Agent Trace

An agent trace is the chronological, machine-readable record of an AI agent run. It captures the task, loaded context, model version, intermediate reasoning artifacts, tool calls, returned data, and the decision that followed. That makes an agent trace different from a simple log. A log often shows technical events in isolation. A trace links intent, context, model behavior, and action into a chain that can be reviewed later. This is critical for agentic systems because an agent does more than generate text. It may read files, call APIs, change code, or trigger external workflows. When something goes wrong, the final output is not enough. Teams need to know whether the failure came from the prompt, a permission boundary, a tool result, manipulated input, or the model’s judgment. Good agent traces are complete enough for forensics and audits, but disciplined enough not to store sensitive data unnecessarily. They need timestamps, stable identifiers, preserved tool results, and clear links between planning and execution.