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To determine what an AI agent did and who started it, begin with the session or request record, follow its trace through turns and spans, and then inspect identity fields on the relevant tool and model events. Timestamps and parent-child links reconstruct the order; recorded arguments, results, status and duration show the operation; attribution fields distinguish the agent that executed work from the human or workflow that initiated it.
A missing field or absent event is an evidence gap, not proof that the action never occurred. Logging may be disabled, the reviewer may lack permission, or content recording may intentionally be off. A reliable review therefore combines platform telemetry with application-level audit context describing the business trigger, approval and outcome.
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What does an AI agent activity log actually contain?
An activity log is a set of related records rather than one chronological paragraph. A session or request is the outer container. Inside it, turns represent exchanges, and spans represent individual operations such as a root-agent run, a subagent handoff, model generation or a tool call. This hierarchy lets you move from a user-visible request to the exact operation that changed data or contacted an external system.
OpenAI’s Agents API tracing documentation describes this navigation model and the event details a trace can expose, including inputs, outputs, tool arguments, results, status and duration: Agents API tracing. The exact fields vary by platform and by whether content recording is enabled, so treat an empty value as “not recorded,” not as a confirmed empty input or result.
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Why the hierarchy matters
- Session or request: the broad unit a reviewer searches for, often tied to a conversation or API request.
- Turn: one exchange or processing cycle; a session can contain several turns.
- Span: a timed operation with a parent and, potentially, child spans. A tool span is usually where the called tool, arguments and result are visible.
Reviewing only the final answer can hide retries, delegated subagent work, failed calls or a later correction. The span tree preserves those intermediate steps when tracing is configured to capture them.
How do I find the session or request I need to review?
Start with the narrowest identifier you have: a session ID, request ID, conversation reference, approximate time or affected resource. In the OpenAI dashboard, the documented path is Logs → Agents. Select the project, search for the session, then narrow the list by model, status or date before opening its timeline. The dashboard workflow is described at OpenAI’s tracing guide.
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- Write down the user report or system alert, including its time zone and the resource that appears to have changed.
- Choose the project or environment in which the agent ran. Searching the wrong project can look identical to a missing event.
- Search by session or request identifier first. If you do not have one, use the smallest practical time window and filters for model, status and date.
- Open the timeline and confirm that the visible turns match the conversation or job you are investigating.
- Record the session ID, trace ID and any child span IDs before opening individual events; those identifiers are the evidence anchors you will cite later.
For systems that do not expose a dashboard, use the equivalent request record in your observability store. Preserve the original identifiers rather than replacing them with a ticket number, because correlation depends on the platform-generated values.
How do correlation IDs and parent spans reconstruct the execution path?
Correlation fields answer different questions. A trace-level identifier groups all events for one request; span identifiers locate one operation; a parent-span identifier shows which operation invoked it. Thread and timestamp fields add conversation and ordering context.
| Field | What it links | How to use it in a review |
|---|---|---|
| TraceId | Events belonging to one request in Azure SRE Agent telemetry | Collect every event with the same value to build the request-wide timeline. |
| SpanId | One operation within that trace | Open the specific model, agent or tool operation and quote its status and timing. |
| ParentSpanId | The operation that caused the current span | Walk upward to identify whether a tool call came from the root agent, a subagent or a retry. |
| ThreadId | Conversation or thread context | Separate turns that share a user conversation from unrelated requests. |
| LogTimestamp | When the event was logged | Order events and compare them with application records; preserve the original value and time zone. |
| CorrelationId | Additional grouping key in Azure SRE Agent events | Use it when TraceId alone does not match the surrounding audit records. |
Microsoft documents these fields and their relationships in Azure SRE Agent audit guidance. Build the sequence from parent-child relationships first, then use timestamps to order siblings. This avoids mistaking a late-arriving log line for a later action.
What should I inspect inside a model or tool span?
Open each span that could have influenced or performed the action. Compare the recorded input, output, arguments, result, status and duration instead of relying on the span name alone.
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- Check the input messages or instruction reference that led to the decision, when content recording is enabled.
- Note the model identifier and the generation’s start and end times.
- Look for a handoff or tool-selection output that explains which child span should be inspected next.
Tool spans
- Identify the tool or function name and the exact arguments recorded.
- Compare the tool’s start time with its parent span to detect retries or parallel calls.
- Read the result and status separately. A successful model turn can contain a failed tool call, and a tool result can be recorded even when a later step rejects it.
- Use duration to spot timeouts or unusually slow dependencies, but do not infer a cause that the record does not state.
Blank arguments, outputs or results limit what the trace establishes. They may reflect redaction, disabled content capture or an instrumentation gap. Document the limitation alongside the span ID rather than filling in the missing detail from memory.
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How can I tell whether a human or an agent initiated the action?
Look for two identities: the agent identity that executed the operation and the user principal or workflow identity that initiated it. Delegated work should preserve both. Autonomous work may legitimately show only the unique agent identity.
Google Cloud’s Agent Platform observability guidance describes this dual attribution. Execution and audit logs can record a SPIFFE-based agent identity together with the initiating human user when an agent acts on someone’s behalf. For autonomous activity, the agent’s unique identity is the actor. The guidance also describes filtering with is_agentic=true, then narrowing by agent identity or user principal: Google Cloud observability overview.
| Observed attribution | What it supports | What it does not prove |
|---|---|---|
| Agent identity plus user principal | The named agent executed work associated with that initiating person. | That the person personally approved every intermediate step unless an approval event is also logged. |
| Agent identity only | The platform attributes execution to that agent, consistent with autonomous operation. | That no human or workflow triggered it; the initiating context may be stored elsewhere. |
| User principal only | A user-associated record exists. | That the user executed the tool directly rather than through delegation. |
| No usable identity | The trace is insufficient for attribution. | That the action was anonymous or did not happen. |
When several users can invoke the same agent, match the principal to the session’s authentication and application records, not merely to a display name. Keep the raw identity value and the human-readable interpretation in your review notes.
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Before concluding that an action is absent, check logging configuration and access. Google Cloud states that Data Access audit logs are disabled by default for Agent Platform, while System Event and Admin Activity logs are always enabled: Google Cloud audit logging documentation. A Data Access event can therefore be missing even when the platform is operating normally.
Also verify that the reviewer can query the relevant project and log category. Microsoft’s Foundry tracing guidance notes that monitoring-resource permissions may be required for queries: Microsoft Foundry agent tracing guidance. In OpenAI’s tracing workflow, trace export must be enabled and the API key needs trace-read or broader agent-read permission before exported traces can be retrieved; the requirement is documented in the Agents API tracing guide.
A coverage check before declaring “no event”
- Confirm the project, region and environment match the reported action.
- Check whether the relevant audit category was enabled at the event time.
- Verify the reviewer’s role or API key includes trace and monitoring read access.
- Check retention and export settings for the date being investigated.
- Look for a parent trace or neighboring spans that indicate the request existed even if a child event is absent.
What if the trace is missing a span or the event has no payload?
Treat the result as an evidence limitation and branch the investigation. An absent record can mean disabled logging, an expired retention window, insufficient permissions, intentional redaction or an instrumentation failure. It is not a reliable negative proof.
When the entire request is absent
Search the application’s request or authentication logs using the user, resource and time window. If those records show an invocation but the agent platform does not, compare project and environment settings and verify that trace export was enabled at that time.
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When the parent exists but a child span is absent
Inspect the parent’s status and output for a handoff, retry or tool-selection decision. Then check the downstream service’s own audit log. A tool may have executed in another system even when the agent trace did not capture a child span.
When values are blank
Determine whether content recording was disabled or redaction removed the value. Preserve the field’s blank state in your report and rely on status, timing and downstream records only for what they actually establish.
How do I connect the technical trace to the business reason?
Platform telemetry explains the execution sequence, but it may not explain why the request was triggered or what business rule justified it. Add an application-level audit record for the initiating event or input, grounding data, action and outcome, and any human-review decision.
Salesforce Architects summarizes this requirement: “When agents take actions, audit trails must reconstruct not just what happened but why.” The architecture guidance is available at Salesforce Architects’ agentic-enterprise trust guide.
Join the application record to the platform trace with a stable request or correlation identifier. If the business trigger is a scheduled workflow, retain the workflow run ID; if it is a user request, retain the authenticated principal and the original input reference. Do not infer the trigger solely from a model’s generated text.
How should sensitive prompts, arguments and results be handled?
Agent traces can contain prompts, retrieved context, credentials accidentally passed as arguments and personal or confidential data in outputs. Microsoft recommends disabling content recording in production when it is not required and redacting sensitive data before telemetry capture, as described in its agent tracing guidance.
- Use least-privilege roles for reviewers and separate read access from export permission.
- Redact secrets before they enter telemetry; post-export cleanup cannot undo every copy.
- Apply the organization’s retention schedule to traces, exports and incident attachments.
- Keep a redaction note so another reviewer can distinguish “not recorded” from “removed for privacy.”
- Export only the spans needed to answer the incident, rather than an entire conversation containing unrelated data.
Privacy controls create an intentional trade-off: less payload detail can make attribution or debugging harder. Record which controls were active at the time so the limitation is understandable later.
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Which tracing capabilities should an implementation provide?
There is no universal product ranking in the cited documentation. Compare implementations against the evidence an investigation needs.
| Capability | Questions to ask | Minimum useful outcome |
|---|---|---|
| Identity attribution | Are agent and initiating-user identities recorded together for delegated work? | A reviewer can distinguish executor from initiator. |
| Correlation depth | Are session, trace, span and parent-span identifiers available? | The reviewer can walk from request to child tool call. |
| Event detail | Are model and tool inputs, arguments, results, timestamps, status and duration captured or intentionally redacted? | The reviewer can establish what was attempted and its outcome. |
| Coverage and defaults | Which audit categories are enabled by default, and can Data Access or equivalent logs be turned on? | An absent event can be interpreted in its configuration context. |
| Access and export | What roles or API permissions allow querying and exporting traces? | Authorized reviewers can retrieve evidence without broad administrative access. |
| Content controls | Can production recording be disabled or fields redacted before capture? | Sensitive data exposure is limited while required metadata remains available. |
Microsoft notes that tracing availability can differ by agent type: at the time of its documentation, prompt and hosted-agent tracing were generally available while workflow and external-agent tracing remained in preview. Check the current product documentation before relying on a specific interface or availability claim.
What is a complete end-to-end review procedure?
Use this sequence for an incident, compliance request or internal audit. Keep the raw identifiers and the reviewer’s decisions with the case record.
- Define the question. State the action, affected resource, approximate time and whether you need to establish execution, initiation, approval or all three.
- Locate the request. Search the correct project or environment by session, request, date, model or status. Open the timeline and save its session and trace identifiers.
- Map the tree. List root-agent, subagent, model and tool spans. Follow
ParentSpanIdor the platform’s equivalent to preserve causality. - Order events. Use timestamps to order sibling spans and retain the original time zone. Note parallel calls rather than forcing them into a false serial order.
- Read the decisive span. Capture the tool name, arguments, result, status and duration. Link any model-selection span that led to the call.
- Resolve identities. Record the agent identity and, where present, the initiating user principal or workflow identity. Use agentic-event filters such as
is_agentic=truewhere supported. - Join business context. Match the trace to the application event, grounding data, approval record and outcome using a stable correlation key.
- Test coverage. Check audit-category enablement, trace export, retention and your query permissions before treating gaps as negative evidence.
- Protect the evidence. Redact sensitive payloads, restrict access and document which fields were intentionally omitted.
- Write the finding. Separate “recorded,” “not recorded” and “inferred from another system.” State the remaining uncertainty and cite the exact span or application record supporting each conclusion.
What are the most common review failures and fixes?
Searching only by the visible chat message
Different sessions can contain identical wording. Use the authenticated principal, project, time window and resource identifier to disambiguate, then confirm the session timeline.
Equating the agent with the initiator
The agent identity identifies the executor. For delegated work, look for the separate user principal or workflow identity; for autonomous work, document that only the agent actor was recorded.
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Inspect each tool span’s status and result. Retries and partial failures can be hidden by a later model response.
Ignoring logging configuration
Check Data Access or equivalent category settings, trace export and monitoring permissions before concluding that no event exists.
Exporting unrestricted payloads
Apply redaction, least privilege and retention controls before attaching traces to tickets or sharing them outside the operations team.
Reporting the technical sequence as the business explanation
Join the trace to an application audit event that records the trigger, grounding information, action, outcome and human-review decision when applicable.
Frequently Asked Questions
Can a trace alone prove that a person approved an agent action?
No. A trace can associate execution with a user principal, but approval requires a distinct approval event or application record showing what was reviewed and when. If no such record exists, report the identity association without calling it human approval.
What should I attach to an incident ticket when exporting a trace?
Include the session, trace and decisive span identifiers, the export time, the query filters used and the reviewer’s access scope. Add a short redaction note describing fields removed or content recording that was disabled, so later reviewers understand why some values are absent.
How can I distinguish an autonomous run from a scheduled workflow?
Look for the initiating identity outside the agent span: a workflow-run ID, scheduler record or service principal can establish that a process started the run. If those records are unavailable and only the agent identity remains, describe the run as agent-attributed rather than asserting that it was autonomous.
What should a custom agent record if the platform’s built-in trace is too sparse?
Emit a stable request or workflow identifier, parent-child operation links, agent identity, initiating principal, timestamps, status and tool name. Keep sensitive prompts and arguments out of production telemetry unless they are necessary and protected, and retain a separate application audit record for the business trigger and outcome.
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