setup-runtime

star 49

Verify dlthub workspace is ready for dltHub Platform. Use when user wants to deploy for the first time, or when another skill reports missing prerequisites like .workspace file or dlt[hub] dependency.

dlt-hub By dlt-hub schedule Updated 6/3/2026

name: setup-runtime description: Verify dlthub workspace is ready for dltHub Platform. Use when user wants to deploy for the first time, or when another skill reports missing prerequisites like .workspace file or dlt[hub] dependency.

Verify workspace for dltHub Platform

Lightweight check that the workspace is ready for runtime work. Run through each check and fix issues as found.

Reference:

1. Verify Python project

Check pyproject.toml exists in the project root. If not:

uv init

dltHub Platform uses pyproject.toml to install dependencies remotely.

2. Check .dlt/.workspace file

ls .dlt/.workspace

This file enables profiles and the runtime CLI. If missing, use dlthub init (preferred):

dlthub init                    # creates .dlt/.workspace, prompts for workspace name
dlthub init --name <workspace> # skip prompt
dlthub init --dry-run          # preview only

Or manually as fallback: touch .dlt/.workspace

Heads up: the workspace description shown in the dltHub Platform UI comes from the first line of the docstring in __deployment__.py. You can set it now or later when creating the manifest in (prepare-deployment).

3. Check dlt[hub] dependency

Verify dlt with the hub extra is installed:

uv pip show dlt

If not installed or missing the hub extra:

uv add "dlt[hub]"

If adding dlt to pyproject.toml, pin the exact installed version (==) — uv add may downgrade pre-release versions.

4. Login to dltHub Platform

dlthub login
  • Opens a device-code OAuth flow (user visits URL + enters code in browser)
  • After login, connect to a workspace:
dlthub workspace connect                          # interactive prompt to select or create
dlthub workspace connect <name_or_id>             # skip prompt
dlthub workspace connect <name_or_id> --org-id <id>  # specify org
  • The selected workspace ID is stored in config.toml under [runtime] workspace_id
  • To switch workspaces (no re-login needed): dlthub workspace connect <name_or_id>
  • To log out: dlthub logout

5. Verify profile files exist

ls .dlt/*.toml

List existing config and secrets files. At minimum these should exist:

  • .dlt/config.toml
  • .dlt/secrets.toml
  • .dlt/.workspace

Profile-scoped files (dev.*, prod.*, access.*) may or may not exist yet — that's fine, (prepare-deployment) handles their creation.

Tell the user what's present and what the next step is: use (prepare-deployment) to set up production credentials and destinations.

Install via CLI
npx skills add https://github.com/dlt-hub/dlthub-ai-workbench --skill setup-runtime
Repository Details
star Stars 49
call_split Forks 3
navigation Branch main
article Path SKILL.md
More from Creator