diff --git a/app/harness/observation.py b/app/harness/observation.py
index b1b9d83..c8e8b5a 100644
--- a/app/harness/observation.py
+++ b/app/harness/observation.py
@@ -348,6 +348,9 @@ def write_gate_evidence(
             question_id 字段承载 **unit_id**（single=question_id，pair=pair_id）——
             逐题明细在 predictions 表溯源，按 pair_id join 真实 question 表会 join 不上。
 
+    返回:
+        无。
+
     关键实现:
         逐行 insert（非 insert_many），保证每行独立事务。
     """
diff --git a/app/harness/validate.py b/app/harness/validate.py
index d16dbe6..b2228c0 100644
--- a/app/harness/validate.py
+++ b/app/harness/validate.py
@@ -1246,9 +1246,12 @@ async def validate_skills_concurrent(
 ) -> dict[str, ValidationOutcome]:
     """连续并发 gate:多题型全部臂共享题槽并发,统计按阶梯序前缀有序推进。
 
-    发射顺序 = 题型 round-robin × 题型内阶梯序(base 先 cand 后);题型过线即
-    冻结,其排队任务启动时自查冻结标志撤销,in-flight 结果不计入(τ 之后样本,
-    合法丢弃)。全部题型判定后统一组装 ValidationOutcome。
+    关键实现细节:
+        发射顺序 = 题型 round-robin × 题型内阶梯序(base 先 cand 后);题型过线
+        即冻结,其排队任务启动时自查冻结标志撤销,in-flight 结果不计入(τ 之后
+        样本,合法丢弃);候选目录逐个物化即登记、统一 finally 清理(中途失败不
+        泄漏);任一任务异常先 cancel+排水其余任务再向上传播;全部题型判定后
+        统一经 _finalize_outcome 组装。
 
     参数:
         workspace_dir: workspace 根目录(候选物化用)。
diff --git a/tests/unit/test_gate_concurrent.py b/tests/unit/test_gate_concurrent.py
index 38acd42..cad1bda 100644
--- a/tests/unit/test_gate_concurrent.py
+++ b/tests/unit/test_gate_concurrent.py
@@ -16,6 +16,14 @@ from tests.unit.test_gate_prefix import _PARAMS, _mk_unit
 from tests.unit.test_gate_unit_arm import _FakeLog
 
 
+class _FakeInferenceResult:
+    """推理结果桩:只承载编排器消费的 run_id 与 total 两个字段。"""
+
+    def __init__(self, run_id: str, total: int) -> None:
+        self.run_id = run_id
+        self.total = total
+
+
 def _mk_spec(task_type: str, slug: str, n: int) -> GateSpec:
     """构造 n 个 single 单元的 gate 规格(unit_id 形如 <slug>-q<i>)。"""
     return GateSpec(
@@ -31,11 +39,6 @@ def _mk_spec(task_type: str, slug: str, n: int) -> GateSpec:
 def _scripted_inference(log: _FakeLog, script: dict[str, tuple[bool, float]]):
     """脚本化假推理:按 question_id+臂 决定 (对错, 延迟秒),制造乱序到达。"""
 
-    class _R:
-        def __init__(self, run_id: str, total: int) -> None:
-            self.run_id = run_id
-            self.total = total
-
     async def _run(questions, *, run_id: str, skills_dir: Path):
         arm = "cand" if run_id.endswith("_cand") else "base"
         correct, delay = script[f"{questions[0].question_id}|{arm}"]
@@ -51,7 +54,7 @@ def _scripted_inference(log: _FakeLog, script: dict[str, tuple[bool, float]]):
                     "steps_json": "[]",
                 }
             )
-        return _R(run_id, len(questions))
+        return _FakeInferenceResult(run_id, len(questions))
 
     return _run
 
@@ -130,10 +133,6 @@ async def test_all_infra_raises(tmp_path, monkeypatch) -> None:
     spec = _mk_spec("Action Reasoning", "action-reasoning", 2)
     log = _FakeLog()
 
-    class _R:
-        def __init__(self, run_id, total):
-            self.run_id, self.total = run_id, total
-
     async def _infra_run(questions, *, run_id, skills_dir):
         for q in questions:
             log.rows.append(
@@ -146,7 +145,7 @@ async def test_all_infra_raises(tmp_path, monkeypatch) -> None:
                     "steps_json": "[]",
                 }
             )
-        return _R(run_id, len(questions))
+        return _FakeInferenceResult(run_id, len(questions))
 
     monkeypatch.setattr(
         "app.harness.validate.materialize_candidate_skill",
@@ -217,10 +216,6 @@ async def test_guard_raise_cancels_remaining_tasks(tmp_path, monkeypatch) -> Non
     log = _FakeLog()
     hang = asyncio.Event()  # 永不 set:B 型推理只能靠取消收束
 
-    class _R:
-        def __init__(self, run_id, total):
-            self.run_id, self.total = run_id, total
-
     async def _run(questions, *, run_id, skills_dir):
         if "counting-problem" in run_id:
             await hang.wait()
@@ -235,7 +230,7 @@ async def test_guard_raise_cancels_remaining_tasks(tmp_path, monkeypatch) -> Non
                     "steps_json": "[]",
                 }
             )
-        return _R(run_id, len(questions))
+        return _FakeInferenceResult(run_id, len(questions))
 
     monkeypatch.setattr(
         "app.harness.validate.materialize_candidate_skill",