diff --git a/docs/architecture/async_ownership_538.md b/docs/architecture/async_ownership_538.md
index cdb1e53a..6e778862 100644
--- a/docs/architecture/async_ownership_538.md
+++ b/docs/architecture/async_ownership_538.md
@@ -1,13 +1,13 @@
 <!-- doc-status: proposed -->
 <!-- doc-promotion: none -->
-<!-- doc-date: 2026-10-25 -->
+<!-- doc-date: 2026-10-26 -->
 <!-- doc-module: cross -->
 
 # 非同步 edge 與 buffer ownership 盤點（#538 D1）
 
-本稿是 [#538](https://github.com/raylei50653/saccade/issues/538) 的 **D1**：依 #535 的 profiles，盤點主要的非同步 edge，逐條記下誰持有資料、何時算完成、何時可以重用或釋放、容量與溢出、失敗怎麼傳、取消與重啟時怎麼收尾，以及支撐這些說法的證據等級。**本稿不修改行為，也不選定政策**；新發現的缺口只列出並路由（§5）。Owner 對發布、路由與 #340 trace 的裁決見 §9（決策來源是 #538 的 comment）。閱讀入口是 [architecture README](README.md)。
+本稿的 §1～§9 是 [#538](https://github.com/raylei50653/saccade/issues/538) 的 **D1**：依 #535 的 profiles，盤點主要的非同步 edge，逐條記下誰持有資料、何時算完成、何時可以重用或釋放、容量與溢出、失敗怎麼傳、取消與重啟時怎麼收尾，以及支撐這些說法的證據等級。D1 只盤點與路由，不修改行為；Owner 對發布、路由與 #340 trace 的裁決見 §9（決策來源是 #538 的 comment）。[§10](#d3-f02) 另記 D3-F02 的候選修復與驗證。閱讀入口是 [architecture README](README.md)。
 
-**Source baseline**：`main@3375e7d4`（#629 merge，2026-10-25）。除 §5 標 `reproduced` 的兩項與 §1 註明的 DALI 建構觀察外，本稿新增的判讀都是 `source-inspected`；引用的既有證據保留原文件的等級與座標，本稿沒有重跑。
+**D1 source baseline（§1～§9）**：`main@3375e7d4`（#629 merge，2026-10-25）。除 §5 標 `reproduced` 的兩項與 §1 註明的 DALI 建構觀察外，D1 新增的判讀都是 `source-inspected`；引用的既有證據保留原文件的等級與座標，D1 沒有重跑。§10 的修復與驗證另列自己的基線。
 
 **本稿不擁有的內容**（只引用）：CAP／REQ 與支持裁決歸 [#535 ledger](capability_requirements_535.md)；節點／邊 ID 歸 [跨 profile 總覽](system_overview_536.md)（本稿的 `AE-*` 掛在它的 `SN-*`／`SE-*` 上，見 [§6](system_overview_536.md#6-給-537538539-的共同邊界)）；失敗狀態與 run 轉換語義歸 [#537](failure_degradation_537.md)；shipping 的排程、graph 與 parity 歸 #465（[resolved config §14](../reference/native_runtime_resolved_config.md#14-native-double-buffercuda-graphpr-10u5)），本稿只引用、不重驗、不推廣成全 repo 的保證；VRAM 快照契約歸 [degradation §6](../modules/resource/architecture_degradation.md#6-vram-level-跨程序快照契約537-b0-f07)；功能保留或退役歸 #539。
 
@@ -131,7 +131,7 @@
 | ID | 發現 | 等級 | 影響的 D3 驗收項 | 路由（§9 已裁決者註明） |
 |:--|:--|:--|:--|:--|
 | D1-F01 | `mot17.py --processes`：子程序以非零碼結束時 parent 只印 `❌`，接著用剩下的輸出算 metrics 並 `exit(0)` | reproduced | error 不得偽裝成正常完成 | **已裁決**：#537 擁有修復契約，#538 只保留追溯連結；修復見 [failure_degradation_537.md](failure_degradation_537.md) §25 |
-| D1-F02 | `WorkbenchPool.put_frame` 溢出時清空整個 queue（最多丟 4 幀），`drops` 只加 1；`AsyncDispatcher` 則是丟 1 個新幀、加 1。兩邊的計數單位不同，`drops` 不是遺失的幀數 | source-inspected | overflow、丟幀與計數語義一致 | **已裁決**：#538 獨立 D3 切片；保留 drain-all，計數改為實際丟棄的幀數（§9） |
+| D1-F02 | `WorkbenchPool.put_frame` 溢出時清空整個 queue（最多丟 4 幀），`drops` 只加 1；`AsyncDispatcher` 則是丟 1 個新幀、加 1。兩邊的計數單位不同，`drops` 不是遺失的幀數 | source-inspected（D1）；修復前重現與候選驗證見 §10 | overflow、丟幀與計數語義一致 | **已裁決**：#538 獨立 D3 切片；保留 drain-all，計數改為實際丟棄的幀數（§9）；候選修復見 [§10](#d3-f02) |
 | D1-F03 | relink 背景寫入（`pipeline_relink`）的 executor 沒有 `shutdown()`；main 先出錯時，未取的 future 不會被等待，背景 thread 可能仍在改 relinker／bank | source-inspected | cancel／drain | #539（選用分支是否保留）後再決定是否修 |
 | D1-F04 | `main.py` 的 producer 以 `asyncio.create_task(media.watchdog_loop())` 啟動 watchdog（8stream 沒有啟動 watchdog），沒有保留引用、不在 `supervise` 內、producer 結束時不取消；它的例外不會被收集。重連路徑的 `time.sleep(1)` 與 `connect()`（最多等 3 s 第一幀）在 event loop 上阻塞，同時卡住所有 stream 與 dispatcher worker | source-inspected | cancel／drain；error 不得被吞 | **已裁決**：留在 #538（event loop 阻塞與 task ownership） |
 | D1-F05 | MediaMTX 的 latest-wins 與 smart sampling 丟幀沒有計數，`AsyncDispatcher` 的 `dropped_queue_full` 看不到 ingest 層的丟幀 | source-inspected | overflow 與計數語義 | 未個別裁決；F02 的計數原則是否涵蓋 ingest 層，待 F02 切片確認 |
@@ -182,7 +182,7 @@
 - [x] 主要 async edge 有 ownership／completion／release 規則，或具名的未知與後續 owner：§2～§3 已逐條列出；未知集中在 AE-E8（C++ eval pool）與 AE-O2／AE-E1b（DALI，documentation-supported），路由見 §5。Owner 已裁決 D1 inventory completed（§9）。
 - [x] WorkbenchPool 的有限狀態契約先於修復固定（D2-WB-0 → WB-1，已合併）。
 - [x] 至少一個故障注入重現了具體違約（D2）；本稿另外重現 D1-F01、D1-F06，其餘標 source-inspected。
-- [~] overflow、丟幀與計數語義一致：**不一致**（D1-F02、D1-F05）。F02 的方向已裁決，修復尚未實作。
+- [~] overflow、丟幀與計數語義一致：F02 的候選修復與待完成門檻見 [§10](#d3-f02)；D1-F05 的 ingest 丟幀仍未處理。
 - [~] error／cancel／timeout 不偽裝成正常完成：D1-F01、D1-F06 違反；D1-F03、D1-F04、D1-F07 待處理。
 - [x] host-only、GPU-validated、documentation-supported 與未驗證的證據分開記錄（§1、§3）。
 - [x] #465 的 native schedule、capture freeze 與 trace／measurement 邊界沒有改動；本稿只引用。G 的 contract／test／limit 映射尚未交付。
@@ -210,3 +210,95 @@
   全量的壓縮率與耗時以首次封存的實測為準。
 - **GE-07**：source／文件支持、GPU-unverified，不能取代 GPU 端到端測試（stream completion、PyTorch consumer、實際 pipeline 組態）。online qualification 維持未通過。
 - **執行順序**：D1 審核並合併 → #537 F01／F06、#538 F02 與 watchdog 分別處理 → 獨立執行 #340 封存。
+
+<a id="d3-f02"></a>
+
+## 10. D3-F02：WorkbenchPool 溢出計數與停止競態
+
+**範圍與狀態**：依 §9 的 F02 裁決接續 `22c01fcd5a3ab5ff01c7f248f768c4be3eae9769` WIP；基線是 `main@aa69c3c1caf502ecc5aeeda92f90d8db6871a6c3`。這是候選實作，尚未合併。只修 `WorkbenchPool` 的 host queue admission、計數與對應停止競態；不修改 CUDA 排程、模型、tracker 參數、AsyncDispatcher 的丟幀策略或線上支持範圍。D1 表格保留原盤點座標。
+
+### 10.1 計數與 identity
+
+| 欄位 | 定義與範圍 |
+|:--|:--|
+| `drops` | 實際從滿 queue 清掉的幀數，從最近一次 `reset_stats()` 起累積 |
+| `overflow_events` | `put_frame()` 第一次 enqueue 遇到滿 queue 的次數；即使 consumer 搶先取走全部幀而清掉 0 幀，仍是一個事件 |
+| `workbench_drops`／`workbench_overflow_events` | 相同事件的 telemetry；由 telemetry 物件累積，pool 的 `reset_stats()` 不重設它 |
+| `streams[stream_id]` | pool 物件生命期的 `submitted`、`dequeued`、`dropped`、`overflow_events`、`discarded_on_stop`、`last_dequeued_seq`、`gaps`、`gap_frames` 及當下 `queued`；stop/start 與 `reset_stats()` 不清掉它們 |
+| `discarded_on_stop` | stop 清掉的 queued 幀，與 overflow drop 分開，重試 stop 不重複計數 |
+
+每條 stream 在接受 frame 時配置從 1 開始、單調遞增的 `seq`。worker 取出 frame 時記 `last_dequeued_seq`；跳過的 identity 數量計入 `gap_frames`，每段缺口計入 `gaps`。這裡的 `dequeued` 表示交給處理，不表示成功處理或 callback 已交付；處理失敗與 late callback 仍走既有契約。現有 callback 的 stream ID／timestamp 介面不變。
+
+所有 producer／worker 安靜後，每條 stream 滿足：
+
+```text
+submitted = dequeued + dropped + discarded_on_stop + queued
+```
+
+仍在執行中的 `get_stats()` 是逐 stream 的觀測，不是整個 pool 與 telemetry 的原子快照。比較總數時須保持相同統計區間：全域 `drops` 可 reset，per-stream 與 telemetry 則累積。尾端被丟棄的幀在下一個 frame 被 worker 取出之前，尚不形成已觀察的 gap。
+
+### 10.2 並行 admission 與有界停止
+
+- 保留 latest-wins／drain-all、每 stream queue 容量 4。per-stream lock 涵蓋第二次 RUNNING 檢查、identity 配置及完整 drain-and-enqueue；worker 仍可以取走舊幀。計數以實際 `get_nowait()` 取出的數量為準。
+- producer 在 lock 外已看過 RUNNING，取得 lock 後仍須再查一次；停止開始後才取得 lock 的 producer 會被拒絕，不增加 `submitted`。已通過第二次檢查的 admission 必須完成，再由 worker 或 stop 收帳。
+- `stop(timeout)` 的 worker joins 與等待 stream lock 共用 deadline。lock 逾時時維持 STOPPING、保留 batcher、增加 `stop_timeouts` 並拋 `WorkbenchPoolStopTimeout`；之後可以重試。每條 stream 一清完就更新全域與該 stream 的 `discarded_on_stop`，後面的 stream 逾時不會遺失前面的計數。batcher shutdown 仍另有既有上限（[#537 §13](failure_degradation_537.md#13-538-d2-wb-1workbenchpool-有界停止worker-failure-與資源釋放)）。
+- lock 會改變競爭下的交錯順序，因此可能改變實際交付哪些幀；保留的是上述有界 queue／latest-wins 契約，沒有宣稱修復前後的丟幀樣本、輸出、吞吐或精度等價。不同 stream 各有自己的 lock。
+
+**審查發現與處置**：對原 WIP `22c01fcd` 重現一項停止回歸：producer 持有 stream lock 時，`stop(timeout=0.1)` 等到 1 秒後才返回，且回報正常停止。原因是 worker joins 之後的 lock acquisition 沒有上限。候選改為上述 deadline 內取得 lock，並補停止後拒絕、保留 batcher、重試及部分 drain 的測試。
+
+### 10.3 證據與尚未完成項
+
+契約測試：[test_workbench_pool_overflow_contract_538.py](../../tests/unit/test_workbench_pool_overflow_contract_538.py)。CPU 情境沿用 D2 的獨立子程序 harness 與外部 timeout；GPU 情境沿用 D2-GPU 的真實 CUDA Workbench／batcher，只替換 TRT inference。
+
+- 修復前重現：送 6 幀，worker 收到 `[0.0, 5.0]`，實際丟 4 幀卻報 `drops=1`。重播使用的 dispatcher git blob 與基線 `aa69c3c1` 相同。
+- 已提交 head `a06f56abaefb6e5ea4ef86abad2ea282afffa6af`、本次新 build：四份相關契約測試 **43 passed／0 skipped**（30 個 CPU、13 個 GPU），RTX 5070 Ti Laptop。這是上述局部測試後，以新 native extension 做的完整相關回歸。
+- CPU 範圍：兩 stream／16 producer threads 的 6,400 次提交、overflow 與 telemetry 對帳、stop discard 分離、重啟 identity gap、admission／stop 競態及部分清理後的重試。
+- CUDA 範圍：既有 D2-GPU 契約與新增 F02 案例。新案例固定第一幀正在 inference，再排入 5 幀：`drops=4`、`overflow_events=1`、callback timestamps `[0.0, 5.0]`，並核對真實 CUDA 前處理交給 batcher 的兩份 input 值。
+- 6 個隔離 mutation 都被行為斷言攔住：把 drops 算成事件、telemetry 算成事件、取消 stop lock timeout、遺失部分 stop 計數、重啟重設 identity、移除 admission 的第二次狀態檢查。
+- 第一次失敗分類：新增的 stop 回歸測試在原 WIP 上失敗（`returned`，應為 `timeout`）；修復後通過。沙箱內 NVML／CUDA 被作業系統阻擋；已在沙箱外核對裝置並執行上述 GPU 測試，沒有把 skip 當通過。
+- 完整 pre-push 首次執行於 combined head `756dde4ebe580f2f551ed3ea04162b54e818f1a4`：6,241 passed、195 skipped、105 deselected、5 xfailed、1 failed。唯一失敗是既有 `test_h2_import_witness.py::test_the_recorder_records_dependencies_rather_than_filtering_them`：驗證 checkout 的 `.venv` 是指向 repo 外的 symlink，`ImportRecorder.note_file()` 依既有契約先 `resolve()` 再判斷是否位於 repo 內，所以沒有記錄該依賴。該 recorder 與測試相對基線完全未改；同一測試在原工作區通過。改以同一 head 的 `.worktrees/550-f02-validation`、repo 內的實體 `.venv` 目錄（同磁碟 hard links，禁止 sync 與 bytecode 寫入）驗證後，整份 import-witness suite **34 passed**。此項分類為已定位的驗證環境問題，沒有改寫或跳過測試。
+- 修正環境後，**同一 combined head** 的完整 `scripts/pre_push.sh` exit 0：**6,242 passed、195 skipped、105 deselected、5 xfailed、0 failed**。格式、mypy（605 files）、文件與其餘適用檢查也通過；這是本機結果，沒有遠端 CI 結果。以下收尾只增加文件中的驗證紀錄，不改實作、測試或 identity 檔案內容。
+
+本機原始輸出與 mutation runner 在 `/tmp/saccade-550-f02-evidence/`；來源與摘要檔 SHA-256：
+
+重播指令（在候選 worktree；GPU 測試需要可存取裝置的 host）：
+
+```bash
+PYTHONPATH=build/runtime_identity:src .venv/bin/python -m pytest -q \
+  tests/unit/test_workbench_pool_overflow_contract_538.py \
+  tests/unit/test_workbench_pool_lifecycle_contract_538.py \
+  tests/unit/test_workbench_pool_lifecycle_observed_538.py \
+  tests/unit/test_workbench_pool_gpu_contract_538.py
+.venv/bin/python /tmp/saccade-550-f02-evidence/run_mutations.py
+```
+
+| 檔案 | SHA-256 |
+|:--|:--|
+| `src/saccade/perception/dispatcher.py` | `c0b9a68eac09ef67b7a8e9df3380fc98cebdb909b6779459c6ae138a1af53afe` |
+| `tests/unit/test_workbench_pool_overflow_contract_538.py` | `e29c073237f4bbcd7937011132f30e7e1e386e57fdadc774e421a78a020849a4` |
+| `run_mutations.py` | `21a7ec01f720484a72070bdfa99bb5997169392108beb8c064d3fa9986dfb5d4` |
+| `mutations.json` | `2a0d106a6ff8db957a7ddad5b895aad240c0ae9aef1a03de96d13d786d68c25c` |
+| `final-contracts.log` | `3a69d4032550ea4bcc409ca9c2eb915b2a31a68ba407000de9e2de3823343b96` |
+| `final-contracts.xml` | `4c3b1f1daec87805add348a84c2c4fca3868b42d1c537d727838acc888e03e94` |
+| `pre-push.log`（首次失敗） | `f37f3683d01bcd4388c9d77ca14f8e0978501028b8ba54d4e8400536d4e05483` |
+| `pre-push-local-venv.log`（環境修正後通過） | `e28174382d9597fd174efa575ff7f5cc599987c3e580ab6f2b7bdbab17d1422e` |
+| `attested-strict.log` | `6f66d4d2da35c315d08ac546f9d406dc828bf9378a7619db41ebb586d58e750d` |
+
+**Runtime identity 候選**：在 clean `a06f56ab` 上獨立 build `saccade_tracking_ext`／`saccade_scan_plugin`，依 runbook 重跑 MOT17-09 identity probe：
+
+```bash
+PYTHONPATH=src .venv/bin/python scripts/tools/build_runtime_identity.py \
+  --run-probe --build-dir build/runtime_identity \
+  --emit /tmp/saccade-550-f02-evidence/runtime_identity.candidate.json \
+  --require-complete
+```
+
+候選 `publication_complete=true`；只有 implementation 改變（`11263f7c… → 0cb15155…`，唯一變動 member 是 `dispatcher.py`），其餘四軸相同。probe 是 fresh run，digest 仍為 `2dabed0b…`；`equivalence=unproven`。候選檔 SHA-256：`f36316235124b7edde843e262b46248299b99077f25aa47c50e1784d51bdb5b2`；capture log：`b52b5757db0b1d98785ad4ed2939e31fc2e4e27fd87c3d8bbd2d7cc396f8cd1e`。候選只寫入 scratch，publication 應以 canonical＋archive 的獨立 review surface 與實作原子落地。
+
+本機 publication 分支已準備 canonical＋archive 的獨立兩檔 commit，archive 與 `main@aa69c3c1` 的原 canonical 逐位元組相同（SHA-256 `d740889a2fe15e58bd868a9af5b8e9ae23b033c76cca1caa068562e65407d85b`）。另以 `h2_behavioral_identity.py --identity-mode` 重跑驗證 probe、`h2_runtime_inputs.py --build-dir build/runtime_identity` 重算完整 manifest，再執行 `check_runtime_identity_staleness.py --mode attested --strict --probe-from <verification-probe.json> --runtime-inputs-from <runtime-inputs.json>`，exit 0；這不是只驗 portable axes 的結果。
+
+完整 pre-push 的環境保護參數為 `UV_NO_SYNC=1`、`PYTHONDONTWRITEBYTECODE=1`；`UV_CACHE_DIR` 指向 `/tmp/saccade-550-uv-cache`。`PYTHONPATH` 依序指定本次新 build、原工作區其他 native extensions，以及驗證 checkout 的 `src`。這些參數不跳過任何檢查。
+
+**尚未完成**：獨立 publication review、最終 head review、PR／required CI 與 atomic co-land。現有本機驗證不能替代這些門檻。WorkbenchPool online qualification、D1-F05 ingest 丟幀、watchdog（F04）、多 worker NMS capture 與其餘 D1／D2 殘留仍 OPEN；沒有清除 #340 trace。
+
+回退需要同時回退實作並依 [runtime identity runbook](../reference/runbooks/runtime_identity_republication.md) 重發座標；不能只把 canonical publication 換回舊檔。
diff --git a/docs/reference/runtime_identity.generated.json b/docs/reference/runtime_identity.generated.json
index 93fd48e9..bb2411a1 100644
--- a/docs/reference/runtime_identity.generated.json
+++ b/docs/reference/runtime_identity.generated.json
@@ -1 +1 @@
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diff --git a/src/saccade/perception/dispatcher.py b/src/saccade/perception/dispatcher.py
index 6cd72ec0..21316d16 100644
--- a/src/saccade/perception/dispatcher.py
+++ b/src/saccade/perception/dispatcher.py
@@ -1,4 +1,5 @@
 import asyncio
+import functools
 import inspect
 import queue
 import re
@@ -59,6 +60,27 @@ class _StreamFrame:
     frame: torch.Tensor | Any  # RGB [H,W,3] uint8 or Nv12Frame
     timestamp: float
     enqueued_at: float
+    seq: int = 0  # per-stream frame identity, 1-based (#538 D3-F02)
+
+
+@dataclass
+class _StreamCounts:
+    """Per-stream frame accounting for ``WorkbenchPool`` (#538 D3-F02).
+
+    Counted for the lifetime of the pool (across restarts). Whenever the
+    pool is quiescent: ``submitted == dequeued + dropped + discarded_on_stop
+    + queued``. ``gaps``/``gap_frames`` are what the worker observes: frame
+    identities it never dequeued (dropped, or discarded by a stop).
+    """
+
+    submitted: int = 0
+    dropped: int = 0
+    overflow_events: int = 0
+    dequeued: int = 0
+    discarded_on_stop: int = 0
+    last_dequeued_seq: int = 0
+    gaps: int = 0
+    gap_frames: int = 0
 
 
 def _match_keypoints_to_tracks(
@@ -124,8 +146,10 @@ def __init__(
         use_nv12: bool = False,
         stop_event: Optional[threading.Event] = None,
         on_failure: Optional[Callable[[str, Exception], None]] = None,
+        on_dequeue: Optional[Callable[[_StreamFrame], None]] = None,
     ):
         super().__init__(daemon=True, name=f"wb-{stream_id}")
+        self.on_dequeue = on_dequeue
         self.stop_event = stop_event if stop_event is not None else threading.Event()
         self.on_failure = on_failure
         self.stream_id = stream_id
@@ -151,6 +175,8 @@ def run(self) -> None:
                     continue
                 if item is None:
                     break  # legacy stop signal
+                if self.on_dequeue is not None:
+                    self.on_dequeue(item)
                 self._process(item)
         except Exception as e:
             if self.on_failure is None:
@@ -351,8 +377,16 @@ def __init__(
 
         self._stats_window: deque[float] = deque(maxlen=stats_window)
         self._queue_wait_window: deque[float] = deque(maxlen=stats_window)
+        # #538 D3-F02: drops = frames actually dropped by overflow; one
+        # overflow (a put that found the queue full) may drop up to 4.
         self._drop_count = 0
+        self._overflow_events = 0
         self._lock = threading.Lock()
+        # Held by put_frame across its state check and the whole
+        # drain-and-enqueue, and by stop() while it drains: every frame is
+        # counted exactly once (dropped, dequeued, discarded or queued).
+        self._stream_locks = [threading.Lock() for _ in range(n_streams)]
+        self._stream_counts = [_StreamCounts() for _ in range(n_streams)]
 
         # #538 D2-WB-1: lifecycle state, the first worker failure, and counters.
         self._state = PoolState.CREATED
@@ -522,6 +556,7 @@ def _cb(
                 use_nv12=self.use_nv12,
                 stop_event=self._stop_event,
                 on_failure=self._on_worker_failure,
+                on_dequeue=functools.partial(self._on_dequeue, i),
             )
             worker.start()
             self._workers.append(worker)
@@ -540,32 +575,63 @@ def put_frame(
         ``WorkbenchPoolFailed``, any other state ``WorkbenchPoolNotRunning``.
         Any other stream id raises ``ValueError``.
         """
+        self._check_running()
+        idx = self._stream_index(stream_id)
+        with self._stream_locks[idx]:
+            # Re-checked under the stream lock: stop() drains under it too, so
+            # a frame is either refused here or counted by that drain.
+            self._check_running()
+            q = self._queues[idx]
+            counts = self._stream_counts[idx]
+            counts.submitted += 1
+            item = _StreamFrame(
+                frame=frame,
+                timestamp=timestamp,
+                enqueued_at=time.perf_counter(),
+                seq=counts.submitted,
+            )
+            try:
+                q.put_nowait(item)
+                return
+            except queue.Full:
+                pass
+            # Latest-wins: drain every queued frame, then enqueue the new one.
+            # Only a holder of this lock adds to q, so the put cannot fail.
+            dropped = 0
+            while True:
+                try:
+                    q.get_nowait()
+                except queue.Empty:
+                    break
+                dropped += 1
+            q.put_nowait(item)
+            counts.dropped += dropped
+            counts.overflow_events += 1
+            with self._lock:
+                self._drop_count += dropped
+                self._overflow_events += 1
+        if self.telemetry is not None:
+            self.telemetry.increment("workbench_drops", dropped)
+            self.telemetry.increment("workbench_overflow_events")
+
+    def _check_running(self) -> None:
         if self._state is PoolState.FAILED:
             raise self._failed()
         if self._state is not PoolState.RUNNING:
             raise WorkbenchPoolNotRunning(
                 f"WorkbenchPool is {self._state.value}; put_frame() needs running"
             )
-        q = self._queues[self._stream_index(stream_id)]
-        item = _StreamFrame(
-            frame=frame,
-            timestamp=timestamp,
-            enqueued_at=time.perf_counter(),
-        )
-        try:
-            q.put_nowait(item)
-        except queue.Full:
-            # Latest-wins: drain oldest and enqueue new one
-            with self._lock:
-                self._drop_count += 1
-            if self.telemetry is not None:
-                self.telemetry.increment("workbench_drops")
-            try:
-                while not q.empty():
-                    q.get_nowait()
-            except queue.Empty:
-                pass
-            q.put_nowait(item)
+
+    def _on_dequeue(self, idx: int, item: _StreamFrame) -> None:
+        """Runs on the worker: the frame left the queue for processing."""
+        with self._stream_locks[idx]:
+            counts = self._stream_counts[idx]
+            counts.dequeued += 1
+            missing = item.seq - counts.last_dequeued_seq - 1
+            if missing > 0:
+                counts.gaps += 1
+                counts.gap_frames += missing
+            counts.last_dequeued_seq = item.seq
 
     def _stream_index(self, stream_id: str) -> int:
         m = re.fullmatch(r"stream_(0|[1-9][0-9]*)", stream_id)
@@ -601,9 +667,10 @@ def _deliver(
             self.on_result(sid, ts, ids, boxes, classes, kps)
 
     def stop(self, timeout: float = 5.0) -> None:
-        """Stop all workers within ``timeout`` seconds, then shut down the batcher.
+        """Stop workers and wait for admission within ``timeout``, then shut down.
 
-        The worker joins share one deadline. If a worker is still alive at the
+        Worker joins and stream-lock acquisition share one deadline. If a
+        worker is still alive or admission holds a stream lock at the
         deadline, the batcher is kept, the state is STOPPING, and
         ``WorkbenchPoolStopTimeout`` is raised; call ``stop()`` again to retry.
         ``batcher.shutdown()`` runs after the deadline with its own bound
@@ -631,16 +698,30 @@ def stop(self, timeout: float = 5.0) -> None:
                 "the batcher was not shut down"
             )
 
-        discarded = 0
-        for q in self._queues:
-            while True:
-                try:
-                    q.get_nowait()
-                except queue.Empty:
-                    break
-                discarded += 1
-        with self._lock:
-            self._discarded_on_stop += discarded
+        for idx, q in enumerate(self._queues):
+            stream_lock = self._stream_locks[idx]
+            if not stream_lock.acquire(timeout=max(deadline - time.monotonic(), 0.0)):
+                with self._lock:
+                    self._stop_timeouts += 1
+                raise WorkbenchPoolStopTimeout(
+                    f"WorkbenchPool stream_{idx} admission still active after "
+                    f"{timeout}s; the batcher was not shut down"
+                )
+            try:
+                n = 0
+                while True:
+                    try:
+                        q.get_nowait()
+                    except queue.Empty:
+                        break
+                    n += 1
+                self._stream_counts[idx].discarded_on_stop += n
+                # A later stream can time out. Publish each completed drain
+                # now, so retrying stop neither loses nor counts it twice.
+                with self._lock:
+                    self._discarded_on_stop += n
+            finally:
+                stream_lock.release()
         if self._batcher is not None:
             # A raise propagates with the batcher kept and the state STOPPING.
             if self._batcher.shutdown() is False:
@@ -659,6 +740,12 @@ def get_stats(self) -> dict[str, Any]:
         """Return current stats. Does not reset counters."""
         with self._lock:
             drops = self._drop_count
+            overflow_events = self._overflow_events
+        streams = {}
+        for idx, counts in enumerate(self._stream_counts):
+            with self._stream_locks[idx]:
+                queued = self._queues[idx].qsize() if idx < len(self._queues) else 0
+                streams[f"stream_{idx}"] = {**vars(counts), "queued": queued}
 
         stats = list(self._stats_window)
         wait = list(self._queue_wait_window)
@@ -678,7 +765,11 @@ def get_stats(self) -> dict[str, Any]:
             "resource_monitor_error": "",
             "active_streams": self.n_streams,
             "queue_depth": sum(q.qsize() for q in self._queues),
+            # #538 D3-F02: frames actually dropped by overflow, and how many
+            # puts found a full queue (one overflow drops up to 4 frames).
             "drops": drops,
+            "overflow_events": overflow_events,
+            "streams": streams,
             "e2e_ms_mean": round(float(np.mean(stats)), 2) if stats else 0.0,
             "e2e_ms_p95": round(_percentile(stats, 95), 2) if stats else 0.0,
             "e2e_ms_p99": round(_percentile(stats, 99), 2) if stats else 0.0,
@@ -689,9 +780,10 @@ def get_stats(self) -> dict[str, Any]:
         }
 
     def reset_stats(self) -> None:
-        """Reset the drop counter."""
+        """Reset ``drops`` and ``overflow_events``; per-stream counts are kept."""
         with self._lock:
             self._drop_count = 0
+            self._overflow_events = 0
 
 
 class DispatcherState(Enum):
diff --git a/tests/unit/test_workbench_pool_overflow_contract_538.py b/tests/unit/test_workbench_pool_overflow_contract_538.py
new file mode 100644
index 00000000..e0fb9785
--- /dev/null
+++ b/tests/unit/test_workbench_pool_overflow_contract_538.py
@@ -0,0 +1,521 @@
+"""#538 D3-F02: WorkbenchPool overflow counts the frames it actually drops.
+
+Owner ruling (#538 comment 6393037794, async_ownership_538.md §9): keep
+latest-wins / drain-all, but ``drops`` is the number of frames actually
+dropped, ``overflow_events`` the number of overflows, ``discarded_on_stop``
+stays separate, and every stream keeps frame identity with an observable
+gap. Concurrent producers must not drop a frame without recording it.
+Contract: async_ownership_538.md §10.
+
+Same harness as the D2-WB tests: each scenario runs in a fresh interpreter
+under an outside timeout, with CPU fakes.
+"""
+
+# scope: perception
+# function: contract
+# lifecycle: active
+
+from __future__ import annotations
+
+import json
+
+import pytest
+
+from tests.unit.test_workbench_pool_lifecycle_observed_538 import _run
+
+_TELEMETRY = """
+from saccade.perception.online_telemetry import OnlineTelemetry
+TEL = OnlineTelemetry()
+def make_counted_pool(n=1):
+    global POOL
+    POOL = d.WorkbenchPool(
+        "fake.engine", n_streams=n, on_result=on_result, input_hw=(8, 8), telemetry=TEL
+    )
+    return POOL
+def counters():
+    s = TEL.summary()
+    return s.get("workbench_drops", 0), s.get("workbench_overflow_events", 0)
+"""
+
+
+def _streams(out: dict[str, str]) -> dict[str, dict[str, int]]:
+    return json.loads(out["streams"])
+
+
+def test_one_overflow_drops_and_counts_every_queued_frame() -> None:
+    """Ruling example: drain 4 frames, enqueue the new one -> drops += 4,
+    overflow_events += 1 (it used to be drops += 1 for 4 lost frames)."""
+    out = _run(
+        _TELEMETRY
+        + """
+async def main():
+    MODE["process"] = "block"
+    pool = make_counted_pool(1)
+    await pool.start()
+    pool.put_frame("stream_0", frame(), 0.0)          # taken by the worker
+    wait_until(lambda: pool.get_stats()["queue_depth"] == 0)
+    for i in range(1, 5):
+        pool.put_frame("stream_0", frame(), float(i))  # fills the queue (4)
+    pool.put_frame("stream_0", frame(), 5.0)          # overflow
+    st = pool.get_stats()
+    print(f"@queue_depth={st['queue_depth']}")
+    print(f"@drops={st['drops']}")
+    print(f"@overflow_events={st['overflow_events']}")
+    print(f"@telemetry={counters()}")
+    GATE.set()
+    wait_until(lambda: len(RESULTS) == 2)
+    await asyncio.sleep(0.05)
+    pool.stop()
+    print(f"@results={RESULTS}")
+    print("@streams=" + json.dumps(pool.get_stats()["streams"]))
+import json
+asyncio.run(main())
+"""
+    )
+    assert out is not None
+    assert out["queue_depth"] == "1"
+    assert out["drops"] == "4"
+    assert out["overflow_events"] == "1"
+    assert out["telemetry"] == "(4, 1)"
+    assert out["results"] == "[0.0, 5.0]"  # frames 1..4 were dropped
+    s0 = _streams(out)["stream_0"]
+    assert s0 == {
+        "submitted": 6,
+        "dropped": 4,
+        "overflow_events": 1,
+        "dequeued": 2,
+        "discarded_on_stop": 0,
+        "last_dequeued_seq": 6,
+        "gaps": 1,
+        "gap_frames": 4,
+        "queued": 0,
+    }
+
+
+def test_repeated_overflows_accumulate_frames_and_events() -> None:
+    out = _run(
+        _TELEMETRY
+        + """
+async def main():
+    MODE["process"] = "block"
+    pool = make_counted_pool(1)
+    await pool.start()
+    pool.put_frame("stream_0", frame(), 0.0)
+    wait_until(lambda: pool.get_stats()["queue_depth"] == 0)
+    for i in range(1, 10):                           # 9 more: two overflows
+        pool.put_frame("stream_0", frame(), float(i))
+    st = pool.get_stats()
+    print(f"@drops={st['drops']}")
+    print(f"@overflow_events={st['overflow_events']}")
+    print(f"@queue_depth={st['queue_depth']}")
+    print(f"@telemetry={counters()}")
+    pool.reset_stats()
+    st = pool.get_stats()
+    print(f"@after_reset={st['drops']},{st['overflow_events']},{st['streams']['stream_0']['dropped']}")
+    GATE.set()
+    wait_until(lambda: pool.get_stats()["queue_depth"] == 0)
+    pool.stop()
+asyncio.run(main())
+"""
+    )
+    assert out is not None
+    # 1..4 fill, 5 drains 4; 6..8 fill to 4, 9 drains 4.
+    assert out["drops"] == "8"
+    assert out["overflow_events"] == "2"
+    assert out["queue_depth"] == "1"
+    assert out["telemetry"] == "(8, 2)"
+    # reset_stats() resets the totals; per-stream counts are kept.
+    assert out["after_reset"] == "0,0,8"
+
+
+def test_discarded_on_stop_is_not_an_overflow_drop() -> None:
+    out = _run(
+        _TELEMETRY
+        + """
+async def main():
+    MODE["process"] = "block"
+    pool = make_counted_pool(1)
+    await pool.start()
+    pool.put_frame("stream_0", frame(), 0.0)
+    wait_until(lambda: pool.get_stats()["queue_depth"] == 0)
+    for i in range(1, 4):
+        pool.put_frame("stream_0", frame(), float(i))  # 3 queued, no overflow
+    try:
+        pool.stop(timeout=0.5)
+    except d.WorkbenchPoolStopTimeout:
+        pass
+    GATE.set()
+    wait_until(lambda: not any(w.is_alive() for w in pool._workers))
+    pool.stop()
+    st = pool.get_stats()
+    print(f"@drops={st['drops']}")
+    print(f"@overflow_events={st['overflow_events']}")
+    print(f"@discarded_on_stop={st['discarded_on_stop']}")
+    print(f"@telemetry={counters()}")
+    print("@streams=" + json.dumps(st["streams"]))
+import json
+asyncio.run(main())
+"""
+    )
+    assert out is not None
+    assert (out["drops"], out["overflow_events"], out["discarded_on_stop"]) == (
+        "0",
+        "0",
+        "3",
+    )
+    assert out["telemetry"] == "(0, 0)"
+    s0 = _streams(out)["stream_0"]
+    assert s0["submitted"] == 4 and s0["dequeued"] == 1
+    assert s0["dropped"] == 0 and s0["discarded_on_stop"] == 3
+
+
+def test_concurrent_producers_never_lose_an_unrecorded_frame() -> None:
+    """8 producer threads per stream against a slow worker. Before the fix a
+    racing producer could refill the queue between the drain and the final
+    put_nowait (queue.Full escaped put_frame), and every overflow counted 1.
+
+    After stop() every frame is accounted for exactly once, per stream:
+    submitted == dequeued + dropped + discarded_on_stop + queued; the totals
+    and the telemetry agree with the per-stream counts.
+    """
+    out = _run(
+        _TELEMETRY
+        + """
+import json
+orig = FakeWorkbench.process_frame
+def slow(self, *a, **kw):
+    time.sleep(0.001)
+    return orig(self, *a, **kw)
+FakeWorkbench.process_frame = slow
+ERRORS = []
+async def main():
+    pool = make_counted_pool(2)
+    await pool.start()
+    def produce(sid, k):
+        for i in range(400):
+            try:
+                pool.put_frame(sid, frame(), float(k * 1000 + i))
+            except Exception as e:
+                ERRORS.append(type(e).__name__)
+    threads = [
+        threading.Thread(target=produce, args=(f"stream_{j % 2}", j)) for j in range(16)
+    ]
+    for t in threads:
+        t.start()
+    for t in threads:
+        t.join()
+    pool.stop()
+    st = pool.get_stats()
+    print(f"@errors={sorted(set(ERRORS))}")
+    print(f"@drops={st['drops']}")
+    print(f"@overflow_events={st['overflow_events']}")
+    print(f"@discarded_on_stop={st['discarded_on_stop']}")
+    print(f"@telemetry={list(counters())}")
+    print("@streams=" + json.dumps(st["streams"]))
+    print(f"@thread_errors={THREAD_ERRORS}")
+asyncio.run(main())
+""",
+        timeout=120.0,
+    )
+    assert out is not None
+    assert out["errors"] == "[]"
+    assert out["thread_errors"] == "[]"
+    streams = _streams(out)
+    for sid, c in streams.items():
+        assert c["submitted"] == 8 * 400, sid
+        assert c["queued"] == 0, sid
+        assert (
+            c["submitted"] == c["dequeued"] + c["dropped"] + c["discarded_on_stop"]
+        ), (sid, c)
+        # every frame identity the worker skipped was dropped or discarded
+        assert c["gap_frames"] <= c["dropped"] + c["discarded_on_stop"], (sid, c)
+        assert c["last_dequeued_seq"] <= c["submitted"], (sid, c)
+    total_dropped = sum(c["dropped"] for c in streams.values())
+    total_events = sum(c["overflow_events"] for c in streams.values())
+    assert total_dropped > 0 and total_events > 0  # the race was exercised
+    assert int(out["drops"]) == total_dropped
+    assert int(out["overflow_events"]) == total_events
+    assert json.loads(out["telemetry"]) == [total_dropped, total_events]
+    assert int(out["discarded_on_stop"]) == sum(
+        c["discarded_on_stop"] for c in streams.values()
+    )
+    # one overflow drops at most the queue capacity
+    assert total_dropped <= 4 * total_events
+
+
+def test_put_after_stop_is_refused_not_counted() -> None:
+    """A put refused because the pool stopped is not a drop or a discard."""
+    out = _run(
+        _TELEMETRY
+        + """
+async def main():
+    pool = make_counted_pool(1)
+    await pool.start()
+    pool.stop()
+    try:
+        pool.put_frame("stream_0", frame(), 0.0)
+    except d.WorkbenchPoolNotRunning:
+        print("@refused=yes")
+    st = pool.get_stats()
+    c = st["streams"]["stream_0"]
+    print(f"@counts={c['submitted']},{c['dropped']},{c['discarded_on_stop']},{st['drops']}")
+asyncio.run(main())
+"""
+    )
+    assert out == {"refused": "yes", "counts": "0,0,0,0"}
+
+
+def test_stop_bounds_a_producer_holding_the_stream_lock_and_can_retry() -> None:
+    """Admission can be paused even after every worker has ended.
+
+    stop must report a timeout and retain its batcher, rather than wait for
+    that producer indefinitely. A later admission is refused, and retrying
+    stop accounts for the frame admitted before stopping exactly once.
+    """
+    out = _run(
+        _TELEMETRY
+        + """
+import json
+async def main():
+    pool = make_counted_pool(1)
+    await pool.start()
+    inside = threading.Event()
+    resume = threading.Event()
+    q = pool._queues[0]
+    original_put = q.put_nowait
+    def paused_put(item):
+        inside.set()
+        assert resume.wait(5.0)
+        original_put(item)
+    q.put_nowait = paused_put
+    errors = []
+    def produce(ts):
+        try:
+            pool.put_frame("stream_0", frame(), ts)
+        except Exception as e:
+            errors.append(type(e).__name__)
+    admitted = threading.Thread(target=produce, args=(0.0,))
+    admitted.start()
+    assert inside.wait(5.0)
+    # This producer waits for the same stream lock, but must not be admitted
+    # once the pool enters STOPPING.
+    checked = threading.Event()
+    original_check = pool._check_running
+    def observe_check():
+        original_check()
+        if threading.current_thread().name == "late-producer":
+            checked.set()
+    pool._check_running = observe_check
+    refused = threading.Thread(target=produce, args=(1.0,), name="late-producer")
+    refused.start()
+    assert checked.wait(5.0)
+    release = threading.Timer(1.5, resume.set)
+    release.start()  # bound the diagnostic even if stop's timeout is broken
+    t0 = time.monotonic()
+    outcome = "returned"
+    try:
+        pool.stop(timeout=0.15)
+    except d.WorkbenchPoolStopTimeout:
+        outcome = "timeout"
+    print(f"@outcome={outcome}")
+    print(f"@bounded={time.monotonic() - t0 < 0.8}")
+    print(f"@state={pool.state.value}")
+    print(f"@batcher_kept={pool._batcher is FakeBatcher.last and not FakeBatcher.last.down}")
+    resume.set()
+    release.cancel()
+    release.join(5.0)
+    admitted.join(5.0)
+    refused.join(5.0)
+    assert not admitted.is_alive() and not refused.is_alive()
+    pool.stop()
+    first = pool.get_stats()
+    pool.stop()
+    print(f"@idempotent={first == pool.get_stats()}")
+    print(f"@errors={errors}")
+    print(f"@discarded={first['discarded_on_stop']}")
+    print(f"@timeouts={first['stop_timeouts']}")
+    print(f"@telemetry={counters()}")
+    print("@streams=" + json.dumps(first["streams"]))
+asyncio.run(main())
+"""
+    )
+    assert out is not None
+    assert out["outcome"] == "timeout"
+    assert out["bounded"] == "True"
+    assert out["state"] == "stopping"
+    assert out["batcher_kept"] == "True"
+    assert out["idempotent"] == "True"
+    assert out["errors"] == "['WorkbenchPoolNotRunning']"
+    assert out["discarded"] == "1" and out["timeouts"] == "1"
+    assert out["telemetry"] == "(0, 0)"
+    c = _streams(out)["stream_0"]
+    assert c["submitted"] == c["discarded_on_stop"] == 1
+    assert c["dequeued"] == c["dropped"] == c["queued"] == 0
+
+
+def test_restart_keeps_frame_identity_and_exposes_stop_discard_gap() -> None:
+    out = _run(
+        _TELEMETRY
+        + """
+import json
+async def main():
+    MODE["process"] = "block"
+    pool = make_counted_pool(1)
+    await pool.start()
+    pool.put_frame("stream_0", frame(), 0.0)
+    assert wait_until(lambda: pool.get_stats()["streams"]["stream_0"]["dequeued"] == 1)
+    for ts in (1.0, 2.0, 3.0):
+        pool.put_frame("stream_0", frame(), ts)
+    try:
+        pool.stop(timeout=0.05)
+    except d.WorkbenchPoolStopTimeout:
+        pass
+    GATE.set()
+    assert wait_until(lambda: not any(w.is_alive() for w in pool._workers))
+    pool.stop()
+    await pool.start()
+    pool.put_frame("stream_0", frame(), 4.0)
+    assert wait_until(lambda: pool.get_stats()["streams"]["stream_0"]["dequeued"] == 2)
+    pool.stop()
+    st = pool.get_stats()
+    print("@streams=" + json.dumps(st["streams"]))
+    print(f"@discarded={st['discarded_on_stop']}")
+    print(f"@telemetry={counters()}")
+asyncio.run(main())
+"""
+    )
+    assert out is not None
+    c = _streams(out)["stream_0"]
+    assert c == {
+        "submitted": 5,
+        "dropped": 0,
+        "overflow_events": 0,
+        "dequeued": 2,
+        "discarded_on_stop": 3,
+        "last_dequeued_seq": 5,
+        "gaps": 1,
+        "gap_frames": 3,
+        "queued": 0,
+    }
+    assert out["discarded"] == "3"
+    assert out["telemetry"] == "(0, 0)"
+
+
+def test_partial_stop_drain_is_counted_before_another_stream_times_out() -> None:
+    out = _run(
+        _TELEMETRY
+        + """
+import json
+async def main():
+    MODE["process"] = "block"
+    pool = make_counted_pool(2)
+    await pool.start()
+    pool.put_frame("stream_0", frame(), 0.0)
+    assert wait_until(lambda: pool.get_stats()["streams"]["stream_0"]["dequeued"] == 1)
+    pool.put_frame("stream_0", frame(), 1.0)
+    pool.put_frame("stream_0", frame(), 2.0)
+    inside = threading.Event()
+    resume = threading.Event()
+    q = pool._queues[1]
+    original_put = q.put_nowait
+    def paused_put(item):
+        inside.set()
+        assert resume.wait(5.0)
+        original_put(item)
+    q.put_nowait = paused_put
+    producer = threading.Thread(target=pool.put_frame, args=("stream_1", frame(), 3.0))
+    producer.start()
+    assert inside.wait(5.0)
+    def release_worker():
+        assert wait_until(lambda: pool.state is d.PoolState.STOPPING)
+        GATE.set()
+    worker_release = threading.Thread(target=release_worker)
+    worker_release.start()
+    release = threading.Timer(1.5, resume.set)
+    release.start()
+    outcome = "returned"
+    try:
+        pool.stop(timeout=0.2)
+    except d.WorkbenchPoolStopTimeout:
+        outcome = "timeout"
+    print(f"@outcome={outcome}")
+    print(f"@partial_discarded={pool._discarded_on_stop}")
+    resume.set()
+    release.cancel()
+    release.join(5.0)
+    producer.join(5.0)
+    worker_release.join(5.0)
+    assert not producer.is_alive() and not worker_release.is_alive()
+    pool.stop()
+    st = pool.get_stats()
+    print(f"@discarded={st['discarded_on_stop']}")
+    print("@streams=" + json.dumps(st["streams"]))
+asyncio.run(main())
+"""
+    )
+    assert out is not None
+    assert out["outcome"] == "timeout"
+    assert out["partial_discarded"] == "2"
+    assert out["discarded"] == "3"
+    streams = _streams(out)
+    assert streams["stream_0"]["discarded_on_stop"] == 2
+    assert streams["stream_1"]["discarded_on_stop"] == 1
+    for c in streams.values():
+        assert c["submitted"] == c["dequeued"] + c["discarded_on_stop"]
+        assert c["queued"] == c["dropped"] == 0
+
+
+@pytest.mark.gpu
+def test_cuda_overflow_counts_frames_and_delivers_the_latest_frame() -> None:
+    """Real CUDA Workbench and batcher; only TRT inference is replaced.
+
+    Hold the first inference while overflowing its stream, then let both
+    frames finish. This exercises F02 on the actual CUDA processing path;
+    it does not qualify a model, throughput or online deployment.
+    """
+    from tests.unit.test_workbench_pool_gpu_contract_538 import (
+        _need_native,
+        _run as run_gpu,
+    )
+
+    _need_native()
+    out = run_gpu(
+        """
+import json
+from saccade.perception.online_telemetry import OnlineTelemetry
+async def main():
+    telemetry = OnlineTelemetry()
+    pool = make_pool(1, telemetry=telemetry)
+    PLAN["gate"] = threading.Event()
+    await pool.start()
+    pool.put_frame("stream_0", frame(0), 0.0)
+    await until(IN_INFER.is_set)
+    for i in range(1, 6):
+        pool.put_frame("stream_0", frame(i * 10), float(i))
+    st = pool.get_stats()
+    print(f"@pending={st['drops']},{st['overflow_events']},{st['queue_depth']}")
+    PLAN["gate"].set()
+    await until(lambda: len(RESULTS) == 2)
+    pool.stop()
+    st = pool.get_stats()
+    print("@streams=" + json.dumps(st["streams"]))
+    print(f"@timestamps={[r['ts'] for r in RESULTS]}")
+    print(f"@inputs_ok={len(SEEN) == 2 and abs(SEEN[0]) < 1e-5 and abs(SEEN[1] - 50.0/255.0) < 1e-3}")
+    print(f"@telemetry={st['workbench_drops']},{st['workbench_overflow_events']}")
+    print(f"@state={st['state']}")
+    print(f"@thread_errors={THREAD_ERRORS}")
+asyncio.run(main())
+done()
+"""
+    )
+    assert out["pending"] == "4,1,1"
+    assert out["timestamps"] == "[0.0, 5.0]"
+    assert out["inputs_ok"] == "True"
+    assert out["telemetry"] == "4,1"
+    assert out["state"] == "stopped"
+    assert out["thread_errors"] == "[]"
+    c = _streams(out)["stream_0"]
+    assert c["submitted"] == 6 and c["dequeued"] == 2
+    assert c["dropped"] == c["gap_frames"] == 4
+    assert c["last_dequeued_seq"] == 6 and c["gaps"] == 1
+    assert c["queued"] == c["discarded_on_stop"] == 0