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'.
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.
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)Full reference docs live on the web: https://github.com/Canner/WrenAI/tree/main/docs/core
wren docs connection-info <ds> # required + optional connection fields for a data sourcewren ask "<question>" --guided # for weaker LLMs (strict task flow)
wren ask "<question>" --direct # for stronger LLMs (minimal wrapping)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.
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If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.