feat(types): extend GeneratedQuestion with skill_target & difficulty_steps

- Add skill_target (str | None) and difficulty_steps (int | None) fields
  to GeneratedQuestion dataclass with field(default=None)
- Update loader.py to pass new fields from JSON (backward-compatible)
- Update pools.py _q_to_dict/_dict_to_q for serialization compat
- Add question_gen_v2 config section to default.yaml
- Add comprehensive test coverage (7 tests)

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

app/harness/pools.py

@@ -139,6 +139,8 @@ def _q_to_dict(q: GeneratedQuestion) -> dict:
         "answer": q.answer,
         "source_nodes": list(q.source_nodes),
         "difficulty": q.difficulty,
+        "skill_target": q.skill_target,
+        "difficulty_steps": q.difficulty_steps,
     }
 
 
@@ -160,6 +162,8 @@ def _dict_to_q(d: dict) -> GeneratedQuestion:
         answer=d["answer"],
         source_nodes=tuple(d.get("source_nodes", ())),
         difficulty=d.get("difficulty", "medium"),
+        skill_target=d.get("skill_target"),
+        difficulty_steps=d.get("difficulty_steps"),
     )
 
 

app/question_gen/loader.py

@@ -46,6 +46,8 @@ def load_benchmark(questions_dir: Path) -> list[GeneratedQuestion]:
                     answer=qa["answer"],
                     source_nodes=tuple(qa.get("source_nodes", ())),
                     difficulty=qa.get("difficulty", _LEGACY_DEFAULT_DIFFICULTY),
+                    skill_target=qa.get("skill_target"),
+                    difficulty_steps=qa.get("difficulty_steps"),
                 )
             )
     return results

config/default.yaml

@@ -69,3 +69,25 @@ harness:
   eval_min_per_class: 2
   early_stop_patience: 8
   use_slow_momentum: true
+
+# ── 出题管线 v2 ──
+question_gen_v2:
+  family_ratios:
+    retrieval: 0.30
+    reasoning: 0.25
+    enumeration: 0.20
+    visual: 0.15
+    spatial: 0.10
+  gate:
+    blind_answer_model: "gpt-4.1-mini"
+    leak_test_model: "gpt-4.1-mini"
+    key_verify_model: "gpt-4.1-mini"
+    multi_true_model: "gpt-4.1-mini"
+  dedup_threshold: 0.85
+  retry_limit: 3
+  heavy_sample_rate: 0.15
+  heavy_agent_model: "gpt-4.1-mini"
+  output_dir: "store/questions/generated-v2"
+  per_type: 20            # 12 类 x 20 = 240 题（设计 §3 硬约束）
+  concurrency: 4
+  seed: 42

core/types.py

@@ -2,7 +2,7 @@
 
 from __future__ import annotations
 
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 
 
 @dataclass(frozen=True)
@@ -41,6 +41,8 @@ class GeneratedQuestion:
         answer: 正确答案字母（如 "B"）。
         source_nodes: 来源节点 ID 元组。
         difficulty: 难度等级。
+        skill_target: 目标技能标识（v2 出题管线使用，None 表示未指定）。
+        difficulty_steps: 推理步数估计（v2 出题管线使用，None 表示未指定）。
     """
 
     question_id: str
@@ -51,3 +53,5 @@ class GeneratedQuestion:
     answer: str
     source_nodes: tuple[str, ...]
     difficulty: str
+    skill_target: str | None = field(default=None)
+    difficulty_steps: int | None = field(default=None)

tests/unit/test_types_v2.py

@@ -0,0 +1,173 @@
+"""GeneratedQuestion v2 类型扩展测试。
+
+验证 skill_target 和 difficulty_steps 新字段的默认值、显式赋值、
+frozen 不可变性，以及 loader 的前后向兼容性。
+"""
+
+from __future__ import annotations
+
+import json
+from typing import TYPE_CHECKING
+
+import pytest
+
+if TYPE_CHECKING:
+    from pathlib import Path
+
+from core.types import GeneratedQuestion
+
+
+class TestGeneratedQuestionV2:
+    """新增字段的单元测试。"""
+
+    def test_new_fields_default_none(self) -> None:
+        """无显式赋值时，skill_target 和 difficulty_steps 默认为 None。"""
+        q = GeneratedQuestion(
+            question_id="q1",
+            video_id="v1",
+            task_type="TN",
+            question="What happens?",
+            options=("A. yes", "B. no", "C. maybe", "D. none"),
+            answer="A",
+            source_nodes=("n1",),
+            difficulty="medium",
+        )
+        assert q.skill_target is None
+        assert q.difficulty_steps is None
+
+    def test_new_fields_explicit(self) -> None:
+        """显式赋值时字段正确存储。"""
+        q = GeneratedQuestion(
+            question_id="q2",
+            video_id="v2",
+            task_type="AR",
+            question="Why did this occur?",
+            options=("A. cause1", "B. cause2", "C. cause3", "D. cause4"),
+            answer="B",
+            source_nodes=("n2", "n3"),
+            difficulty="hard",
+            skill_target="M1",
+            difficulty_steps=5,
+        )
+        assert q.skill_target == "M1"
+        assert q.difficulty_steps == 5
+
+    def test_frozen_immutable(self) -> None:
+        """frozen=True 保证新字段不可修改。"""
+        q = GeneratedQuestion(
+            question_id="q3",
+            video_id="v3",
+            task_type="EN",
+            question="How many items?",
+            options=("A. 1", "B. 2", "C. 3", "D. 4"),
+            answer="C",
+            source_nodes=("n4",),
+            difficulty="easy",
+            skill_target="M2",
+            difficulty_steps=3,
+        )
+        with pytest.raises(AttributeError):
+            q.skill_target = "M3"  # type: ignore[misc]
+        with pytest.raises(AttributeError):
+            q.difficulty_steps = 7  # type: ignore[misc]
+
+
+class TestLoaderV2Compat:
+    """loader.py 前后向兼容性测试。"""
+
+    def test_load_old_format_json(self, tmp_path: Path) -> None:
+        """旧格式 JSON（无新字段）加载后新字段为 None。"""
+        from app.question_gen.loader import load_benchmark
+
+        data = [
+            {
+                "question_id": "old_q1",
+                "task_type": "TN",
+                "question": "What is shown?",
+                "options": ["A. cat", "B. dog", "C. bird", "D. fish"],
+                "answer": "A",
+                "source_nodes": ["seg_01"],
+                "difficulty": "easy",
+            }
+        ]
+        json_file = tmp_path / "video_old.json"
+        json_file.write_text(json.dumps(data), encoding="utf-8")
+
+        questions = load_benchmark(tmp_path)
+        assert len(questions) == 1
+        q = questions[0]
+        assert q.skill_target is None
+        assert q.difficulty_steps is None
+        assert q.video_id == "video_old"
+
+    def test_load_new_format_json(self, tmp_path: Path) -> None:
+        """新格式 JSON（含新字段）正确加载。"""
+        from app.question_gen.loader import load_benchmark
+
+        data = [
+            {
+                "question_id": "new_q1",
+                "task_type": "AR",
+                "question": "Why did X happen?",
+                "options": ["A. r1", "B. r2", "C. r3", "D. r4"],
+                "answer": "B",
+                "source_nodes": ["seg_02", "seg_03"],
+                "difficulty": "hard",
+                "skill_target": "M3",
+                "difficulty_steps": 7,
+            }
+        ]
+        json_file = tmp_path / "video_new.json"
+        json_file.write_text(json.dumps(data), encoding="utf-8")
+
+        questions = load_benchmark(tmp_path)
+        assert len(questions) == 1
+        q = questions[0]
+        assert q.skill_target == "M3"
+        assert q.difficulty_steps == 7
+
+
+class TestPoolsSerializationV2:
+    """pools.py _q_to_dict / _dict_to_q 新字段兼容性测试。"""
+
+    def test_roundtrip_with_new_fields(self) -> None:
+        """新字段经过序列化反序列化后保持一致。"""
+        from app.harness.pools import _dict_to_q, _q_to_dict
+
+        q = GeneratedQuestion(
+            question_id="rt_q1",
+            video_id="v_rt",
+            task_type="VS",
+            question="Where is the object?",
+            options=("A. left", "B. right", "C. top", "D. bottom"),
+            answer="A",
+            source_nodes=("node_1",),
+            difficulty="medium",
+            skill_target="M5",
+            difficulty_steps=10,
+        )
+        d = _q_to_dict(q)
+        assert d["skill_target"] == "M5"
+        assert d["difficulty_steps"] == 10
+
+        restored = _dict_to_q(d)
+        assert restored.skill_target == "M5"
+        assert restored.difficulty_steps == 10
+
+    def test_roundtrip_without_new_fields(self) -> None:
+        """旧字典（无新字段）反序列化时新字段默认为 None。"""
+        from app.harness.pools import _dict_to_q
+
+        d = {
+            "question_id": "legacy_q1",
+            "video_id": "v_legacy",
+            "task_type": "TN",
+            "question": "What?",
+            "options": ["A", "B", "C", "D"],
+            "answer": "A",
+            "source_nodes": ["n1"],
+            "difficulty": "medium",
+        }
+        q = _dict_to_q(d)
+        assert q.skill_target is None
+        assert q.difficulty_steps is None