Catalog Tool

Search your full data catalog directly from DinoAI. Find dbt models, sources, tests, macros, and third-party assets across your data stack.

The Catalog Search Tool allows DinoAI to search across your full data catalog, helping you discover the assets you need without leaving the Code IDE.

This tool lets DinoAI find dbt models, sources, tests, and macros, along with assets from third-party integrations, so you can quickly locate the right resource before building or extending a model.

Capabilities

The Catalog Search Tool exposes a single underlying operation:

search_catalog searches the data catalog across all dbt assets — models, sources, tests, and macros — as well as third-party integrations including Looker, Tableau, and Fivetran. It supports a text query, a result limit between 1 and 10 (default 3), and offset-based pagination. Results include asset metadata such as descriptions, tags, relationships, and lineage. Catalog data is sourced from the latest manifest.json and catalog.json; third-party data refreshes daily.

Using the Catalog Search Tool

1. Open DinoAI in the right panel of the Code IDE

2. Describe the asset you want to find

3. Add your prompt describing what you want DinoAI to do with the catalog results

4. Review DinoAI's findings and apply them to your development work

Example Use Cases

Searching the Data Catalog

Prompt

Search the catalog for assets related to marketing attribution.

Result: DinoAI queries the catalog across dbt models, sources, and third-party integrations, returning matching assets with their descriptions, tags, and lineage relationships.

Checking for Existing Assets Before Building

Prompt

Is there already a model that calculates monthly active users?

Result: DinoAI searches the catalog for matching dbt models, sources, and BI assets so you can reuse existing work instead of duplicating logic.

Working with Other Tools

The Catalog Search Tool works well alongside DinoAI's other capabilities to support your full development workflow:

• Combine with the Column Level Lineage Tool to trace the upstream or downstream dependencies of an asset you've found in the catalog

• Combine with the SQL Execution Tool to validate the structure of a model or source surfaced by a catalog search

• Combine with the Google Docs Tool or Notion Tool to cross-reference catalog assets against your data modeling specs

• Use alongside Git Lite to commit and push catalog-informed changes before opening a pull request

Best Practices

Use catalog search to explore before you build — Run a catalog search before creating new models to check whether a similar asset already exists in your workspace.

Use descriptive search terms — Search by business concept (e.g., "marketing attribution", "customer churn") to surface relevant assets across both dbt and third-party tools.

Account for refresh cadence — Catalog data reflects the latest manifest.json and catalog.json; third-party integration data refreshes daily, so very recent changes may not yet appear.