routing

# 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 s...