Operations · Advanced
Agent trace behavioral anomaly monitor
Scan production agent traces for loops, prompt leaks, and user frustration
- When something happensNew agent traces logged
- ThenClassify behavioral failure patterns
- ResultLog metrics and queue incident alert
Inspect high-volume interaction traces from deployed autonomous agents to identify operational breakdowns. The bot flags repetitive tool calls, internal reasoning leaks, and customer dissatisfaction, recording signals to your monitoring database and alerting engineering teams before failures compound.
Prompt to start with
BotBentoRecommended
Analyze incoming agent execution traces retrieved from the database. Score each conversation turn for behavioral failure patterns such as repetitive tool execution loops, leaked internal reasoning, and negative sentiment. Record classified metrics into Datadog. When critical anomaly thresholds are exceeded, draft an incident summary for Slack, but always wait for operator approval before dispatching alerts or halting running agent tasks.