feat(kb-workflow): 添加严格失败判断逻辑

- kb-deep-analyzer: 新增判断逻辑，只有AI真正完成分析才算成功
- 失败条件: summary以'共'开头、topics为空、full_analysis为None
- kb-workflow: 明确深度分析失败则整个流程失败
- 禁止降级处理或使用模板'假装成功'

skills/kb-deep-analyzer/deep_analyzer.py

@@ -444,7 +444,7 @@ class DeepAnalyzer:
                 result = self._analyze_chunks_concurrent(
                     title, text, duration, segments, metadata,
                     batch_size=batch_size,
-                    on_batch_complete=on_batch_complete
+                    on_segment_complete=on_batch_complete
                 )
             elif duration < self.SHORT_VIDEO_THRESHOLD:
                 print(f"[DeepAnalyzer] 使用轻量分析策略 (时长 < 10分钟)")
@@ -671,6 +671,7 @@ class DeepAnalyzer:
         segments: list = None,
         metadata: Dict = None,
         max_concurrent: int = 3,
+        batch_size: int = 3,
         on_segment_complete: callable = None
     ) -> AnalysisResult:
         """
@@ -787,8 +788,8 @@ class DeepAnalyzer:
 
             # 回调通知当前批次完成
             batch_summaries = [batch_results[i] for i in range(batch_idx, batch_end) if i in batch_results]
-            if on_batch_complete:
-                on_batch_complete(batch_summaries)
+            if on_segment_complete:
+                on_segment_complete(batch_summaries)
 
             all_summaries.extend(batch_summaries)
 
@@ -1627,6 +1628,32 @@ def main():
         f.write(markdown_content)
 
     # 统一输出格式
+    # 检查是否真正使用 AI 完成了分析
+    # 如果 summary 以"共"开头或 topics 为空，通常是降级处理的默认内容
+    is_real_analysis = (
+        result.summary and 
+        not result.summary.startswith("共") and
+        len(result.main_topics) > 0 and
+        len(result.key_insights) > 0 and
+        result.full_analysis is not None
+    )
+
+    if not is_real_analysis:
+        # 未真正使用 AI 分析，属于执行失败
+        output = {
+            "success": False,
+            "error": "深度分析未能完成。可能是 AI 调用失败或返回内容不完整。",
+            "message": "执行失败：未使用正确的 AI 完整分析字幕内容",
+            "stats": {
+                "summary_length": len(result.summary) if result.summary else 0,
+                "topics_count": len(result.main_topics),
+                "insights_count": len(result.key_insights),
+                "is_real_analysis": False
+            }
+        }
+        print(json.dumps(output, ensure_ascii=False, indent=2))
+        sys.exit(1)
+
     output = {
         "success": True,
         "filename": Path(args.output).name,