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 d
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/canner/wrenai --skill wren- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads wren automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
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
wren docs connection-info <ds> # required + optional connection fields for a data source
Prompt enhancement (wraps a user question for an agent)
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)
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.
FAQ
What does the wren skill do?
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 d
How do I install wren?
Run npx skills add https://github.com/canner/wrenai --skill wren in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/wren/ (personal) or .claude/skills/wren/ (project).
Which AI agents can use wren?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is wren safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains wren?
It is published by canner in canner/wrenai. It has 1,539 recorded installs.
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wren-dlt-connector
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Connect SaaS data (HubSpot, Stripe, Salesforce, GitHub, Slack, etc.) to Wren Engine for SQL analysis. Guides the user through the full flow: install dlt, pick a SaaS source, set up credentials, run the data pipeline into DuckDB, then auto-generate a Wren semantic project from the loaded data. Use this skill whenever the user mentions: connecting SaaS data, importing data from an API, dlt pipelines, loading HubSpot/Stripe/Salesforce/GitHub/Slack data, querying SaaS data with SQL, or setting up a new data source from a REST API. Also trigger when the user already has a dlt-produced DuckDB file and wants to create a Wren project from it.
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Augment a Wren project with business context that DB schema cannot carry — enum value meanings, units (USD vs cents, ms vs sec), NULL semantics, magic sentinels (-1 = unknown), soft-delete default filters, business synonyms, time-grain / TZ conventions, cross-system identifiers, currency rules, canonical-table preferences, AND named aggregation metrics (ARR, churn, DAU, WAU, NRR) proposed as cubes. Runs in one of two modes selected at session start: grill (one question at a time, user-driven) or auto-pilot (agent infers and applies, escalates only on conflicts and high-blast-radius additions like new cubes / views / relationships). Reads everything under /raw/ (PDFs, glossaries, handbooks, code, data dictionaries) and optionally samples low-cardinality columns from the live DB (grill mode), compares against the current MDL / cubes / instructions.md / queries.yml / memory pairs, then fills gaps via the ten-category gap catalog and the cube proposal flow. Confirmed findings
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