routing

name	routing
description	Route tasks to the cheapest capable model automatically via the llm-router MCP tools

LLM Router — Smart Routing Skill

Route tasks to the cheapest capable model automatically using llm-router MCP tools.

When to Use This Skill

Before answering research, code, writing, or analysis tasks — call the appropriate llm-router tool instead of answering directly. The router picks the cheapest model that can handle the task (Ollama → Codex → paid APIs in free-first order).

Task → Tool Mapping

Task type	Tool to call	Why
Simple factual question	llm_query	Gemini Flash / Groq — 50× cheaper than o3
Research / current events	llm_research	Perplexity (web-grounded, not stale)
Writing / summaries / brainstorm	llm_generate	Gemini Flash / Haiku
Deep analysis / debugging	llm_analyze	GPT-4o / Gemini Pro
Code generation / refactoring	llm_code	Ollama → Codex built-in → o3
Don't know which type	llm_auto	Auto-classifies + routes, tracks savings

How to Call

llm_query(prompt="What is the capital of France?")
llm_code(prompt="Refactor this function to use async/await", complexity="moderate")
llm_research(prompt="What changed in Python 3.13?")
llm_auto(prompt="<the full user request>")   # safest default

When NOT to Route

• File read/write/edit operations — execute directly
• Inline tool calls where you have the answer already
• Tasks under 5 words (likely follow-ups, not standalone requests)

Cost Impact

Routing simple tasks to Gemini Flash instead of o3 saves ~50–100×. llm_auto shows cumulative savings every 5 calls automatically. Run llm_savings anytime to see your totals.