When you ask a question in Ask Anything, the agent works through several visible steps before arriving at a final answer. Here’s what you’ll see and what it means.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.
Reasoning
The first thing you’ll often see is the agent’s thinking — a collapsible block that shows how the agent interprets your question. This is where it breaks down what you’re asking, identifies the key concepts, and plans its approach. Reading the thinking block is useful when you want to understand why the agent chose a particular approach, or when the final answer doesn’t match your expectations and you want to see where the reasoning diverged.Searching Your Semantic Catalog
Next, the agent searches your Semantic Catalog for relevant business definitions — metrics, features, segments, and entities that match the concepts in your question. You’ll see a brief note showing what the agent searched for and how many results it found. This step is how ClarityQ connects your plain-language question to the business logic your team has defined. If you asked about “churn,” the agent is looking for your organization’s specific definition of churn — not guessing.Reviewing Semantic Components
After searching, the agent reviews the components it found. You’ll see a list of the semantic items being examined — with their names, types, and descriptions. You can click any component to view its full definition in the Semantic Catalog. This is where the agent decides which metrics, dimensions, and entities to use in its analysis. If you notice the agent picked the wrong component, you can follow up with a correction or use an@ mention to be more specific.
Asking for Clarification
Sometimes — especially when your question could mean more than one thing — the agent pauses and asks you a question before continuing. You’ll see a card with multiple choice options or a text field. For example, the agent might ask which time granularity you want (daily vs. weekly), or which of two similar metrics you’re referring to. Answer the question and the agent continues from where it left off.Running Queries
Once the agent knows what to analyze, it executes one or more SQL queries against your data warehouse. For each query, you’ll see:- A title describing what the query does
- The SQL code in a collapsible block — expand it to see exactly what was run
- Execution time and cost — how long the query took and what it cost
- A results table — interactive, with sortable columns
The Final Answer
After all the analysis is complete, the agent presents its findings:- A written insight summarizing what the data shows, putting numbers in context — for example, noting that a metric is “down 3.2% compared to last week” or “at its highest point in 90 days”
- Visualizations — when the visualization toggle is on, every numeric answer includes rich visuals. Depending on the complexity of the question, this can be a single chart or a full visual report with multiple charts, all automatically selected to best fit the data
Working with Results
Once you have your answer, you can:- Ask follow-up questions — “Break that down by country” or “What about last month?”
- Challenge the result — If something looks off, tell the agent. Ask it to re-check assumptions or approach the question differently.
- Edit your question — Hover over your message and click edit to refine it. The agent re-runs the analysis with your updated wording.
- Check the SQL — Expand any SQL block to verify the query logic yourself.