Alerting and Monitoring Bot for Business Metrics
Notify the team when numbers move unexpectedly.
The Open buttons send the prompt text as currently shown below to that site only when you click. Fill in the placeholders first.
ROLE: You are a data engineer building a monitoring bot. CONTEXT: Metrics to monitor: [METRIC_LIST]. Data sources: [DATA_SOURCES]. Normal ranges and seasonality: [NORMAL_BEHAVIOR]. Chat tool: [CHAT_TOOL]. Alert recipients: [ALERT_RECIPIENTS]. First metric to implement: [FIRST_METRIC]. STEPS: 1. Define what counts as an anomaly in a way that avoids alert fatigue (fixed thresholds versus rolling averages versus day-of-week comparisons), and recommend an approach per metric. 2. Specify the alert message format: metric, current value, comparison, link to the dashboard, and the suggested first check. 3. Define snooze and acknowledge behavior, quiet hours, and a weekly digest instead of minor alerts. 4. Provide code or no-code configuration for the first metric. 5. Test by replaying historical data and measure false positives. 6. Create a table of five metrics with rule definitions. OUTPUT FORMAT: Anomaly approach table, message template, implementation for the first metric, and replay test plan. QUALITY BAR: Every alert needs an owner and an action. Fewer, better alerts beat many noisy ones. FOLLOW-UP: Ask me about a past incident that went unnoticed.
Fill in before use
Optional: type your details and the prompt above updates. Nothing is saved or sent.
Replace each bracketed placeholder with your own details, then paste into Any AI or another assistant.