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A scheduled agent’s green “Success” status does not always mean the requested change happened. It may mean only that the scheduler handed work to an agent thread. To find out what occurred, trace the run from trigger to thread, tool call, approval or permission gate, delivery, and the final state of the system the task was meant to change.
What “success” can mean
Status labels are defined by each platform; there is no universal contract for what a scheduled agent’s “Success” proves. In Azure SRE Agent, Microsoft documents that an execution is marked successful once its work is handed to a thread. The agent can then stop, pause for approval, or encounter a failed tool call while the execution still shows Success. Microsoft’s workflow documentation describes that product-specific behavior.
That makes it important to distinguish evidence that a scheduler fired from evidence that the agent attempted the task, that an integration accepted the action, and that the intended result exists. A final message saying “done” is not a substitute for checking the destination.
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Trace the run from trigger to outcome
1. Confirm that the schedule fired
Find an execution record at the expected time. If there is none, check whether the task is enabled, its next run time, and its schedule and time-zone settings before investigating a task-level no-op. Microsoft lists enabled status and next-run checks for Azure SRE Agent in its troubleshooting guidance.
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2. Open the execution’s thread or trace
In Azure SRE Agent, an execution row may link to a thread or say “No thread found.” The thread can show the plan, tools called, and conclusion. Microsoft’s scheduled-task tutorial also describes thread details such as planning steps, tool use, memory context, outcome summaries, and notifications. Other platforms may expose different records, or less detail.
3. Look for the intended action, not just a confident answer
Check whether the trace contains the tool call or operation the task required. If it does not, investigate the task instructions, selected agent, available tools, and autonomy or review settings. In Azure SRE Agent, a Review autonomy setting can leave a thread waiting for approval rather than proceeding.
4. Check whether the integration could act
A tool may be missing or disabled, authorization may have expired, or the agent may lack access to the target resource. For a missing email in Azure SRE Agent, Microsoft recommends checking whether the Outlook tool was called and reviewing its connector configuration. It also identifies cases where the send operation is not enabled or the recipient is locked to a different address. These are examples from that product, not assumptions about every connector.
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5. Verify the destination independently
Read back the result in the system the task was supposed to change: query the updated record, inspect the created artifact, check the sent message, or confirm the external system’s state. A successful-looking tool response is an intermediate signal; it does not by itself prove the target reached the intended state.
6. Distinguish a legitimate no-op from a missed action
Some scheduled runs correctly find nothing to do. The task should record an explicit no-action result and enough evidence to show that it checked the intended inputs and scope. Without that distinction, an empty result can look identical to a missed trigger, blocked operation, or incorrect query. This is a useful implementation practice, not a universal platform standard.
Match the evidence to the failure
| What happened | Evidence to seek | Next check |
|---|---|---|
| Schedule did not fire | No execution at the expected time | Enabled status, next run, schedule and time zone. Azure SRE Agent checks are described by Microsoft. |
| Execution fired but no thread appeared | “No thread found” or equivalent | Task and agent setup, then connector configuration. Azure-specific examples: Microsoft’s troubleshooting guidance. |
| Agent ran but skipped the intended operation | Thread lacks the expected tool call or action | Instructions, agent selection, tool availability, and review or approval state. See Microsoft’s tutorial. |
| Action is awaiting approval | Pending approval in the thread | Review or autonomy policy and the approval workflow. Azure SRE Agent’s status behavior is documented by Microsoft. |
| Tool call failed or was unavailable | Error or missing tool in the trace | Connector configuration, authorization, and permissions. See Microsoft’s Azure SRE Agent troubleshooting guidance. |
| Tool reported success, but the outcome is absent | Positive tool trace but unchanged destination state | Read back the target state rather than treating the tool response as proof. The distinction is also central to Advani’s benchmark study. |
| Action happened but its notification did not arrive | Destination changed, but delivery evidence is missing | Send operation, recipient, channel configuration, and delivery trace. Azure email examples appear in Microsoft’s guidance. |
| No change was required | Explicit result indicates no eligible work | Validate input freshness and scope, and retain an auditable no-op result. This is a general diagnostic practice, not a platform guarantee. |
Why an agent’s own completion claim is weak evidence
An agent can describe a plan or claim completion without the environment reflecting the intended result. In a 2026 benchmark paper, Laksh Advani analyzed 9,876 tau2-bench trajectories across eight model families and 1,879 AppWorld trajectories across four model families. Within those specific benchmark samples, 45–48% of failures in single-control tau2-bench domains were classified as false success, compared with 3% in the dual-control telecom setting. In AppWorld, 75.8% of self-assessing coding-agent trajectories with explicit status claims were classified as false success.
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The same paper found that no evaluated LLM-judge configuration exceeded 0.65 AUROC for false-success detection on its tau2-bench setup; the reported AppWorld judge result was 0.54 AUROC. These figures describe the study’s benchmark samples and evaluation method, not the prevalence of silent failures in production scheduled agents. They do show why confident wording and coarse activity signals are weaker than checking the environment state directly. See the paper.
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A useful monitor should report separate stages rather than collapse them into one green status. When choosing or configuring monitoring, check whether it can:
- Alert when an expected run is missing, and show whether the schedule fired.
- Expose a thread or tool trace, including errors and approval waits.
- Distinguish an attempted action from a delivered action.
- Verify the resulting application state, or make that verification straightforward.
- Retain enough audit evidence to explain a no-op, failure, or successful change.
Scheduling a task and orchestrating a longer workflow are also distinct concerns. Cloudflare’s Agents documentation describes scheduled tasks and discusses when workflows are appropriate for different use cases; it does not establish a universal status definition for other platforms. See Cloudflare’s scheduling documentation.
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