What problem does it solve? Routing AI model requests across multiple providers requires juggling different SDKs, API keys, model IDs, failover logic, and spend controls. This Skill guides setup and operation of Vercel AI Gateway so requests use correct authentication, live model IDs, routing rules, and budget limits without relying on outdated training-data knowledge. ## Core Features & Use Cases - Setup and Authentication: Configure AI Gateway API keys or Vercel OIDC tokens, migrate existing OpenAI or Anthropic SDK integrations by changing base URLs, and run a verified first request. - Routing and Model Selection: Fetch the live /v1/models catalog, choose models by modality, capability, price, or data retention, and configure provider ordering, model fallbacks, prompt caching, BYOK, and timeouts. - Spend and Observability: Set team, project, key, or user budgets via the vercel ai-gateway CLI, query credit balances and generation costs, and debug requests through AI Gateway Logs. - Use Case: A team migrating an existing OpenAI SDK app keeps its client, points the base URL to https://ai-gateway.vercel.sh/v1, swaps in a live provider/model ID, adds a fallback model, and caps spend with a monthly API key budget. ## Quick Start Ask the assistant to add Vercel AI Gateway to your app and make one verified request using a current model from the live model list.