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## Why DeerFlow declares one timestamp convention in deerflow/utils/time.py: every lifecycle timestamp is UTC (now_iso / datetime.now(UTC)). SubagentResult writers in subagents/executor.py still used naive datetime.now(), so on any non-UTC host the in-memory lifecycle metadata (started_at / completed_at) was local wall-clock time. The sibling durable-batch path (subagents/batch_service.py) already stamps datetime.now(UTC), so the same run model carried two different conventions depending on which path wrote it. ## What changed - Added an executor-local _utcnow() helper that stamps datetime.now(UTC). - SubagentResult.completed_at default in try_set_terminal(), result.started_at in _aexecute(), and the started_at default in _aexecute_admitted() now route through _utcnow(). - Explicit caller-supplied timestamps (completed_at=...) still pass through unchanged. - Added regression tests asserting the default writers produce UTC-aware datetimes. ## Surface area - [x] Backend runtime (deerflow.subagents.executor) - internal dataclass lifecycle metadata, no wire format change - [ ] Frontend UI / Backend API / Sandbox / Skills / Dependencies / Default behavior change ## Bug fix verification - New tests: tests/test_subagent_executor.py::test_timestamp_writers_stamp_utc_aware_datetimes and test_utcnow_helper_returns_utc_aware_datetime encode the convention. - Updated BlockingDateTime.now() in the terminal-publication-order test to mirror datetime.now's optional tz argument. ## Validation - cd backend && python -m pytest tests/test_subagent_executor.py: 136 passed; 2 pre-existing TestBashExecutionHarvest failures reproduce identically on clean main (Windows sandbox env), unrelated to this change. - ruff format + ruff check clean on both changed files. ## AI assistance **Tool(s) used:** Codex (coding agent) **How you used it:** analysis of the timestamp conventions, implementation, and regression tests authored with AI assistance; change reviewed before commit. - [ ] I've read and understand every line of this change and take responsibility for it — it's not unreviewed AI output.