Cost Optimization Skill

What problem does it solve?

Reduces the cost of running large language models by intelligently routing requests to cost-effective models while preserving required quality and latency targets.

Core Features & Use Cases

• Cost-aware routing: selects the most economical model candidates without compromising quality.
• MCP-driven tooling: exposes estimate_cost, find_cheapest_model, and get_pricing to enable cost optimization workflows.
• Use Case: in a multi-model deployment, route user requests to minimize spend while meeting defined quality thresholds and latency budgets.

Quick Start

Route a 1000-token prompt to the cheapest model that maintains target quality.