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Dynamic Model Selector

该 Skill 分析用户查询的复杂度与任务类型，结合性能、成本与可用性，从 GitHub Copilot 的模型选项中给出推荐，并附带任务分类脚本与模型参考清单。适用于需要在免费与付费模型之间做选择或希望自动路由模型的场景。

mpelissari
mpelissari
热度 81.00
最近更新 2026-05-11 15:54:46
分类：自动化依赖：代码执行 / 读写文件应用场景：推荐 / 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 dynamic-model-selector
Metadata
name
dynamic-model-selector
description
Dynamically select the best AI model for a task based on complexity, cost, and availability in GitHub Copilot. Use when deciding between free/paid models, or when you want automatic model routing based on query analysis.

Dynamic Model Selector

Overview

This skill analyzes user queries to recommend the optimal AI model from available GitHub Copilot options, balancing performance, cost, and task requirements.

How to Use

  1. Provide the user query or task description.
  2. Run the classification script to analyze complexity.
  3. Choose the suggested model or adjust based on preferences.

Classification Criteria

  • Simple tasks (short responses, basic chat): Use faster, free models like grok-code-fast-1.
  • Complex reasoning (analysis, multi-step): Use advanced models like gpt-4o or claude-3.5-sonnet.
  • Code generation: Prefer code-optimized models.
  • Cost sensitivity: Favor free models when possible.

Example Usage

For a query like "Explain quantum computing": Classify as medium complexity -> Recommend gpt-4o.

For "Write a Python function to sort a list": Classify as code task -> Recommend grok-code-fast-1.

Resources

scripts/

  • classify_task.py: Analyzes the query and outputs model recommendation.

references/

  • models.md: Detailed list of available models, pros/cons, costs.