Requires a DuckDB connection. Before using this tool, make sure your DuckDB instance is accessible from your Paradime workspace.
Capabilities
The DuckDB Tool exposes three underlying operations:list_all_duckdb_schemas lists all schemas in your DuckDB database, excluding system schemas (information_schema and pg_catalog). Use this to get an overview of the available namespaces in your instance before drilling down into specific tables.
list_all_tables_in_duckdb_schema lists all tables and views within a given schema. Results include the table name and type, giving you a complete inventory of what’s available in each namespace.
list_all_columns_in_duckdb_table fetches full column-level details for a specific table — including column names, data types, and ordinal positions. Use this when you need to understand a table’s structure before writing SQL or defining dbt sources.
Using the DuckDB Tool
- Open DinoAI in the right panel of the Code IDE
- Describe what you want to explore — a schema, a table, or a specific column
- Grant permission when DinoAI asks to access your DuckDB instance
- Review the results DinoAI surfaces and incorporate them into your workflow
Example Use Cases
Exploring Available Schemas
PromptDiscovering Tables in a Schema
Promptanalytics schema and returns a list of all tables and views with their types, so you can identify the right table for your query or model.
Understanding a Table’s Structure
Promptanalytics.orders, including data types and positions, giving you the schema context to write accurate SQL or define a dbt source without leaving the IDE.
Working with Other Tools
The DuckDB Tool works well alongside DinoAI’s other capabilities to support your full development workflow:- Combine with the Terminal Tool to run dbt commands or SQL queries against the tables DinoAI discovers
- Use alongside the Data Warehouse Tools for cross-warehouse exploration when your stack includes both DuckDB and a cloud warehouse
- Pair with Git Lite to commit generated models and source definitions after exploring your DuckDB structure
Best Practices
Start broad, then drill down — Uselist_all_duckdb_schemas first to orient yourself, then move to tables and columns. This keeps DinoAI’s context focused and responses accurate.
Provide exact schema and table names — If you already know the schema, include it in your prompt. This avoids unnecessary round-trips and keeps the conversation efficient.
Verify column types before writing SQL — Always check data types when writing transformations, especially for date, timestamp, or JSON columns, which behave differently across DuckDB versions.
Use results to define dbt sources — Column-level output from DinoAI can be directly incorporated into schema.yml source definitions, saving manual lookup time.