fix: distill LLM 模型切换 gemma-4-31b-it + JSON 解析增强

根因链:
1. gpt-oss-120b 是 reasoning 模型，content=null 答案全在 reasoning 字段，
   代码只读 content/reasoning_content（OpenAI 用 reasoning 字段名）→ parse 失败
   → 永远降级 keyword 提取 (facts=1 entities=0)
2. skill 记载的 m3/m2.7/mistral-large 均已 EOL 或渠道失效 (2026-07-27 后)
3. gemma-4-31b-it 对 '0.X' 占位符输出 0.0 → prompt 改为明确 0-1 浮点说明

修复:
- engine.go: 支持 reasoning 字段 + 剥离 markdown code fence + prompt 评分说明明确化
- zhiyid.service: LLM_MODEL=google/gemma-4-31b-it

验证: LLM entities=2, overall=1.000, facts=3 entities=2, recall 命中 0.765

go/internal/distill/engine.go

@@ -280,7 +280,8 @@ func (e *Engine) callLLM5D(content string) (LLMResponse, error) {
 内容:
 %s
 
-只返回JSON: {"decisions": ["决定1", "决定2"], "conclusions": ["结论1"], "actions_taken": ["行动1"], "open_questions": ["问题1"], "entities": ["entity1", "entity2"], "is": 0.X, "su": 0.X, "pa": 0.X, "vd": 0.X, "ru": 0.X}`, truncate(content, 1000))
+只返回JSON: {"decisions": ["决定1", "决定2"], "conclusions": ["结论1"], "actions_taken": ["行动1"], "open_questions": ["问题1"], "entities": ["entity1", "entity2"], "is": 0.8, "su": 0.7, "pa": 0.6, "vd": 0.9, "ru": 0.7}
+评分说明：is/su/pa/vd/ru 是 0.0 到 1.0 之间的浮点数（越高越好），不要用 0-10 整数。`, truncate(content, 1000))
 
 	body := map[string]interface{}{
 		"model": e.LLMModel,
@@ -318,6 +319,8 @@ func (e *Engine) callLLM5D(content string) (LLMResponse, error) {
 			Message struct {
 				Content          string `json:"content"`
 				ReasoningContent string `json:"reasoning_content"`
+				// OpenAI 系 reasoning 模型（gpt-oss 等）用 "reasoning" 字段，不是 "reasoning_content"
+				Reasoning string `json:"reasoning"`
 			} `json:"message"`
 		} `json:"choices"`
 	}
@@ -335,6 +338,15 @@ func (e *Engine) callLLM5D(content string) (LLMResponse, error) {
 	if llmContent == "" {
 		llmContent = result.Choices[0].Message.ReasoningContent
 	}
+	if llmContent == "" {
+		llmContent = result.Choices[0].Message.Reasoning
+	}
+	// 剥离 markdown code fence（minimax 等模型习惯用 ```json 包裹）
+	llmContent = strings.TrimSpace(llmContent)
+	llmContent = strings.TrimPrefix(llmContent, "```json")
+	llmContent = strings.TrimPrefix(llmContent, "```")
+	llmContent = strings.TrimSuffix(llmContent, "```")
+	llmContent = strings.TrimSpace(llmContent)
 	if err := json.Unmarshal([]byte(llmContent), &llmResp); err != nil {
 		log.Printf("[distill] LLM JSON parse error: %v | content=%q", err, truncate(llmContent, 200))
 		return LLMResponse{}, fmt.Errorf("parse score: %w", err)