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AI Skills

Datazone publishes a set of public agent skills that teach AI coding assistants how to work with Datazone. Install them once, and your agent knows the YAML schemas, the config.yml registration rules, the deploy loop, and the mistakes that produce a project which validates and then fails at runtime. Without them, an assistant guesses at Datazone’s conventions. With them, it writes a @transform that deploys, an endpoint YAML that resolves, and a Studio App that does not 404 on its own assets.

Browse the collection on skills.sh

Eight skills covering pipelines, endpoints, flows, objects, apps, and the API

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Install

Run this in the root of your Datazone project repository:
The CLI detects which assistant you use and installs the skills where it expects to find them. Supported clients include Claude Code, Cursor, Codex, GitHub Copilot, Windsurf, Gemini, Cline, AMP, and Antigravity. To install a single skill instead of the whole collection, pass --skill:
Skills are instructions, not credentials. They tell your agent how Datazone works — they do not grant it access. Your agent still authenticates with your own API key or datazone CLI profile, under your existing policies.

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What’s included

Each skill loads only when it is relevant. Ask your agent to “add a chart to the sales app” and it reads datazone-intelligent-app; ask it to “expose this query as an API” and it reads datazone-endpoint. You do not choose between them by hand.

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Using them

Once installed, work in plain language. The skill supplies the schema and the conventions.
The agent writes pipelines/revenue_by_region.py, registers it in config.yml under pipelines: with a unique alias, commits, and pushes — because pushing is what deploys. It then checks the deploy result, since validation is server-side and asynchronous. Some further examples that map cleanly onto a single skill:
  • “Create a Knowledge Object for Contract with a relationship to Customer.”
  • “This flow fails validation — the for_each node isn’t receiving its input.”
  • “Expose the unpaid-invoices query as an endpoint and show me how to call it.”
  • “My Studio App builds but shows a blank page.”
Skills are most useful inside your project repository, where the agent can read your actual config.yml, datasets, and existing definitions. Several skills begin by confirming they are in a Datazone project — one with a config.yml at the root — and will stop and ask if they are not.

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Keeping them current

Datazone’s YAML schemas and CLI evolve. Re-run the install command to pull the latest published versions:
The collection is versioned alongside the platform, so refreshing after a release keeps your agent’s knowledge aligned with what your deployment actually accepts.

Command Line

Install the datazone CLI and manage profiles

Projects

How a project repository is structured and deployed

Orion AI

Datazone’s built-in assistant for queries and apps

API Reference

The REST API your agents and scripts call