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

• Provide the user query or task description.
• Run the classification script to analyze complexity.
• 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.