eval-models

Run the user's own examples against several AI models (Claude, Gemini, OpenAI, or any OpenAI-compatible endpoint including local Ollama or vLLM) and measure pass rate, latency, and billed cost to find the cheapest model that meets their quality bar. Use whenever the user wants to test, benchmark, evaluate, or prove which model works for their task, asks "is the cheaper model good enough", wants evidence before switching models, or has a shortlist from find-model to validate, even if they don't say "eval". Generates a config, runs a standard-library Python script with the user's keys from environment variables, and writes results.json plus a summary.