Observability

A trace is a tree of spans — one per LLM call, tool call and state change — that records what the agent saw, decided, spent and how long it took; it is the primary artefact for both debugging and evaluation.

When an agent misbehaves, the trace is the evidence: walk it to the first bad decision, reconstruct the context the model saw at that step, compare tool arguments to the schema, then replay with a fix — a loop, not a guess.

Structured logs, RED metrics plus agent-specific ones (steps, tokens, cost per task), alerts on loops and cost anomalies, and dashboards — with PII redacted before anything leaves the process.