A support agent receives an assistant response with stop_reason=tool_use and two tool requests. The app has already shown a short progress sentence. What should the orchestrator do next?
The agent loop should service approved calls, maintain tool_use_id associations, and send tool_result content back. It can finish when the model later returns an appropriate terminal stop reason.
Progress text does not override a tool_use stop reason. The model has requested actions whose results are still needed to answer the user, so treating the turn as finished would omit evidence.
Faked successful results would erase real-world failures and could cause wrong customer advice. Optimization must not substitute invented tool observations for execution.
Tool use is an ordinary nonterminal control-flow outcome. A new session would unnecessarily discard context and still fail to complete the requested work.
An architect is deciding how to build a Claude feature: A claims workflow may run for hours while a model occasionally returns max_tokens during a long reasoning phase. Success requires: Avoid reporting a cut-off response as a completed settlement recommendation. Which approach is appropriate?
A maximum-output-length stop indicates incomplete model generation and must be handled according to application limits.
Uncontrolled retries can duplicate external side effects and miss the truncation issue.
The draft may omit conditions, exceptions or the actual decision.
Timeout extension does not repair truncated model output semantics.
A release engineer evaluates this requirement: Avoid reporting a cut-off response as a completed settlement recommendation. The production context is: A claims workflow may run for hours while a model occasionally returns max_tokens during a long reasoning phase. Which TWO safeguards or validation actions best support a safe implementation of the requirement? Select TWO answers.
The claim recommendation may still terminate at max_tokens after the continuation budget expires. The system must report the unresolved policy exception as partial work or escalate it; continuation is not a settlement guarantee. To verify that boundary in the acceptance exercise, record interruption state and make the retry limit visible to operators.
A maximum-output-length stop indicates incomplete model generation and must be handled according to application limits. Exercising this runtime path would detect the specific fault: the orchestrator maps max_tokens to the same terminal state as end_turn.
Readable partial text can still omit a settlement condition; the completion state must stay incomplete.
Retry accounting does not prevent a prematurely finalized claim from being released.
A happy path does not show how the system handles truncated recommendations or budget limits.
During integration testing the team reports: The report stops in the middle of a policy exception, yet the dashboard shows Complete. What diagnosis most directly matches the failed requirement: Avoid reporting a cut-off response as a completed settlement recommendation?
This diagnosis explains the observed pilot behavior: The report stops in the middle of a policy exception, yet the dashboard shows Complete. The architectural fault is the orchestrator maps max_tokens to the same terminal state as end_turn. A targeted correction is: Treat truncation as incomplete, continue with an explicit budget or hand off with a partial-status marker.
This would be an operator decision despite correct state propagation, not an orchestrator that marks truncation Complete.
A denied tool is a separate access failure and cannot explain why visibly cut-off output was marked finished.
A display clipping issue differs from the model stopping at max_tokens and having that stop treated as a completed turn.
A stakeholder asks whether the proposed Claude solution guarantees success for this requirement: Avoid reporting a cut-off response as a completed settlement recommendation. Which qualification is technically defensible?
The claim recommendation may still terminate at max_tokens after the continuation budget expires. The system must report the unresolved policy exception as partial work or escalate it; continuation is not a settlement guarantee.
A progress sentence does not establish that the final policy exception or settlement decision was generated. The orchestrator must handle the stop reason and unfinished state.
A larger cap can reduce truncation but cannot guarantee completion, valid evidence, or successful external calls under finite budgets.
An end_turn denotes a model response boundary, not a receipt from an external claims system. Business state needs independently checked tool results.
A Claude application is failing a realistic test: The report stops in the middle of a policy exception, yet the dashboard shows Complete. Which remedy directly addresses the defect without a broad redesign?
A maximum-output-length stop indicates incomplete model generation and must be handled according to application limits. In this failure, the report stops in the middle of a policy exception, yet the dashboard shows Complete. The corrective action is to treat truncation as incomplete, continue with an explicit budget or hand off with a partial-status marker.
A higher cap may reduce frequency of truncation but does not change a max_tokens stop into a completed settlement. The dashboard must preserve incomplete state.
Starting a continuation is insufficient when the workflow already exposes unfinished advice as final. Completion must follow verified terminal output.
A manual handoff may be appropriate, but an unlabeled partial answer misrepresents what was actually generated. Explicit partial status is required.
A team designing a Claude workflow faces this situation: A freight-dispute assistant calls a carrier API and must continue interpreting the returned shipment events. The business requirement is: Finish only after Claude has a final user-facing answer, not immediately after a tool request. Which architecture addresses it most directly?
A tool_use response requests application execution; only a subsequent response ending in end_turn completes the conversational turn.
Text can accompany a pending tool request and does not establish completion.
A token limit indicates truncation and requires a bounded continuation policy.
A round trip may terminate with tool_use and still require tool execution.
A team plans to deploy this solution: A freight-dispute assistant calls a carrier API and must continue interpreting the returned shipment events. Its requirement is: Finish only after Claude has a final user-facing answer, not immediately after a tool request. Which TWO safeguards or validation actions best support a safe implementation of the requirement? Select TWO answers.
A tool_use response requests application execution; only a subsequent response ending in end_turn completes the conversational turn. Exercising this runtime path would detect the specific fault: the loop treats tool_use as terminal instead of executing and returning the result.
A carrier API can hang, return repeated errors, or send incomplete shipment events. The freight-dispute loop needs step and wall-clock limits plus an escalation path even when it handles tool_use correctly. To verify that boundary in the acceptance exercise, enforce a step and wall-clock budget for the loop and escalate if the cap is reached.
Registration alone cannot show that the freight assistant executed the call and read its evidence.
Transport success is not completion of the assistant's requested analysis after tool use.
The test omits the nonterminal tool-use branch and cannot establish that tool results inform the answer.
A pilot of a Claude solution produces this symptom: The application presents a tool request as its final answer and never reads the carrier event it requested. The intended requirement is: Finish only after Claude has a final user-facing answer, not immediately after a tool request. Which root cause best explains the failure?
This diagnosis explains the observed pilot behavior: The application presents a tool request as its final answer and never reads the carrier event it requested. The architectural fault is the loop treats tool_use as terminal instead of executing and returning the result. A targeted correction is: Execute requested approved tools, append tool_result messages, and request continuation until an accepted terminal state.
This would require completed tool execution; the described failure never reads the carrier result.
Invalid lookup arguments can cause a tool error, but the symptom is premature finalization before the tool runs.
A rendering omission occurs after continuation and is inconsistent with ending the turn at tool_use.
A risk reviewer is considering a Claude architecture with this requirement: Finish only after Claude has a final user-facing answer, not immediately after a tool request. Which residual limitation should remain explicit?
A carrier API can hang, return repeated errors, or send incomplete shipment events. The freight-dispute loop needs step and wall-clock limits plus an escalation path even when it handles tool_use correctly.
Text can accompany a pending tool request and does not establish completion. That alternative does not close the stated reliability or safety gap.
A successful carrier replay checks a normal path, not repeated API failures. The unattended loop still requires a step budget, bounded recovery and an escalation path when the carrier never responds.
The terminal marker says the model ended its turn, not that the requested carrier event was fetched, correctly matched, or accurate. Reconcile result identifiers and enforce incomplete-data handling.
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