wren-dlt-connector
wren-dlt-connector
Connect SaaS data to Wren Engine for SQL analysis — from zero to a verified, queryable project in one conversation.
Who this is for
Data analysts who know SQL and some Python, but may not have used dlt or Wren before. Explain concepts briefly when they first appear, but don't over-explain things a SQL-literate person would already know.
Overview
This skill walks through a four-phase workflow:
- Extract — Use dlt (data load tool) to pull data from a SaaS API into a local DuckDB file
- Model — Introspect the DuckDB schema and auto-generate a Wren semantic project (YAML models, relationships, profile)
- Build & Verify — Build the project and run actual SQL queries to confirm everything works end-to-end
- Handoff — Show the user their data and next steps
The user might enter at any phase. Ask which phase they're starting from — they may already have a .duckdb file and just need phases 2–4.
More from canner/wrenai
wren-generate-mdl
Generate a Wren MDL project by exploring a database with available tools (SQLAlchemy, database drivers, MCP connectors, or raw SQL). Guides agents through schema discovery, type normalization, and MDL YAML generation using the wren CLI. Use when: user wants to create or set up a new MDL, onboard a new data source, or scaffold a project from an existing database.
40wren-onboarding
Onboard a user to Wren Engine end-to-end. Walks through environment checks, project scaffolding, connection configuration via .env, and first query. Use when: user wants to install Wren Engine, set up a new data source connection, or bootstrap a new project from scratch. Triggers: '/wren-onboarding', 'install wren', 'set up wren engine', 'wren onboarding', 'connect new database to wren'.
39wren-usage
Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.
39