Guides end-to-end Wren Engine setup from environment checks to first query.
npx skills add https://github.com/Canner/wren-engine --skill wren-onboarding
Please help me install this Agent Skill. Skill: wren-onboarding Source: https://github.com/Canner/wren-engine/tree/main/skills/wren-onboarding Command: npx skills add https://github.com/Canner/wren-engine --skill wren-onboarding
Setting up Wren Engine involves many ordered steps—environment checks, project scaffolding, connection configuration, and MDL generation—and doing them out of order or exposing credentials in chat causes failures. This Skill walks an AI agent through the entire onboarding flow one step at a time with strict safety rules.
.env templates by introspecting the live connector schema via wren docs connection-info, so credentials never pass through chat.wren-generate-mdl, wren-usage, wren-dlt-connector) at the right handoff points, and surfaces the official troubleshooting playbook on errors..env template, creates the connection profile, hands off to MDL generation, and finishes with suggested natural-language questions.Ask the agent to install Wren Engine and connect your database by saying "set up wren engine" or invoking /wren-onboarding.
High-intent search queries and answers about installing and using this skill.
Run the wren-onboarding skill, which checks your Python environment, scaffolds a project with wren context init, generates a .env template from the connector schema, and creates a connection profile with wren profile add. It then hands off to MDL generation before your first query.
Credentials are never entered in chat. The skill generates a .env file with empty fields based on wren docs connection-info output, you fill in values in your editor, and the connection profile references them as ${VAR} placeholders.
Supported datasources include postgres, mysql, bigquery, snowflake, clickhouse, trino, and duckdb. Run wren docs connection-info with no argument to see the full list introspected from the live connector schema.
Queries fail if MDL has not been built yet, since tables not in the MDL cannot be queried. Run the wren-generate-mdl skill first, then wren context validate and wren context build before querying.
Wren Engine requires Python 3.11 or newer. The onboarding preflight checks python3 --version first and stops with an upgrade request if the version is older.
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