AI-Skills for a Pragmatic Data Vault on Snowflake

We have often spoken about the need for proper data modelling discipline, and this is especially true when an enterprise team embarks on a data vault journey. A true data vault is designed to absorb changes to an enterprise while at the same time being frictionless to evolve. A data vault is an information map for the context, relationships and historical state of your business entities and their relationships. But to ensure you are confidently building that almost unbreakable data vault you must leverage the pragmatic approach to building one.

Ultimately, we are accountable for building data platforms that remain adaptable, trustworthy, and maintainable. This article introduces an AI-assisted framework designed to help practitioners build a pragmatic Data Vault while reducing the cognitive load associated with making hundreds of design decisions.

The Conversational Assistant

Using Snowflake’s new Cortex Code use the ‘/find-skill’ skill and either

• Use /find-skill and point directly to the GitHub repository here.
• Clone the repository and copy it to ~/.snowflake/cortex/plugins/dvos-data-vault
• Fork the repository and customise the doctrine, templates, and naming standards for your organisation

Once installed you will find:

dvos-skills/
└──.cortex-plugin/
│   └── plugin.json              Plugin manifest (skills + agents declarations)
│
└──  skills/                             User-invokable skills (slash commands)
│
└── agents/                          Subagent instruction files (not invoked directly)

Uploading the plugin includes the 13 skills and 6 specialised agents, data vault doctrine and naming standards, SQL templates; that are designed to help you:

• Analyse your source systems and proposes a raw vault data model
• Choose the correct satellite variant for each entity
• Validate every construct against 42 doctrine rules before generating anything
• Produce Snowflake-optimised DDL and load patterns
• Generate Snowflake Task DAGs with correct dependency ordering
• Deploy with roles, grants, and zero-copy clones
• Attach Data Metric Functions for continuous quality monitoring
• Build Information Mart views where hash keys never appear

The Workflow

The plugin provides 13 slash commands that follow a natural progression:

Specialist agents

Subagents are not necessarily directly invoked, based on your need your orchestration agent chooses which subagent to run.

Agents in Action

You’ll find a full scripted demo here.

What This Is Not

A replacement for understanding data vault. You need to understand the data vault model primitives of hub, link and satellite tables. All other data vault model structures build on those three primitives.

A black box. Using these skills complements your own, every skill is explained and violation reported. You stay in control

An unattended code generator. It’s conversational — it asks questions, proposes, explains and waits for confirmation before producing anything.

What it is

Your AI-powered assistant on Snowflake, you can convert the templates to Claude skills and even expand on these to make them your own.

Until next time!

The views expressed in this article are that of my own, you should test implementation performance before committing to this implementation. The author provides no guarantees in this regard.