When you ask a question in Ask Anything, ClarityQ’s AI agent goes through a structured workflow to find the most accurate answer. Understanding this workflow helps you ask better questions and interpret results more effectively.Documentation Index
Fetch the complete documentation index at: https://docs.clarityq.ai/llms.txt
Use this file to discover all available pages before exploring further.
The Agent Workflow
Every question goes through these steps:Search the Semantic Catalog
The agent searches your Semantic Catalog for relevant components — metrics, features, segments, and entities that match the business concepts in your question.
Review matching components
The agent examines each promising result in detail, reviewing its properties, dimensions, measures, and logic to determine what’s relevant.
Import components
Components that will be used in the analysis are imported, similar to loading the right definitions before writing a query. If a component has clarification hooks, the agent may ask you a question before proceeding.
Execute SQL
The agent builds and runs a SQL query against your data warehouse, applying the appropriate date range, filters, and constraints.
The agent performs the search, review, and import steps silently. You only see the final results — SQL, data, visualizations, and the written analysis.
How the Agent Uses Your Context Layer
The quality of answers depends directly on your Context Layer:| Context Layer Component | How the Agent Uses It |
|---|---|
| Semantic Catalog | Primary source for business definitions — metrics, features, segments, dimensions, and entities |
| Table Catalog | Falls back to raw table/column metadata when no semantic component exists |
| Memory | Injects business rules, naming conventions, and domain knowledge into the agent’s reasoning |
| Skills | When invoked with /, follows step-by-step analysis methodologies with clarifications and validation |
Parallel Execution
The agent runs independent operations in parallel — for example, searching for multiple concepts simultaneously or viewing several components at once. This makes complex analyses faster without sacrificing accuracy.When the Agent Asks for Clarification
If your question is ambiguous or the agent discovers multiple valid interpretations during its search, it will ask a clarification question before executing. For example:- “Do you mean daily active users or monthly active users?”
- “Which region should I filter to — US only or global?”