026-05-11 17:27:24
分类:自动化依赖:内部调用大模型 / 第三方 API / 代码执行应用场景:工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add model-selector
Metadata
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"]

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"}