Basic workflow

Here's a typical interaction pattern for creating a data structure.

1. Get context

Important

Always ensure get_context is called at the start of your conversation. If you don't see it happen, then ask for it.

Please call get_context before we start working.

The assistant will retrieve the built-in schema and rules that define how Snowplow components should be structured. This provides the structural templates and requirements for your tracking implementation.

2. Create a data structure

Create a data structure for tracking when users view a product page.

Include properties for product ID, product name, category, and price.

The assistant will:

• Generate a proper UUID for the data structure
• Create a valid event schema following Snowplow conventions
• Save the file locally to the appropriate location

Note: Files are created locally only. Use snowplow-cli data-structures publish to sync to Console when ready.

3. Validate (automatic)

The assistant should automatically call validate_data_structures on the created file and report any validation issues.

4. Iterate if needed

The price should be optional, not required.

Also add a description field.

The assistant will modify the structure and re-validate.

5. Data product creation

Create a data product for ecommerce product interactions. Include:
- The existing product page views
- Add to cart events
- A source application for our website
- Proper validation of all components

The assistant will:

1. Create the necessary data structures for events (locally)
2. Create a source application definition (locally)
3. Create a data product linking everything together (locally)
4. Validate all components together (including cross-references)

6. Publish to Console

Use snowplow-cli data-structures publish and snowplow-cli data-products publish to push changes to Console.