List either the data specs (parsing + mapping rule sets, resource: "specs") or the data processing jobs (executions of a spec, resource: "jobs") defined in a workspace. Each spec includes its specId and current status — poll a specific one with get_status. Both resources are paginated (default 25/page, max 100, newest first); pass the returned nextCursor to fetch more.

A spec row also carries its stored input set — sourceType, sampleFileName, formatFileName, targetOption/targetTables/targetSchemaFileName, sourceTables, merge and additionalPrompt — which is exactly what AI code generation re-reads on every re-analysis. Read that set here BEFORE calling update_data_spec: an update regenerates the parser and mapping from all of it, not just from the fields you change, so it is the only way to tell which components are about to be reused as-is.

This is NOT a table listing — specs describe configured pipelines (parsing/mapping rules), not the live set of Iceberg tables in the workspace. Multiple specs can target the same table (e.g. one spec creates it, another merges more data into it), and specs can be deleted or fail without the underlying table being dropped. For "what tables exist in my workspace" or any question about actual current data, use submit_query with SHOW TABLES instead of inferring an answer from specs.