Text Topic Modeler Agent

What Text Topic Modeler Agent does

A text topic modeler agent is an AI agent specialized in text topic modeler. It does not answer from memory alone. It run queries and explain results with the sql shown, stores observations, verifies completeness, and delivers data analysis memo with queries with explicit gaps when tools fail.

The agent receives a text topic modeler task, plans tool calls (sql-warehouse, notebook, chart-builder, verifier), executes run queries and explain results with the sql shown, keeps working notes, verifies the draft, and publishes data analysis memo with queries. If query returned empty results for the selected window, it validate filters and join keys against the schema catalog. This page simulates that observable loop — not private chain-of-thought.

Workflow

Each step maps to a node in the lab above. Scroll up to play and watch the packets travel.

1. 01

   Input

   Receive task

   Accept the text topic modeler request and output constraints.

   Data preview

   In

   Run text topic modeler for Q3: produce data analysis memo with queries with audit trail.

   Out

   Normalized objective: produce data analysis memo with queries.

2. 02

   Plan

   Plan the run

   Choose tool order for Run queries and explain results with the SQL shown.