dynamic-model-selector

What This Skill Does

The Dynamic Model Selector acts as an intelligent router for your OpenClaw AI environment. Instead of manually choosing a model for every interaction, this skill automatically evaluates incoming prompts based on complexity, intent, and resource requirements. It effectively bridges the gap between high-performance reasoning engines like GPT-4o or Claude 3.5 Sonnet and lightweight, rapid-response models such as Grok-code-fast. By analyzing keywords, sentence structure, and task categories, the skill optimizes for the best balance of latency, cost-efficiency, and accuracy.

Installation

To integrate this skill into your environment, run the following command in your terminal: clawhub install openclaw/skills/skills/mpelissari/dynamic-model-selector Ensure that you have your GitHub Copilot credentials properly configured within your environment variables, as the tool relies on accessing these endpoints to route requests effectively.

Use Cases

This skill is perfect for power users who want to maximize their tokens and response speed. Ideal scenarios include:

• Development Workflows: Automatically switching to a code-optimized model when you start typing a function, but reverting to a general assistant for PR descriptions.
• Cost Management: Prioritizing free or low-cost models for simple conversational queries to keep your usage metrics low.
• Complex Research: Automatically triggering advanced, high-reasoning models when the tool detects a request involving deep data analysis or multi-step logical deduction.

Example Prompts

1. "Analyze this massive JSON file and tell me which field causes the most errors."
2. "Explain the basic concept of recursion in under three sentences."
3. "Write a custom Python decorator that logs function execution time and adds a retry mechanism."

Tips & Limitations

The Dynamic Model Selector is a heuristic-based engine. While highly effective, it may occasionally misclassify highly nuanced tasks. If you find the model recommendation is not meeting your needs, you can override the selection manually. Always review the models.md reference file to understand the specific capabilities and trade-offs of the models available in your current GitHub Copilot subscription. Note that this skill does not execute code itself; it purely functions as a decision-making layer, keeping your interaction pipeline efficient and cost-aware.