V6 expert generation validation: gemma4:e2b 3/3 PASS

- gemma3:4b: 1/3 (small model struggles with complex JSON generation)
- gemma4:e2b: 3/3 (FastAPI CRUD, pytest fixture, DB migration all pass)
- All generated experts have valid structure, keywords, and pipelines

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

STATUS.md

@@ -57,7 +57,7 @@ MVP 流水线 + 6 步搜索增强 + 专家注册表 + 3 层记忆 + 飞轮自动
 | V3 Locator精度 | 文件级 90%，函数级 20% | 函数级已加 few-shot 优化，待更大模型验证 |
 | V4 搜索模块 | 意图4/4, DDG 4/4, Fetch 3/4, 压缩4/4 | trafilatura+bs4, 耗时略超15s(LLM瓶颈) |
 | V5 AST Locator | 脚本就绪，待运行 | A组(LLM猜测) vs B组(tree-sitter stub) |
-| V6 专家生成质量 | 脚本就绪，待运行 | 3组×5轨迹，需要Ollama在线 |
+| V6 专家生成质量 | gemma3:4b 1/3, gemma4:e2b 3/3 PASS | 小模型JSON生成弱，大模型全过 |
 | E2E 单文件 | 通过 | gemma3:4b 5.7s / gemma4:e2b 64.9s，5/5 测试 |
 | E2E 多文件 | 通过 | gemma3:4b 7.7s，password leak 跨2文件，3/3 测试 |
 | gemma4:e2b Gate | 100% 类型准确率（含 office） | 比 gemma3:4b 的 67% 大幅提升，但慢 10x |
@@ -270,7 +270,7 @@ kaiwu/
 - [x] Windows cmd原生验证（Python import + pytest 24/24 通过）
 - [x] 红线约束代码review（10/10 CORE 全部 PASS）
 - [ ] V5 AST Locator实际验证（需要tree-sitter + Ollama）
-- [ ] V6 专家生成质量实际验证（需要Ollama）
+- [x] V6 专家生成质量验证（gemma4:e2b 3/3 PASS，gemma3:4b 1/3）
 - [ ] 预置专家20任务验证（Step 16）
 
 ### 已知限制

kaiwu/validation/v6_conclusion.json

@@ -0,0 +1,104 @@
+{
+  "status": "completed",
+  "model": "gemma4:e2b",
+  "groups_passed": 3,
+  "groups_total": 3,
+  "overall_pass": true,
+  "groups": {
+    "fastapi_crud": {
+      "label": "FastAPI CRUD endpoint",
+      "generated": true,
+      "expert_name": "FastAPICodeGeneratorExpert",
+      "expert_keywords": [
+        "FastAPI",
+        "CRUD接口",
+        "API实现",
+        "数据管理",
+        "模型生成"
+      ],
+      "expert_pipeline": [
+        "generator",
+        "verifier"
+      ],
+      "system_prompt_len": 604,
+      "structure_checks": {
+        "has_name": true,
+        "has_trigger_keywords": true,
+        "has_system_prompt": true,
+        "has_pipeline": true,
+        "pipeline_valid": true,
+        "system_prompt_nonempty": true,
+        "system_prompt_has_content": true,
+        "confidence_reasonable": true,
+        "all_passed": true
+      },
+      "keyword_coverage": 0.6,
+      "elapsed_s": 54.7,
+      "passed": true
+    },
+    "pytest_fixture": {
+      "label": "pytest fixture",
+      "generated": true,
+      "expert_name": "PytestFixtureGenerator",
+      "expert_keywords": [
+        "pytest fixture",
+        "pytest conftest",
+        "test setup",
+        "fixture creation",
+        "test teardown",
+        "mocking fixture"
+      ],
+      "expert_pipeline": [
+        "generator",
+        "verifier"
+      ],
+      "system_prompt_len": 592,
+      "structure_checks": {
+        "has_name": true,
+        "has_trigger_keywords": true,
+        "has_system_prompt": true,
+        "has_pipeline": true,
+        "pipeline_valid": true,
+        "system_prompt_nonempty": true,
+        "system_prompt_has_content": true,
+        "confidence_reasonable": true,
+        "all_passed": true
+      },
+      "keyword_coverage": 1.0,
+      "elapsed_s": 31.1,
+      "passed": true
+    },
+    "db_migration": {
+      "label": "database migration",
+      "generated": true,
+      "expert_name": "DatabaseMigrationCodegenExpert",
+      "expert_keywords": [
+        "写迁移脚本",
+        "Alembic",
+        "数据库迁移",
+        "schema 变更",
+        "表结构修改",
+        "模型迁移"
+      ],
+      "expert_pipeline": [
+        "generator",
+        "verifier"
+      ],
+      "system_prompt_len": 592,
+      "structure_checks": {
+        "has_name": true,
+        "has_trigger_keywords": true,
+        "has_system_prompt": true,
+        "has_pipeline": true,
+        "pipeline_valid": true,
+        "system_prompt_nonempty": true,
+        "system_prompt_has_content": true,
+        "confidence_reasonable": true,
+        "all_passed": true
+      },
+      "keyword_coverage": 0.4,
+      "elapsed_s": 32.6,
+      "passed": true
+    }
+  }
+}