model-escalation

What problem does it solve?

This Skill addresses the challenge of optimizing AI model usage by automatically selecting the most appropriate model (Haiku, Sonnet, or Opus) based on the estimated complexity of a given task, thereby managing API costs and ensuring efficient performance.

Core Features & Use Cases

• Dynamic Model Selection: Automatically switches between Anthropic's Haiku, Sonnet, and Opus models based on task complexity thresholds.
• Prefix Consistency: Enforces and tracks the use of model-specific prefixes ([H], [S], [O]) to ensure alignment between the model and its output.
• Cost Optimization: Reduces API expenses by using less powerful, cheaper models for simpler tasks.
• Use Case: When building a multi-model agent, this Skill ensures that simple chat interactions use Haiku, code-related queries use Sonnet, and complex architectural planning uses Opus, all while maintaining output consistency.

Quick Start

Use the model_escalation_hook_v2 function from Tools.model_escalator_v2 to determine the appropriate model for a given conversation context.