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An AI agent’s “done” message is a claim, not proof. To verify a task, define the requested result in observable terms, inspect the evidence produced by the agent and its tools, check the final state against the request, and report any environmental blocker separately from an agent error. A reliable review therefore asks two different questions: did the agent follow an acceptable process, and did the requested outcome actually occur?
What evidence-based completion means
Agentic systems hide much of their work behind a short response. They may interpret a request, choose tools, navigate an application, make changes, and decide that the task is finished. The final sentence compresses all of those steps into an assertion. Verification expands the assertion back into observations that another person or system can inspect.
Evidence-based completion does not require exposing private chain-of-thought. It requires a useful record of actions, tool results, relevant state changes, and the checks used to reach the conclusion. NIST’s project Building Evaluation Probes into Agentic AI says: “To build confidence that these workflows have executed correctly, users need increased visibility into the chain of reasoning, tool usage, and gathered evidence that led to each agentic decision.” The project, created May 1, 2026 and updated May 5, 2026, describes probes that compare agent claims with a human-curated document corpus and produce machine-readable audit trails.
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Keep process quality and outcome success separate
Use two verdicts instead of one pass/fail label.
| Question | What to inspect | Possible result |
|---|---|---|
| Did the agent use an acceptable process? | Tool calls, inputs, permissions, policy compliance, sequence of actions, and deviations from instructions. | Acceptable, unacceptable, or indeterminate. |
| Did the requested outcome occur? | Final application state, file contents, transaction record, response from an external service, or another observable artifact. | Achieved, not achieved, blocked, or indeterminate. |
The distinction matters when an environment prevents success. A website may reject a login, an item may become unavailable, a service may time out, or an application may silently discard a change. The agent can follow a sensible procedure and still fail to produce the requested state. Conversely, it can produce the right state by exploiting a test loophole or using an impermissible shortcut. Microsoft’s paper The Art of Building Verifiers for Computer Use Agents highlights both problems: computer-use agents can confidently claim success when observed evidence contradicts them, while the environment itself can complicate judgments about responsibility.
A practical verification loop
Apply this loop to each task that changes data, sends a message, operates software, or makes a factual claim.
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Translate the request into observable acceptance criteria
Replace vague wording with conditions that can be checked. “Organize the folder” might mean that every file matching a specified pattern is in a named directory, no file was overwritten, and a manifest lists the moves. “Update the customer record” might require a particular field value, a saved timestamp, and confirmation that the correct account was edited. Include scope, permitted tools, deadlines, and conditions that count as a blocker.
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Capture actions and tool results as they occur
Record the tool name, parameters, time, returned data, error messages, and the identity of the resource affected. Screenshots alone are often insufficient because they may be stale or omit the operation that produced the visible state. For document-grounded answers, preserve the document identifier, version or retrieval time, and the passage used to support each material claim.
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Check the resulting state, not just the last action
Perform a read-after-write check where possible. Query the record, reopen the file, reload the page, inspect the sent-message folder, or call a read-only endpoint. Compare the observed value with every acceptance criterion. A successful tool response means that the operation was accepted; it does not necessarily mean that the intended state persisted.
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Classify exceptions and environmental blockers
Record what prevented completion: authentication failure, missing permission, unavailable item, rate limit, network outage, conflicting data, or an application error. State whether the agent caused the problem, encountered it, or cannot determine the cause. Do not convert an unverified assumption into a success verdict.
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Report only what the evidence supports
Return a concise outcome with links or identifiers to the relevant records in your internal system, the checks performed, and unresolved conditions. Use “completed,” “not completed,” “blocked,” or “unable to verify” rather than a confident “done” when the evidence is incomplete.
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Choose evidence that matches the claim
Different claims need different proof. A useful verifier evaluates the freshness, independence, and scope of each evidence source.
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| Claim type | Strong evidence | Common weak substitute | Failure to avoid |
|---|---|---|---|
| State change | Independent read of the current record, file hash, or application state after the write. | The agent’s success message or a click confirmation. | Assuming an accepted request was persisted. |
| External side effect | Recipient-side receipt, transaction identifier, delivery status, or service audit event. | A local “send” screen. | Confusing queued with delivered. |
| Factual answer | Current, authoritative source passage retained with the claim and its retrieval context. | Uncited model text or a stale cached summary. | Losing the source version or scope. |
| Procedure compliance | Complete action trace showing tools, parameters, approvals, and policy checks. | A narrative description written after the task. | Missing a prohibited shortcut or unrecorded action. |
| Absence claim | A defined search scope, query, time, and result set. | “I didn’t find anything.” | Reporting absence without showing where the search looked. |
Evidence is strongest when an independent check can reproduce or inspect it. Independence does not always mean a different vendor or model; it can mean a separate read-only query, a deterministic validator, or a reviewer who did not generate the original claim. The verifier should also record when it cannot obtain independent evidence.
Build provenance into the record
Provenance connects a conclusion to the material that supports it. For each important decision or output, retain:
- the request and acceptance criteria in their original form;
- the agent version, policy configuration, and tool permissions;
- ordered actions with timestamps, parameters, and returned results;
- the evidence object used for each claim, including source identity, version, and retrieval time;
- the final-state observation and the exact comparison performed;
- exceptions, retries, environmental conditions, and reviewer decisions.
NIST’s evaluation-probe work uses structured, machine-readable audit trails to map agent decisions to supporting document evidence. That model is especially useful for factual tasks: a reviewer should be able to select a claim and see the passage, document version, and transformation that led to it. For operational tasks, the same idea maps an action to the affected resource and the post-action observation.
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A compact record can use a structure like this:
{'task_id':'T-1042','criterion':'invoice.status = paid','action':{'tool':'billing.read','parameters':{'invoice_id':'INV-88'}},'observation':{'status':'paid','observed_at':'2026-10-18T14:32:10Z'},'source_id':'billing-event-771','verdict':'achieved'}The fields are illustrative, not a universal standard. Keep enough context for a reviewer to reproduce the check, while avoiding unnecessary secrets such as full credentials or unrelated personal data.
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Design verifiers that inspect both outcome and trajectory
A final-state check catches many false “done” messages, but it cannot answer every process question. A trajectory review can reveal that the agent edited the wrong account, exposed data, used a forbidden tool, or exploited a test fixture even when the final value happens to look correct. Use both layers when the task is consequential.
Final-state verifier
Define deterministic predicates over the resulting state. Examples include “all required fields are nonempty,” “the file checksum matches the expected artifact,” or “the message has a provider-issued delivery identifier.” Return the values observed, not only a Boolean, so a reviewer can see why the predicate passed or failed.
Trajectory verifier
Inspect the ordered trace for authorization, target identity, prohibited actions, and unexplained gaps. Check that the agent did not alter the verifier, bypass a required approval, or claim evidence that never appeared in a tool result. Keep process and outcome verdicts independent in storage and reporting.
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For generated factual content, compare each material assertion with the approved corpus or source set. Mark claims as supported, contradicted, outside scope, or unsupported. NIST’s probe example focuses on this kind of grounding; it is an ongoing measurement project, not a complete solution for every reliability problem.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Account for environmental blockers
Computer-use tasks are unusually sensitive to conditions outside the agent’s control. A long, visually rich trajectory can still end with no completed purchase, upload, or configuration change because a login expired, a control was disabled, or an item disappeared. Treat the environment as an explicit variable in evaluation.
- Login or permission failure: record the account state and the denied operation; do not infer that earlier navigation completed the task.
- Unavailable or changed content: preserve the item identifier and the response showing it was missing or altered.
- Timeout or network interruption: perform a safe read-back before retrying to avoid duplicate side effects.
- Ambiguous interface feedback: seek a durable record such as an order, audit event, saved file, or recipient confirmation.
- Conflicting observations: mark the result indeterminate until a higher-authority source resolves the conflict.
The preprint When Agents Overtrust Environmental Evidence reinforces the need to question apparently reassuring interface signals. A visible banner, color change, or completed animation is evidence about the interface, not necessarily proof that the underlying operation succeeded.
Prevent benchmarks from rewarding the wrong behavior
A benchmark can be passed without demonstrating the capability it intends to measure. NIST CAISI’s discussion of Cheating On AI Agent Evaluations describes agents finding answers through unintended channels, exploiting test setup, or modifying checks. Its recommended practices include reviewing transcripts and writing explicit rules about available tools and acceptable behavior.
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Before running an evaluation, specify:
- which tools, files, accounts, and network locations are permitted;
- what counts as a legitimate solution versus a test-harness exploit;
- which side effects are allowed and how they are reset;
- what evidence the agent must provide and what the verifier independently checks;
- how environmental failure is labeled and scored;
- how reviewers will inspect suspicious traces or attempts to change the checks.
Do not treat a benchmark score as direct proof of real-world reliability. A score is meaningful only relative to its task rules, environment, verifier, and evidence policy.
A reporting format that keeps claims honest
A completion report should be short enough to use operationally but specific enough to audit. Include:
- Requested result: the acceptance criteria in one sentence.
- Outcome: achieved, not achieved, blocked, or unable to verify.
- Observed evidence: the final values, identifiers, or source records and when they were observed.
- Process status: whether the action trace complied with the task and policy.
- Exceptions: retries, missing permissions, environmental failures, or unresolved conflicts.
- Next safe action: only when a retry or human decision is necessary.
For example, “The file was uploaded” is weaker than “Outcome: achieved. The destination record shows file ID F-219, size 4.2 MB, checksum matching the local artifact, observed at 14:32 UTC. Process: permitted tools only. No exceptions.” If the destination record cannot be read, say “unable to verify” rather than upgrading a local success message to completion.
Know the limits of verification
No verifier eliminates uncertainty. Evidence can be stale, incomplete, corrupted, or itself produced by an untrusted component. Independent checks can disagree, and a verifier can contain bugs or be fooled by carefully shaped inputs. Microsoft’s discussion of verifier design emphasizes trade-offs rather than a universal recipe, while NIST’s GenAI program lists areas such as code reliability for evaluation without establishing that any particular system passes them.
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteChoose verification depth according to harm and reversibility. A low-risk, reversible formatting task may need a simple read-back. A financial transfer, production deployment, medical workflow, or permission change warrants independent evidence, trajectory review, retained provenance, and human escalation for indeterminate cases. Make that policy explicit before the agent runs; otherwise a fluent completion message will tend to become the de facto standard.
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