dynamic-model-selector

# 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.