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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.

Once your data warehouse is connected and you have some Context Layer components in place, you’re ready to ask your first question.

Starting a New Conversation

Navigate to Ask Anything from the sidebar. You’ll see a welcome screen with the prompt: “What would you like to ask your data today?” ClarityQ may display suggested questions based on your semantic catalog — click any of them to get started quickly, or type your own question in the input field.

Writing Your Question

Type your question in plain English. ClarityQ understands natural language, so ask the way you’d ask a colleague on the data team. Good questions to start with:
  • “How many active users did we have last week?”
  • “What are the top 10 events by volume this month?”
  • “Show me daily revenue for the last 30 days”

Input Options

Beyond typing a question, you have several tools to refine your request:
OptionHow to UseWhat It Does
Date RangeSelect from the date picker dropdownScopes your question to a specific time period (last 7 days, this month, custom range, etc.)
FiltersExpand the filters panel above the inputApply pre-configured product filters (e.g., platform, region) that constrain the data the agent queries
MentionsType @ followed by a nameReference a specific metric, feature, segment, or entity from your semantic catalog
SkillsType / followed by a skill nameInvoke a reusable analysis workflow that guides the agent step by step
Using mentions (@) is a great way to point the agent to the exact semantic components you want it to use. This leads to more accurate and faster answers.
Product filters are configured by the ClarityQ team during onboarding. Contact support@clarityq.ai if you need to add or modify filters.

Understanding the Response

A typical response includes:
  • Written insight — A natural language explanation of what the data shows and what it means.
  • Data table — Query results displayed as an interactive table with sorting and column resizing. You can download results as CSV or Excel.
  • Visualizations — When the visualization toggle is on, every numeric answer includes rich visualizations — from a single chart to full visual reports with multiple charts, depending on the complexity of the answer.
  • SQL query — The generated query, shown in a collapsible code block so you can review exactly what was run.
Sometimes the agent will ask a clarification question before answering — for example, to confirm which metric you mean or what time granularity you want. This ensures accurate results rather than guessing.

Continuing the Conversation

Ask Anything is conversational — you can ask follow-up questions in the same session. The agent retains the full context of your conversation, so you can say things like:
  • “Break that down by platform”
  • “What about the previous month?”
  • “Filter to only premium users”
  • “Show me that as a line chart”

Sharing Conversations

Once you have a useful conversation, you can:
  • Share — Generate a read-only link that anyone with access can view.
  • Star — Mark conversations as favorites for easy access later.
  • Send to Analyst — Request a data analyst to review or continue your conversation. Choose an analyst from the list, add an optional note, and it will appear in their request queue.