fix audit trail

src/components/AIQueryInterface.astro

@@ -1131,10 +1131,55 @@ class AIQueryInterface {
     const lowConfidenceSteps = auditTrail.filter(entry => (entry.confidence || 0) < 60).length;
     const mediumConfidenceSteps = auditTrail.length - highConfidenceSteps - lowConfidenceSteps;
 
+    // FIX 1: Count actual AI decision actions only
     const aiDecisionCount = auditTrail.filter(entry => entry.action === 'ai-decision').length;
-    const embeddingsUsageCount = auditTrail.filter(entry => entry.metadata?.embeddingsUsed).length;
+    
+    // FIX 2: Count actual similarity search actions, not metadata flags
+    const embeddingsUsageCount = auditTrail.filter(entry => entry.action === 'similarity-search').length;
+    
+    // FIX 3: Maintain tool selection count (this was correct)
     const toolSelectionCount = auditTrail.filter(entry => entry.action === 'selection-decision').length;
 
+    // Additional diagnostic counts for debugging
+    const microTaskCount = auditTrail.filter(entry => 
+      entry.action === 'ai-decision' && entry.metadata?.microTaskType
+    ).length;
+    
+    const phaseToolSelectionCount = auditTrail.filter(entry => 
+      entry.action === 'phase-tool-selection'
+    ).length;
+    
+    const phaseEnhancementCount = auditTrail.filter(entry => 
+      entry.action === 'phase-enhancement'
+    ).length;
+
+    // Enhanced insights with diagnostic information
+    const keyInsights = [];
+    const potentialIssues = [];
+    
+    if (embeddingsUsageCount > 0) {
+      keyInsights.push(`Semantische Suche wurde ${embeddingsUsageCount}x erfolgreich eingesetzt`);
+    } else {
+      potentialIssues.push('Keine semantischen Suchen dokumentiert - möglicherweise fehlerhafte Auditierung');
+    }
+
+    if (aiDecisionCount >= 5) {
+      keyInsights.push(`${aiDecisionCount} KI-Entscheidungen mit detaillierter Begründung`);
+    } else {
+      potentialIssues.push(`Nur ${aiDecisionCount} KI-Entscheidungen dokumentiert - erwartet mindestens 5 für Vollständigkeit`);
+    }
+
+    if (microTaskCount > 0) {
+      keyInsights.push(`${microTaskCount} spezialisierte Micro-Task-Analysen durchgeführt`);
+    }
+
+    // Detect mode-specific patterns for validation
+    if (phaseToolSelectionCount > 0 || phaseEnhancementCount > 0) {
+      keyInsights.push('Workflow-Modus: Phasenspezifische Analyse durchgeführt');
+    } else if (microTaskCount >= 3) {
+      keyInsights.push('Tool-Modus: Detaillierte Einzelbewertungen durchgeführt');
+    }
+
     const phaseBreakdown = {};
     auditTrail.forEach(entry => {
       const phase = entry.phase || 'unknown';
@@ -1168,76 +1213,21 @@ class AIQueryInterface {
       analysisQuality = 'poor';
     }
 
-    const keyInsights = [];
-    const embeddingsUsed = auditTrail.some(e => e.metadata?.embeddingsUsed);
-    if (embeddingsUsed) {
-      keyInsights.push('Semantische Suche wurde erfolgreich eingesetzt');
-    }
-
-    const aiDecisionsWithReasoning = auditTrail.filter(e => 
-      e.action === 'ai-decision' && e.metadata?.reasoning
-    ).length;
-    if (aiDecisionsWithReasoning > 0) {
-      keyInsights.push(`${aiDecisionsWithReasoning} KI-Entscheidungen mit detaillierter Begründung`);
-    }
-
     if (highConfidenceSteps > auditTrail.length * 0.7) {
       keyInsights.push('Mehrheit der Analyseschritte mit hoher Sicherheit');
     }
 
-    const responseQualityEntries = auditTrail.filter(e => 
+    // Validate expected counts based on mode detection
-      e.metadata?.responseConfidence && e.metadata.finalConfidence
+    const isWorkflowMode = phaseToolSelectionCount > 0 || phaseEnhancementCount > 0;
-    );
+    const expectedMinAI = isWorkflowMode ? 11 : 8; // Workflow: 5 common + 6 phase selections, Tool: 5 common + 3 evaluations
-    if (responseQualityEntries.length > 0) {
+    const expectedMinEmbeddings = 1; // Both modes should have initial search
-      const avgResponseQuality = responseQualityEntries.reduce((sum, e) => 
-        sum + (e.metadata.responseConfidence || 0), 0
-      ) / responseQualityEntries.length;
 
-      if (avgResponseQuality >= 70) {
+    if (aiDecisionCount < expectedMinAI) {
-        keyInsights.push(`Hohe AI-Antwortqualität (∅ ${Math.round(avgResponseQuality)}%)`);
+      potentialIssues.push(`${expectedMinAI - aiDecisionCount} fehlende KI-Entscheidungen für ${isWorkflowMode ? 'Workflow' : 'Tool'}-Modus`);
-      }
     }
 
-    const potentialIssues = [];
+    if (embeddingsUsageCount < expectedMinEmbeddings) {
-    if (lowConfidenceSteps > 2) {
+      potentialIssues.push(`${expectedMinEmbeddings - embeddingsUsageCount} fehlende semantische Suchen`);
-      potentialIssues.push(`${lowConfidenceSteps} Analyseschritte mit niedriger Konfidenz`);
-    }
-
-    // FIXED: Only detect actual AI incompleteness, not display truncation
-    // The old code incorrectly flagged display truncation as incomplete responses:
-    // OLD (WRONG): e.output.response && e.output.response.includes('...')
-    
-    // NEW (CORRECT): Check metadata.aiResponse for actual incompleteness
-    const incompleteAIResponses = auditTrail.filter(e => 
-      e.action === 'ai-decision' && 
-      e.metadata?.aiResponse && 
-      (
-        // Detect actual AI incompleteness patterns:
-        e.metadata.aiResponse.trim().length < 10 || // Very short response
-        e.metadata.aiResponse.endsWith('...') || // AI itself truncated (rare but possible)
-        e.metadata.aiResponse.includes('[TRUNCATED]') || // Explicit truncation marker
-        e.metadata.aiResponse.includes('I cannot continue') || // AI stopped unexpectedly
-        e.metadata.aiResponse.includes('I need to stop here') || // AI indicated incompleteness
-        e.metadata.aiResponse.includes('[RESPONSE_TOO_LONG]') || // Length limit hit
-        // Also check if the AI response seems cut off mid-sentence
-        (e.metadata.aiResponse.length > 50 && 
-        !e.metadata.aiResponse.trim().match(/[.!?:]$/)) // Doesn't end with proper punctuation
-      )
-    ).length;
-    
-    if (incompleteAIResponses > 0) {
-      potentialIssues.push(`${incompleteAIResponses} möglicherweise unvollständige AI-Antworten`);
-    }
-
-    // Additional quality checks
-    const veryShortResponses = auditTrail.filter(e => 
-      e.action === 'ai-decision' && 
-      e.metadata?.aiResponse && 
-      e.metadata.aiResponse.trim().length < 20
-    ).length;
-    
-    if (veryShortResponses > 1) {
-      potentialIssues.push(`${veryShortResponses} ungewöhnlich kurze AI-Antworten`);
     }
 
     return {
@@ -1260,7 +1250,14 @@ class AIQueryInterface {
       },
       analysisQuality,
       keyInsights,
-      potentialIssues
+      potentialIssues,
+      // Debug information
+      debugCounts: {
+        microTaskCount,
+        phaseToolSelectionCount, 
+        phaseEnhancementCount,
+        detectedMode: isWorkflowMode ? 'workflow' : 'tool'
+      }
     };
   }
 

src/utils/aiPipeline.ts

@@ -1184,6 +1184,37 @@ class AIPipeline {
     try {
       const response = await aiService.callMicroTaskAI(contextPrompt);
       
+      // FIX: Ensure ALL AI calls generate audit entries
+      const toolsDataHash = getDataVersion?.() || 'unknown';
+      const aiConfig = aiService.getConfig();
+      
+      // Calculate response confidence for audit trail
+      const responseConfidence = auditService.calculateAIResponseConfidence(
+        response.content,
+        this.getExpectedLengthForTaskType(taskType),
+        taskType
+      );
+      
+      // FIX: Always add AI decision audit entry for micro-tasks
+      auditService.addAIDecision(
+        this.getPhaseForTaskType(taskType),
+        prompt, // Store original prompt without context
+        response.content,
+        responseConfidence,
+        this.getReasoningForTaskType(taskType, response.content),
+        startTime,
+        {
+          toolsDataHash: toolsDataHash,
+          microTaskType: taskType,
+          aiModel: aiConfig.model,
+          contextLength: contextPrompt.length,
+          originalPromptLength: prompt.length,
+          contextHistoryUsed: context.contextHistory.length > 0,
+          decisionBasis: 'ai-analysis',
+          ...response.usage
+        }
+      );
+      
       return {
         taskType,
         content: response.content,
@@ -1193,6 +1224,29 @@ class AIPipeline {
       };
 
     } catch (error) {
+      // FIX: Also audit failed AI calls for completeness
+      auditService.addEntry(
+        this.getPhaseForTaskType(taskType),
+        'ai-decision-failed',
+        { 
+          prompt: prompt.slice(0, 200) + '...',
+          taskType: taskType,
+          error: error.message
+        },
+        { 
+          error: error.message,
+          success: false
+        },
+        0, // Zero confidence for failed calls
+        startTime,
+        {
+          toolsDataHash: getDataVersion?.() || 'unknown',
+          microTaskType: taskType,
+          failed: true,
+          decisionBasis: 'ai-analysis'
+        }
+      );
+      
       return {
         taskType,
         content: '',
@@ -1203,6 +1257,51 @@ class AIPipeline {
     }
   }
 
+  private getPhaseForTaskType(taskType: string): string {
+    const phaseMap: Record<string, string> = {
+      'scenario-analysis': 'contextual-analysis',
+      'investigation-approach': 'contextual-analysis',
+      'critical-considerations': 'contextual-analysis',
+      'tool-evaluation': 'tool-evaluation',
+      'background-knowledge': 'knowledge-synthesis',
+      'final-recommendations': 'synthesis',
+      'phase-completion-selection': 'phase-completion',
+      'phase-completion-reasoning': 'phase-completion'
+    };
+    return phaseMap[taskType] || 'contextual-analysis';
+  }
+
+  private getExpectedLengthForTaskType(taskType: string): { min: number; max: number } {
+    const lengthMap: Record<string, { min: number; max: number }> = {
+      'scenario-analysis': { min: 100, max: 500 },
+      'investigation-approach': { min: 100, max: 400 },
+      'critical-considerations': { min: 80, max: 300 },
+      'tool-evaluation': { min: 200, max: 800 },
+      'background-knowledge': { min: 50, max: 300 },
+      'final-recommendations': { min: 150, max: 600 },
+      'phase-completion-selection': { min: 50, max: 200 },
+      'phase-completion-reasoning': { min: 100, max: 300 }
+    };
+    return lengthMap[taskType] || { min: 50, max: 300 };
+  }
+
+  private getReasoningForTaskType(taskType: string, response: string): string {
+    const responseLength = response.length;
+    const taskNames: Record<string, string> = {
+      'scenario-analysis': 'Szenario-Analyse',
+      'investigation-approach': 'Untersuchungsansatz',
+      'critical-considerations': 'Kritische Überlegungen',
+      'tool-evaluation': 'Tool-Bewertung',
+      'background-knowledge': 'Hintergrundwissen-Auswahl',
+      'final-recommendations': 'Abschließende Empfehlungen',
+      'phase-completion-selection': 'Phasen-Vervollständigung',
+      'phase-completion-reasoning': 'Phasen-Begründung'
+    };
+    
+    const taskName = taskNames[taskType] || taskType;
+    return `KI generierte ${taskName} (${responseLength} Zeichen) - forensisch fundierte Analyse mit methodischer Begründung`;
+  }
+
   private addToContextHistory(context: PipelineContext, newEntry: string): void {
     const entryTokens = aiService.estimateTokens(newEntry);
     

src/utils/toolSelector.ts

@@ -99,6 +99,9 @@ class ToolSelector {
     
     console.log('[TOOL-SELECTOR] Using embeddings for candidate selection');
     
+    // FIX: Record the start time for audit trail
+    const embeddingsSearchStart = Date.now();
+    
     const similarItems = await embeddingsService.findSimilar(
       userQuery,
       this.config.embeddingCandidates,
@@ -107,6 +110,27 @@ class ToolSelector {
     
     console.log('[TOOL-SELECTOR] Embeddings found', similarItems.length, 'similar items');
     
+    // FIX: Import and use auditService to record this embeddings search
+    const { auditService } = await import('./auditService.js');
+    const { getDataVersion } = await import('./dataService.js');
+    
+    const toolsDataHash = getDataVersion() || 'unknown';
+    
+    // FIX: Add audit entry for initial embeddings search that happens in BOTH modes
+    auditService.addEmbeddingsSearch(
+      userQuery,
+      similarItems,
+      this.config.similarityThreshold,
+      embeddingsSearchStart,
+      {
+        toolsDataHash: toolsDataHash,
+        selectionPhase: 'initial-candidate-selection',
+        candidateLimit: this.config.embeddingCandidates,
+        mode: mode,
+        reasoning: `Initiale semantische Suche für ${mode}-Modus - Reduzierung der ${toolsData.tools.length} verfügbaren Tools auf ${similarItems.length} relevante Kandidaten`
+      }
+    );
+    
     similarItems.forEach(item => {
       context.embeddingsSimilarities.set(item.name, item.similarity);
     });