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

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.