LLM Task Orchestrator — AI skill for Claude Code


Polyphonic Decision Engine

**Polyphonic Decision Engine** is an orchestration layer for large language model routing that transcends simple load balancing. Where typical routers treat LLMs as interchangeable parts, Polyphonic treats each model as a distinct instrument in an ensemble—selecting the right voice for each task based on deep semantic analysis of the request's structure, ambiguity level, novelty, and required reasoning depth.

Built for teams managing complex AI workflows, this system deterministically routes high-volume, pattern-matching tasks to faster models while reserving deeper analytical capacity for ambiguous architectural decisions, refactoring challenges, and creative problem-solving. Every routing decision is fully auditable, with complete provenance tracking from request intake through response delivery.

Overview

Modern software development increasingly depends on multiple AI models, each with unique strengths and weaknesses. The challenge is not merely choosing a model, but orchestrating them with intentionality—ensuring that the right cognitive load reaches the right processing engine.

Polyphonic Decision Engine approaches this challenge through what we call **semantic routing triage**: each incoming request is analyzed across multiple dimensions including structural complexity, domain specificity, novelty coefficient, and ambiguity index. Based on this analysis, the engine directs the request to the optimal model while maintaining a complete, deterministic audit trail of every decision.

The system operates on a fundamental insight: **not all code tasks are created equal**, and treating them as such wastes both resources and cognitive potential. By matching task characteristics to model capabilities, teams achieve higher quality outputs, faster turnaround times, and more predictable resource consumption.

**Key differentiator:** U