By 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
- 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.