# wren

> Provides a discovery stub for the Wren CLI, a semantic SQL layer over 22+ databases, with commands to install, set up, connect data sources, generate MDL projects, enrich context, and deploy GenBI dashboards.

- Skill: `gabrielmoreira/wren` (Agent Skill)
- Install (CLI): `npx skillmds add gabrielmoreira/wren`
- Raw SKILL.md: https://api.skillmd.com/api/skills/gabrielmoreira/wren/raw
- Safety review: CAUTION (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics, ETL & Pipelines, SQL & Databases
- Tags: Database, Dlt, Etl, Genbi, Mdl, Sql, Wren
- License: Apache-2.0
- Author: gabrielmoreira (https://skillmd.com/u/gabrielmoreira)
- Updated: 2026-08-22
- Page: https://skillmd.com/skills/gabrielmoreira/wren

---


# Wren CLI

This is a discovery stub. The actual workflow guides and prompt helpers
live inside the `wren` CLI itself, so they always match the installed
wrenai version (no skill cache, no version drift).

Install: `pip install wrenai`.

## Workflow guides

```bash
wren skills list                        # all available workflow guides
wren skills get onboarding              # set up Wren end-to-end
wren skills get usage                   # day-to-day querying
wren skills get generate-mdl            # generate MDL from a database schema
wren skills get dlt-connector           # connect SaaS sources via dlt
wren skills get enrich-context          # add business context (units, enums, cubes)
wren skills get genbi                   # build & deploy a shareable GenBI web app
# add --full to include the skill's reference docs
# add --script <name> to fetch a bundled script (e.g. dlt-connector / introspect_dlt)
```

## Reference docs

Full reference docs live on the web: <https://github.com/Canner/WrenAI/tree/main/docs/core>

```bash
wren docs connection-info <ds>          # required + optional connection fields for a data source
```

## Prompt enhancement (wraps a user question for an agent)

```bash
wren ask "<question>" --guided          # for weaker LLMs (strict task flow)
wren ask "<question>" --direct          # for stronger LLMs (minimal wrapping)
```

## Day-to-day data commands (not a sub-app — top-level)

```bash
wren --sql '...'                        # execute SQL through the MDL layer
wren query --sql '...'                  # same, explicit
wren dry-plan --sql '...'               # transpile only, no DB hit
wren context show / build / validate    # project / MDL lifecycle
wren profile add / list / switch        # named connection profiles
wren memory index / recall / store      # semantic memory (needs `[memory]` extra)
```

Run `wren --help` for the full surface; load the matching `wren skills get
<name>` guide before driving any multi-step workflow.