curate

Curate

Manage data products, publish to marketplaces, and enrich catalog metadata.

Routing

User Intent	CLI Command	When to Use
Create/update/delete data products	scripts/run-cli product	Managing product specs and versions
Publish/unpublish to marketplace	scripts/run-cli marketplace publish/unpublish	Making products discoverable
Manage marketplaces themselves	scripts/run-cli marketplace	Creating or configuring marketplaces
Add descriptions/tags/custom fields	scripts/run-cli enrich	Enriching metadata on any catalog object

Not This Skill

• User wants to query a data product for answers → use ask
• User wants to browse or search data sources, the catalog, data products, or marketplaces → use explore
• User wants to schedule recurring queries against a product → use automate
• User wants to create a data source connection → use configure

Key distinction: curate manages data product definitions and metadata. ask runs queries against those products. "Create a data product" is curate. "Query a data product" is ask.

Data Product Lifecycle

First, check what you already have. If a complete or near-complete spec is available (e.g. from bi product-spec, a user-provided JSON/YAML file, or a prior conversation step), use it as-is — do not discard its schema, record sets, or delivery systems. Only fall back to the empty-schema workflow when you are building a spec from scratch.

When a spec is already available

1. Review the spec with the user. Confirm product ID, name, record sets, and schema look correct.
2. Save the spec as a JSON file (e.g. spec.json), then create the product: scripts/run-cli product create < spec.json If the spec is in YAML (e.g. from bi product-spec), convert it to JSON before saving.
3. Continue to Mark version ready and Publish below.

When building from scratch

1. Create product with minimal spec ("schema": []): scripts/run-cli product create < spec.json See references/product-schema.md for the JSON schema.

2. Discover columns by querying the product (use the ask skill) or browsing the data source (use the explore skill).

3. Update spec with discovered schema: scripts/run-cli product update < updated_spec.json

After creation (both paths)

4. Mark version ready: scripts/run-cli product update-version PRODUCT_ID VERSION_ID --status ready

5. Publish to marketplace: scripts/run-cli marketplace publish --marketplace EXTERNAL_MARKETPLACE_ID --product ID

Metadata Enrichment

• scripts/run-cli enrich list-fields — see available custom fields
• scripts/run-cli enrich get-values --otype table --oid 123 — see current values
• scripts/run-cli enrich set-field --otype table --oid 123 --field-id 456 --value "description text"
• Object types: table, schema, attribute (column), data (datasource)

Common Mistakes

Mistake: Trying to publish a product whose version is still in "draft" status. Why it seems reasonable: the product exists, so it should be publishable. Instead: Check version status first. Mark it as "ready" before publishing.

Mistake: Setting deliverySystems.type to uppercase "SQL". Why it seems reasonable: the dataAccess[].type field IS uppercase. Instead: deliverySystems.type must be lowercase "sql". The dataAccess[].type must be uppercase "SQL". Yes, this is inconsistent — see references/product-schema.md.

Next Steps

After finishing curation, suggest next steps to the user — but don't proceed without their go-ahead unless their original request already implies it.

• After creating or updating a data product: Share the product URL from the CLI response so the user can view it in the Alation UI.
• After publishing a data product: "Would you like to query this product? I can do that using the ask skill." If the user mentions recurring reports, suggest the automate skill to schedule queries.

Red Flags

• "I'll populate the full schema upfront" — only when building from scratch. If a pre-populated spec was provided, use it as-is.
• "Let me set the product version to ready immediately" — only after the spec is complete and validated.
• "Let me strip the schema and start fresh" — if the spec already has schema/record sets, do not discard them.