What problem does it solve? Setting up Wren Engine from scratch involves many ordered steps—environment checks, CLI installation, credential configuration, profile creation, and MDL generation—and doing them out of order causes confusing failures. This Skill walks an AI agent through the entire onboarding flow one step at a time, enforcing safe rules like never asking for credentials in chat. ## Core Features & Use Cases - Guided Environment Preflight: Checks Python version, virtualenv status, and existing CLI installation before any project work begins. - Credential-Safe Connection Setup: Generates a .env template introspected from the live connector schema via wren docs connection-info, so secrets never pass through the chat. - Project Scaffolding and Binding: Creates the project layout with wren context init, binds a validated connection profile, and hands off to MDL generation before any query runs. - Use Case: A user says "set up Wren Engine and connect my Postgres database." The agent checks the environment, scaffolds the project, generates the .env template, validates the connection profile, builds the MDL, and finishes with suggested natural-language questions. ## Quick Start Ask your agent to run the Wren onboarding flow by saying "set up Wren Engine and connect my database" or invoking /wren-onboarding.
