Productivity
wren-onboarding - Claude MCP Skill
Onboard a user to Wren Engine end-to-end. Walks through environment checks, project scaffolding, connection configuration via .env, and first query. Use when: user wants to install Wren Engine, set up a new data source connection, or bootstrap a new project from scratch. Triggers: '/wren-onboarding', 'install wren', 'set up wren engine', 'wren onboarding', 'connect new database to wren'.
SEO Guide: Enhance your AI agent with the wren-onboarding tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to onboard a user to wren engine end-to-end. walks through environment checks, project scaffolding, con... Download and configure this skill to unlock new capabilities for your AI workflow.
Documentation
SKILL.md# Wren Onboarding — Agent Workflow
This skill walks the agent through onboarding — environment checks, project scaffolding, profile creation, MDL generation, and first query. **Procedural details, per-datasource setup notes, and the troubleshooting playbook live in the docs**, not here. The skill's job is to enforce the agent-side rules (one step per turn, never ask for credentials in chat) and to dispatch the agent to the right doc / sibling skill at each step.
Reference docs (the skill points to these — never duplicate their content):
- [`docs/get_started/installation.md`](https://github.com/Canner/wren-engine/blob/main/docs/get_started/installation.md) — CLI install + skill install
- [`docs/get_started/connect.md`](https://github.com/Canner/wren-engine/blob/main/docs/get_started/connect.md) — full connection procedure, **per-datasource setup notes, complete troubleshooting playbook**
- [`docs/get_started/quickstart.md`](https://github.com/Canner/wren-engine/blob/main/docs/get_started/quickstart.md) — bundled `jaffle_shop` demo
## Version check
Silently fetch `https://raw.githubusercontent.com/Canner/wren-engine/main/skills/versions.json`. Compare the `wren-onboarding` key with this skill's version (from the frontmatter above). If the remote version is newer, notify the user:
> A newer version of the **wren-onboarding** skill is available.
> Update with:
> ```
> npx skills add Canner/wren-engine --skill wren-onboarding
> ```
Continue regardless of update status.
## Mode of operation — READ THIS FIRST
**One step per round-trip.** Each numbered step below is its own turn: explain briefly, ask **only** what the step needs, run the command(s), confirm, move on.
- ❌ **Never collect information for future steps upfront.** Do not ask for project name + database type + credentials in one message.
- ❌ **Never ask for credentials in chat — not host, port, user, password, tokens, anything.** Credentials always go through `.env`. The user fills the file in their editor; the agent never sees the values.
- ❌ **Never query the database before MDL is built** via the `wren-generate-mdl` skill.
- ❌ **Never invent connection field names.** Always run `wren docs connection-info <ds>` to see the real fields — it's introspected from the live Pydantic schema, so it's always correct.
- ✅ Wait for each command to finish, report its output in plain language, then move on.
- ✅ For any error, consult `connect.md#troubleshooting` and surface the relevant section to the user — don't carry a copy of the playbook here.
## Preflight (environment only — no user questions about the project)
Read-only checks. Report findings, do **not** ask about project / credentials / datasource yet.
1. `python3 --version` — requires Python 3.11+. If older, ask the user to upgrade and stop.
2. Check virtualenv: `python3 -c "import sys; print(sys.prefix != sys.base_prefix)"`. If `False`, offer to create one (`python3 -m venv .venv && source .venv/bin/activate`). PEP 668 systems will need this.
3. `wren --version` — if already installed, confirm before reinstalling.
4. `pwd` — record it. Don't ask where the project should live yet.
Report findings as a 4-bullet list, then continue.
## Early branch — demo or own database?
> "Try the bundled `jaffle_shop` demo first (~30s, no DB needed), or connect your own database?"
- **demo** → point at [`quickstart.md`](https://github.com/Canner/wren-engine/blob/main/docs/get_started/quickstart.md) and stop this skill.
- **own DB** → continue.
## Step 1 — Collect project name + database type
These two are the only thing Step 2 needs; ask both together so the user has a clean handoff:
> "Two things before I scaffold:
> 1. **Project name** — I'll create `~/<name>/` and `cd` into it.
> 2. **Database type** — run `wren docs connection-info` (no argument) to see the full list, or pick a common one: `postgres`, `mysql`, `bigquery`, `snowflake`, `clickhouse`, `trino`, `duckdb`, …"
Wait for both. Don't ask for credentials.
## Step 2 — Project setup (batch)
Side effects: creates `~/<project>/`, installs `wren-engine[<ds>,main]`, scaffolds project files, writes an empty `.env` template.
Run as a batch — report each command briefly, then end with one "please fill `.env`" ask:
1. `mkdir -p ~/<project> && cd ~/<project>`. Refuse to overwrite an existing `wren_project.yml`.
2. `pip install "wren-engine[<ds>,main]"`. For datasource-specific install gotchas (macOS mysql, etc.), see [`connect.md#per-datasource-setup-notes`](https://github.com/Canner/wren-engine/blob/main/docs/get_started/connect.md).
3. `wren context init --empty` to scaffold without placeholder examples. Edit `wren_project.yml` to set `data_source: <ds>`.
4. **Generate the `.env` template by introspecting the connector**:
```bash
wren docs connection-info <ds> --format md
```
Use the field list to write `.env` with `<DS>_<FIELD>=` keys (UPPER_SNAKE), values **empty**. Example for postgres:
```ini
POSTGRES_HOST=
POSTGRES_PORT=5432
POSTGRES_DATABASE=
POSTGRES_USER=
POSTGRES_PASSWORD=
```
Special encodings (BigQuery base64, Snowflake account format, Athena AWS creds, etc.) are documented in [`connect.md#per-datasource-setup-notes`](https://github.com/Canner/wren-engine/blob/main/docs/get_started/connect.md). Surface the relevant section to the user verbatim — don't paraphrase.
5. Add `.env` to `.gitignore` if the project is a git repo. Suggest `chmod 600 .env`.
6. Tell the user: project is ready, `.env` is at `<path>`, please fill every value and reply **"done"**.
## Step 3 — Create the connection profile
Only after the user replies "done".
Write `/tmp/conn.yml` with **every field as a `${VAR}` placeholder** matching the `.env` keys you generated in Step 2:
```yaml
datasource: <ds>
host: ${<DS>_HOST}
port: ${<DS>_PORT}
# … one line per field from `wren docs connection-info <ds>`
```
Then:
```bash
wren profile add <project> --from-file /tmp/conn.yml
```
Validation runs automatically. The CLI overwrites profiles silently — there is no `--force` flag.
- ✓ **Success** → continue to Step 4.
- ⚠ **Any warning** → consult [`connect.md#troubleshooting`](https://github.com/Canner/wren-engine/blob/main/docs/get_started/connect.md) for the exact symptom (missing secret, driver auth failure, ValidationError, unreachable host, …) and tell the user what to fix.
## Step 4 — Generate MDL (hand off)
> ⚠️ The agent **must** build MDL before any data query. Queries against tables not in MDL will fail.
Invoke the **`wren-generate-mdl`** skill. It walks the agent through table introspection, type normalization, and YAML generation. When it finishes, return here and run:
```bash
wren context validate
wren context build
```
Report the model count and any validate warnings.
**Memory recommendation**: count models with `wren context show | grep -c '^model:'`. If `>= 200`, suggest `pip install "wren-engine[memory]"` + `wren memory index` (~800 MB). If `< 200`, skip.
## Step 5 — Ready to explore (hand off)
Suggest 2–3 NL questions based on the discovered tables (e.g. for an orders schema: "How many orders last month?", "Top 5 customers by total"). Then end this skill: for day-to-day querying the agent should switch to the **`wren-usage`** skill.
## Cross-skill routing
| Trigger | Skill |
|---------|-------|
| User mentions a SaaS source (HubSpot, Stripe, Salesforce, GitHub, Slack, …) | `wren-dlt-connector` |
| User has a connected DB but no MDL yet | `wren-generate-mdl` |
| User has MDL ready, wants to query | `wren-usage` |
| Anything else from-scratch | `wren-onboarding` (this skill) |
## On error
Don't carry an error playbook here — surface [`connect.md#troubleshooting`](https://github.com/Canner/wren-engine/blob/main/docs/get_started/connect.md) sections to the user. The doc covers:
- `wren: command not found`
- `pip install … externally-managed-environment`
- Missing secret (`MissingSecretError`)
- Driver authentication failures
- Pydantic `ValidationError` / unknown datasource
- Connection refused / firewall / cloud DB IP allow-list
- `wren context validate` warning categories
If you hit something not in the playbook, tell the user:
> "I hit an error I don't know how to fix: `<error>`.
> See <https://docs.getwren.ai/oss/engine> or open an issue at <https://github.com/Canner/wren-engine/issues>."Signals
Information
- Repository
- Canner/WrenAI
- Author
- Canner
- Last Sync
- 5/10/2026
- Repo Updated
- 5/9/2026
- Created
- 4/30/2026
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