> ## Documentation Index > Fetch the complete documentation index at: https://docs.upsolve.ai/llms.txt > Use this file to discover all available pages before exploring further. # Giving Feedback > How end users rate an answer, and where that feedback shows up for you. Every agent answer carries a **Was this helpful?** prompt with a thumbs up and a thumbs down. It's the cheapest signal you will get from your users, and it lands directly next to the automated evaluations in [Chat History](/ai-agent-builder/chat-history). The action row beneath an agent answer, with a Was this helpful? prompt and thumbs up and thumbs down buttons ## Thumbs up Clicking thumbs up records the rating immediately — no dialog, no extra step. Clicking it again clears the rating, so a mis-click costs nothing. ## Thumbs down Thumbs down opens a short **Provide feedback** dialog asking *"What was wrong with this response?"*. The user can pick one of five common causes: * **Wrong chart type** * **Incorrect SQL query** * **Wrong data selected** * **Doesn't answer my question** * **Inaccurate analysis** …or type their own explanation in the free-text box, which takes precedence over the selected option. Either way the rating and the comment are submitted together. The Provide feedback dialog asking what was wrong with the response, with five preset causes and a free-text box The five preset options aren't cosmetic — they map onto the stages of the agent's pipeline, so a cluster of "Incorrect SQL query" reports points you at [System Prompts](/ai-agent-builder/system-prompts) and [Golden Queries](/ai-agent-builder/golden-assets), while a cluster of "Wrong chart type" points at [Golden Charts](/ai-agent-builder/golden-assets). ## Feedback is per answer, not per conversation The rating attaches to the specific exchange the user was looking at. A conversation where the third answer went wrong keeps that precision: * In the **Traces** view of Chat History, the thumbs down sits on the row for that exchange. * In the **Sessions** view, the session's **Feedback** column reflects the feedback given in that conversation, and the detail sidebar shows the rating and comment. ## Where it shows up for you **Chat History** — the **Feedback** column in both the Sessions and Traces views. Hover a badge to read the written comment. You can filter the table on feedback to pull up every negative answer in a time range. The Chat History table filtered to thumbs-down answers, with a feedback badge hovered to show the user's written comment **The detail sidebar** — when you open a conversation, the metadata card carries **Feedback** and the user's **Comment** verbatim. **In the thread itself** — a rated answer renders a read-only card beneath it saying *"User found this helpful"* or *"User found this unhelpful"*, along with their comment, so you see the rating in the context of the answer that earned it. **Alongside evaluations** — a thumbs down on an answer that every automated [evaluation](/ai-agent-builder/agent-observability#evaluations) passed is the most interesting row in the table. It means the answer was defensible and the user still didn't get what they needed, which is usually a context problem rather than a correctness one. ## Turning feedback into a fix The workflow that works: 1. Filter Chat History's **Traces** view to thumbs-down answers over the last week. 2. Open each one and read the user's comment, then switch to the **Observability** tab. 3. Find the step that went wrong — usually **SQL Generation** or **Chart Generation**. 4. Fix it at the source: a [System Prompt](/ai-agent-builder/system-prompts) rule if it should always apply, a [Golden Query or Chart](/ai-agent-builder/golden-assets) if it's a recurring question with one right answer. ## Next steps Let users send a single answer or a whole conversation to a colleague. Trace the answer behind a thumbs down, step by step.