> ## 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. # Best Practices > Tips for getting the most accurate and useful answers from ClarityQ. These tips will help you get better results from ClarityQ — whether you're asking your first question or running complex analyses daily. ## Asking Questions ### Be concise and intentional Translate business questions into clear analysis questions. The clearer the question, the better the analysis. ### Ask ClarityQ how to investigate your problem If you're unsure where to start, ask ClarityQ what questions you should ask. For example: *"I see a drop in revenue per user over the last 4 weeks. What should I ask to get the most accurate analysis?"* ### Split complex questions into smaller ones Break down big or multi-part questions and use follow-ups. This helps ClarityQ reason more effectively and reduces confusion. ## Using the Semantic Layer ### Reference semantic layer components with @mentions Prefer metrics and segments from the Semantic Catalog. Type `@` and select from the popup to ensure consistency and correctness across your analyses. ## Managing Conversations ### Start a new session when changing context If you move to a different problem or business area, start a fresh chat to avoid context bleed from previous questions. ### Use Edit when you want to refine, not restart Edit is best for small corrections — clarifying a question, adjusting a filter, fixing wording, or changing a metric. No need to start over for minor changes. ### Turn off visualizations unless needed Save tokens and focus on reasoning first. Enable charts only when you need to visualize results. ## Validating Results ### Validate complex results ClarityQ improves constantly, but no system is 100% accurate. Always sanity-check complex queries and conclusions. ### If something looks odd in a visualization, say it Tell the agent what seems wrong and ask it to fix, explain, or regenerate the visualization. ### Challenge results that don't make sense You can investigate further, disagree with the agent, and ask it to re-check assumptions or analyze the data from a different angle. ## What's Next? Set up your data warehouse connection. Learn about the Context Layer and its components.