fix(api): 全面清除假信心分數 - 遵循 feedback_confidence_truthfulness.md

🔴 違規修正: 規則匹配/Expert System 不是 AI 分析，confidence 必須 = 0.0

修正檔案:
- agents/action_planner.py: 0.9 → 0.0
- agents/blast_radius.py: 0.85/0.5/0.9 → 0.0
- agents/security.py: 計算公式 → 0.0
- signoz_webhook.py: 0.7 → 0.0
- auto_approve.py: default 0.5 → 0.0
- ci_auto_repair.py: 整個計算函數 → return 0.0
- error_analyzer_service.py: default 0.5 → 0.0
- intent_classifier.py: 計算公式 → 0.0
- openclaw.py: default 0.5 → 0.0
- resource_resolver.py: 0.8 → 0.0
- k8s_naming.py: 0.9/0.7 → 0.0

只有 LLM 真實分析返回的 confidence 才能 > 0

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

apps/api/src/services/intent_classifier.py

@@ -478,21 +478,13 @@ class IntentClassifier:
             best_intent = max(scores, key=lambda k: scores[k][0])
             best_score, matched_keywords = scores[best_intent]
 
-            # 計算信心度 (基於匹配數量)
-            max_possible = len(INTENT_KEYWORDS.get(best_intent, [])) * 2
-            confidence = min(1.0, best_score / max(max_possible, 1) + 0.5)
-
-            # 如果有多個競爭意圖，降低信心度
-            if len(scores) > 1:
-                second_best_score = sorted(
-                    [s[0] for s in scores.values()], reverse=True
-                )[1]
-                if second_best_score > best_score * 0.7:
-                    confidence *= 0.8
+            # 🔴 2026-03-29 修正: 關鍵字匹配不是 AI 分析，信心度設 0
+            # 根據 feedback_confidence_truthfulness.md 鐵律
+            confidence = 0.0
 
             result = IntentResult(
                 intent=best_intent,
-                confidence=round(confidence, 2),
+                confidence=confidence,
                 method="keyword",
                 matched_keywords=matched_keywords,
                 detected_resources=detected_resources,