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Everything the platform can do — query connectors, run governed queries, author and install ontology files, drive agents — from your terminal, scriptable and CI-ready. This workshop takes you from install to a complete ontology-as-code loop: author locally, test against live data, install programmatically, and measure the difference it makes.

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Who this is for

Data and platform engineers, analytics engineers who live in a terminal, and anyone wiring TextQL into CI or automation. You should be comfortable with a shell; Python helps but the CLI does the heavy lifting.

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What you’ll be able to do

  • Install and authenticate the CLI, and read refinery info before assuming any capability exists.
  • Query any connector into a named remote sandbox and analyze there — without pulling data to your laptop.
  • Run governed .tql query surfaces with typed parameters — the same approved queries the product runs.
  • Author new .tql files using the deployment’s own writing-tql skill as the authoritative grammar.
  • Install ontology files programmatically and run the execute-before-save loop that catches bugs before users see them.
  • Script a before/after evaluation that proves what your ontology changed.

Install & authenticate

One binary, device-flow or API-key auth, and refinery info as your compass.

Query into sandboxes

Connectors → named Python kernels; aggregate in place, never locally.

Run governed queries

The ontology mount, ANA.md, and executing approved .tql with parameters.

Author .tql correctly

The deployment’s own writing-tql skill is the grammar — use it, don’t guess.

Ontology as code

Install files via RPC, with the review discipline that makes it safe.

Prove the lift

Baseline → install → re-run: the before/after that sells the ontology.

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Before you start

You need a TextQL workspace with at least one database connector and permission to use the CLI (an admin or data-team role). Modules 3–5 write to the ontology — run them in a workspace where that’s welcome (a sandbox org, or your team’s with a heads-up).
🤖 Prefer to have Ana coach this workshop? — Paste the runner from ana-runner-full.md into a new Ana thread — you run the CLI commands in your terminal; Ana explains output and coaches module by module.