Observability for a multi-step commerce agent should let an operator reconstruct the work without guessing from the final answer. The essential questions are what was requested, what evidence was used, which actions were attempted, which effects actually occurred and where uncertainty remains.
This guide proposes a trace structure. It does not require or recommend exposing hidden model reasoning. Operational evidence, tool inputs and outputs within appropriate privacy limits, explicit decisions and verified state transitions are the useful records.
Give the task a stable identity
Use one identifier for the business task and separate identifiers for runs, steps and retries. A restarted workflow should not look like an unrelated new customer request. Record the authorized user or service context and the intended scope without placing credentials in the trace.
The task record should show the requested outcome, start time, current state, owner and relevant version information. Model, prompt, tool and business-rule changes can all alter behavior, so a trace needs enough version context to support later comparison.
Record meaningful state transitions
| Trace element | Purpose |
|---|---|
| Evidence reference | Connects a conclusion to the inspected record |
| Proposed action | Shows what the agent intended to change |
| Authorization result | Shows whether the action was permitted |
| Tool attempt | Records the requested operation and response class |
| Verified effect | Distinguishes an accepted request from a completed outcome |
| Retry relationship | Connects repeated attempts to the same logical work |
| Escalation reason | Explains why a person or another process is needed |
Avoid storing every raw payload by default. A compact reference and a redacted summary may be sufficient for routine diagnosis, with controlled access to more detail when justified.
Distinguish success from a plausible response
A tool can return an acknowledgment before a downstream operation finishes. The agent can also produce a reassuring summary after an ambiguous response. Neither should automatically mark the task complete.
Define a completion condition for each meaningful effect. A report may be complete when its evidence-backed sections are generated and validated. A record update may require reading the resulting state. A message draft and a sent message must remain different outcomes. This prevents the final narrative from becoming the only source of truth.
Make uncertainty an operational state
Use explicit states for partial completion, unknown outcome and waiting for review. “Failed” is too broad when some steps already changed external state. The next operator needs to know what can be safely repeated and what requires reconciliation.
Include a next action and an owner for unresolved work. An alert that only says “agent error” creates investigation from scratch. The exception-first dashboard offers a pattern for turning trace findings into a manageable queue.
Protect the trace itself
Logs can contain customer information, business records and tool responses. Apply access controls, retention rules and redaction based on the task. Never log access tokens or passwords as a debugging convenience. Test that error paths follow the same restrictions as normal paths.
Keep user-facing explanations separate from internal diagnostics. Customers need a clear account of what happened and what remains; they do not need raw infrastructure details or other customers’ context.
Use traces to improve evaluation
Select representative failures and convert them into controlled replay tasks. Compare the repaired workflow against the same initial conditions. A trace is most valuable when it explains a defect and helps prevent recurrence, rather than merely proving that many tool calls occurred.
The replayable-task evaluation guide describes that feedback loop, while the agent cost and latency guide adds resource limits. Good observability makes the agent’s external behavior accountable without confusing a detailed log with evidence that the work was correct.