| 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.
