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Databases · Data Analysis / AGENT SKILL
wren
0
Use Wren CLI for semantic SQL analytics, database and SaaS connections, business context modeling, and shareable dashboards.
Wren CLI for AI agents — a semantic SQL layer over 22+ databases (Postgres, MySQL, BigQuery, Snowflake, Spark, …). The actual workflow guides live inside the `wren` CLI itself; this is just a discovery stub. Use whenever the user asks a data question (how many, show me, top N, compare, trend, breakdown, metric, revenue, customers, orders), wants to install / set up Wren Engine, connect a new database, connect SaaS data via dlt (HubSpot, Stripe, Salesforce, GitHub, Slack), generate or regenerate an MDL project from a database schema, enrich a project with business context (enum meanings, units, cubes like ARR / DAU / churn), or turn a project's context layer into a shareable GenBI web app / dashboard and deploy it to Vercel or Cloudflare. Triggers: 'install wren', 'set up wren engine', 'connect database to wren', 'connect SaaS to wren', 'load hubspot / stripe / salesforce data', 'generate mdl', 'scaffold wren project', 'enrich wren context', 'augment my project', 'add cubes', 'build a dashboard', 'make a shareable analytics app', 'deploy my context layer as a web app', 'genbi app', 'wren onboarding', 'wren usage', 'wren generate mdl', 'wren dlt connector', 'wren enrich context', 'wren genbi'.
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Original instructions from the publisher’s SKILL.md
# 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.