Get AI Sentiment Drop Alerts
Sentiment drop detected, Slack gets the alert with the cause, the model, and the source.
ChatBakers 
Claude 
Slack What this workflow does
By the time you notice a sentiment problem in your dashboard, it has already been shaping AI answers for days. The issue is that sentiment scores are averages — they smooth out the signal. A single negative source being retrieved across hundreds of conversations can drag your number down without ever becoming obvious in a weekly review.
This workflow catches the shift the moment it happens, identifies the specific AI conversations behind the decline, and surfaces the exact verbatim responses driving it.
Your PR team gets the raw material: not a vague metric, but the actual phrases AI is using, which models are affected, and what sources appear in those conversations.
Example prompt
ChatBakers MCP connected ❯ Pull our brand sentiment report for the last 7 days broken down by date. Compare it to the 7-day period before that. If our sentiment score has dropped, identify the specific AI conversations driving the lowest scores and retrieve the conversation details. Format the output as a Slack alert message that includes: the overall sentiment change, which AI models show the worst drop, and the 3 conversations with the lowest scores, the topics they cover, and the source URLs retrieved in those chats. Schedule this as a daily Claude task.
