wren
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'.
Works with
--- name: wren description: 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'. license: Apache-2.0 --- # 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.
More Database skills
supabase-postgres-best-practices
supabase/agent-skills
Postgres best practices maintained by Supabase, for Postgres running anywhere. Load this skill BEFORE writing or changing anything that lives in a Postgres database: creating or altering tables and columns (including choosing column types), schema design, migrations and declarative schema files, RLS policies and the tests that verify them, indexes, triggers, database functions, queues and scheduled jobs (pg_cron, pgmq), vector/semantic search (pgvector), and restoring dumps (pg_restore) or importing data. Also load it when diagnosing slow queries, high CPU, timeouts, EXPLAIN plans, connection exhaustion, locking, bloat, or rows visible to the wrong user or tenant. This is not just a performance guide — schema, migration, security, and SQL authoring tasks need these rules too, even for a one-column change or a single query.
prisma-database-setup
prisma/skills
Guides for configuring Prisma with different database providers (PostgreSQL, MySQL, SQLite, MongoDB, etc.). Use when setting up a new project, changing databases, or troubleshooting connection issues. Triggers on "configure postgres", "connect to mysql", "setup mongodb", "sqlite setup".
prisma-postgres
prisma/skills
Prisma Postgres setup and operations guidance across Console, create-db CLI, Management API, and Management API SDK. Use when creating Prisma Postgres databases, working in Prisma Console, provisioning with create-db/create-pg/create-postgres, or integrating programmatic provisioning with service tokens or OAuth.
