diff --git a/src/components/AIQueryInterface.astro b/src/components/AIQueryInterface.astro
index 8f97f6d..2ae93ea 100644
--- a/src/components/AIQueryInterface.astro
+++ b/src/components/AIQueryInterface.astro
@@ -50,7 +50,7 @@ const domainAgnosticSoftware = data['domain-agnostic-software'] || [];
 
       <!-- Input Layout -->
       <div class="ai-input-layout">
-        <div class="ai-textarea-section">
+        <div class="ai-textarea-section" style="height: 200px">
           <textarea 
             id="ai-query-input" 
             placeholder="Beschreiben Sie Ihr forensisches Szenario..."
@@ -1158,12 +1158,10 @@ class AIQueryInterface {
     const lowConfidenceSteps = auditTrail.filter(entry => (entry.confidence || 0) < 60).length;
     const mediumConfidenceSteps = auditTrail.length - highConfidenceSteps - lowConfidenceSteps;
 
-    // Enhanced metrics
     const aiDecisionCount = auditTrail.filter(entry => entry.action === 'ai-decision').length;
     const embeddingsUsageCount = auditTrail.filter(entry => entry.metadata?.embeddingsUsed).length;
     const toolSelectionCount = auditTrail.filter(entry => entry.action === 'selection-decision').length;
 
-    // Phase breakdown
     const phaseBreakdown = {};
     auditTrail.forEach(entry => {
       const phase = entry.phase || 'unknown';
@@ -1175,7 +1173,6 @@ class AIQueryInterface {
       phaseBreakdown[phase].totalTime += entry.processingTimeMs || 0;
     });
 
-    // Calculate average confidence per phase
     Object.keys(phaseBreakdown).forEach(phase => {
       const phaseEntries = auditTrail.filter(entry => entry.phase === phase);
       const validEntries = phaseEntries.filter(entry => typeof entry.confidence === 'number');
@@ -1191,7 +1188,6 @@ class AIQueryInterface {
     const aiTransparency = auditTrail.length > 0 ? 
       (auditTrail.filter(entry => entry.metadata?.aiPrompt || entry.metadata?.reasoning).length / auditTrail.length) * 100 : 0;
 
-    // RESTORED: Intelligent Analysis Quality Assessment
     let analysisQuality;
     if (avgConfidence >= 85 && lowConfidenceSteps === 0) {
       analysisQuality = 'excellent';
@@ -1203,7 +1199,6 @@ class AIQueryInterface {
       analysisQuality = 'poor';
     }
 
-    // RESTORED: Intelligent Insights Generation
     const keyInsights = [];
     const embeddingsUsed = auditTrail.some(e => e.metadata?.embeddingsUsed);
     if (embeddingsUsed) {
@@ -1226,7 +1221,6 @@ class AIQueryInterface {
       keyInsights.push('Mehrheit der Analyseschritte mit hoher Sicherheit');
     }
 
-    // RESTORED: Automatic Issue Detection (excluding processing time warnings)
     const potentialIssues = [];
     if (lowConfidenceSteps > 2) {
       potentialIssues.push(`${lowConfidenceSteps} Analyseschritte mit niedriger Konfidenz`);
diff --git a/src/config/prompts.ts b/src/config/prompts.ts
index a1babec..9ec3ddf 100644
--- a/src/config/prompts.ts
+++ b/src/config/prompts.ts
@@ -36,6 +36,11 @@ AUSWAHLSTRATEGIE:
   - Lieber weniger perfekte Items als viele mittelmäßige
   - Jedes Item muss begründbar sein
 
+4. **TASK RELEVANCE REALISM**
+  - Gib realistische Bewertungen (50-85% typisch)
+  - Vermeide übertriebene 90-100% Scores
+  - Nur bei perfekter Übereinstimmung >85%
+
 AUSWAHLREGELN:
 - Wähle ${mode === 'workflow' ? '15-25' : '4-10'} Items total, max ${maxSelectedItems}
 - BEIDE Arrays füllen: selectedTools UND selectedConcepts
@@ -59,7 +64,13 @@ ${JSON.stringify(toolsToSend, null, 2)}
 VERFÜGBARE KONZEPTE (${conceptsToSend.length} Items - theoretisches Wissen):
 ${JSON.stringify(conceptsToSend, null, 2)}
 
-WICHTIGER HINWEIS: Wähle sowohl aus TOOLS als auch aus KONZEPTEN aus! Konzepte sind essentiell für methodische Fundierung.`;
+WICHTIGER HINWEIS: Wähle sowohl aus TOOLS als auch aus KONZEPTEN aus! Konzepte sind essentiell für methodische Fundierung.
+
+TASK RELEVANCE GUIDELINES:
+- 50-65%: Grundlegend relevant, aber nicht optimal
+- 66-75%: Gut geeignet für die Aufgabe
+- 76-85%: Sehr gut geeignet, klare Vorteile
+- 86-100%: NUR für perfekte Übereinstimmung verwenden`;
   },
 
   scenarioAnalysis: (isWorkflow: boolean, userQuery: string) => {
@@ -148,13 +159,19 @@ AUSWAHLREGELN FÜR PHASE "${phase.name}":
 3. Mindestens 1 Methode wenn verfügbar, Rest Software-Tools
 4. Begründe WARUM jedes Item für diese Phase optimal ist
 
+TASK RELEVANCE GUIDELINES:
+- 60-70%: Grundlegend für diese Phase geeignet
+- 71-80%: Gut geeignet, klare Phasenrelevanz
+- 81-90%: Sehr gut geeignet, optimal für Phase
+- 91-100%: NUR für perfekte Phasenübereinstimmung
+
 WICHTIG: Verwende EXAKT die Namen wie oben aufgelistet (ohne Präfixe wie M1./T2.)!
 
 ANTWORT AUSSCHLIESSLICH IM JSON-FORMAT OHNE JEGLICHEN TEXT AUSSERHALB:
 [
   {
     "toolName": "Exakter Name aus der Liste oben",
-    "taskRelevance": 85,
+    "taskRelevance": 75,
     "justification": "Detaillierte Begründung (60-80 Wörter) warum optimal für ${phase.name} - erkläre Anwendung, Vorteile und spezifische Relevanz",
     "limitations": ["Mögliche Einschränkung für diese Phase"]
   }
@@ -266,6 +283,7 @@ AUSWAHLREGELN FÜR NACHERGÄNZUNG:
 1. Wähle 1-2 BESTE Methoden/Tools die die ${phase.name}-Phase optimal ergänzen
 2. Methoden/Tools müssen für die ursprüngliche Anfrage relevant sein
 3. Ergänzen, nicht ersetzen - erweitere die zu spezifische Erstauswahl
+4. Realistische Task Relevance (70-85% typisch für Nachergänzungen)
 
 ANTWORT AUSSCHLIESSLICH IM JSON-FORMAT:
 {
diff --git a/src/utils/aiPipeline.ts b/src/utils/aiPipeline.ts
index 924e678..7f0f706 100644
--- a/src/utils/aiPipeline.ts
+++ b/src/utils/aiPipeline.ts
@@ -1,11 +1,11 @@
-// src/utils/aiPipeline.ts - Enhanced with comprehensive audit logging
+// src/utils/aiPipeline.ts - Enhanced with comprehensive audit logging and restored sophisticated logic
 import { getCompressedToolsDataForAI, getDataVersion } from './dataService.js';
 import { aiService } from './aiService.js';
 import { toolSelector, type SelectionContext } from './toolSelector.js';
 import { confidenceScoring, type AnalysisContext } from './confidenceScoring.js';
 import { embeddingsService } from './embeddings.js';
 import { auditService, type AuditEntry } from './auditService.js';
-import { JSONParser } from './jsonUtils.js'; // FIXED: Use centralized JSON parsing
+import { JSONParser } from './jsonUtils.js';
 import { getPrompt } from '../config/prompts.js';
 import 'dotenv/config';
 
@@ -13,6 +13,11 @@ interface PipelineConfig {
   microTaskDelay: number;
   maxContextTokens: number;
   maxPromptTokens: number;
+  taskRelevanceModeration: {
+    maxInitialScore: number;
+    maxWithPhaseBonus: number;
+    moderationThreshold: number;
+  };
 }
 
 interface MicroTaskResult {
@@ -40,6 +45,10 @@ interface AnalysisResult {
     contextContinuityUsed: boolean;
     totalAITokensUsed: number;
     auditEntriesGenerated: number;
+    aiModel: string;
+    toolsDataHash: string;
+    temperature: number;
+    maxTokensUsed: number;
   };
 }
 
@@ -78,10 +87,15 @@ class AIPipeline {
     this.config = {
       microTaskDelay: parseInt(process.env.AI_MICRO_TASK_DELAY_MS || '500', 10),
       maxContextTokens: parseInt(process.env.AI_MAX_CONTEXT_TOKENS || '4000', 10),
-      maxPromptTokens: parseInt(process.env.AI_MAX_PROMPT_TOKENS || '1500', 10)
+      maxPromptTokens: parseInt(process.env.AI_MAX_PROMPT_TOKENS || '1500', 10),
+      taskRelevanceModeration: {
+        maxInitialScore: 85,
+        maxWithPhaseBonus: 95,
+        moderationThreshold: 80
+      }
     };
 
-    console.log('[AI-PIPELINE] Initialized orchestration pipeline');
+    console.log('[AI-PIPELINE] Initialized orchestration pipeline with enhanced logic');
   }
 
   async processQuery(userQuery: string, mode: string): Promise<AnalysisResult> {
@@ -92,7 +106,6 @@ class AIPipeline {
     
     console.log('[AI-PIPELINE] Starting', mode, 'analysis pipeline');
 
-    // Initialize audit trail
     auditService.clearAuditTrail();
 
     try {
@@ -111,7 +124,6 @@ class AIPipeline {
         embeddingsSimilarities: new Map<string, number>()
       };
 
-      // AUDIT: Pipeline initialization
       auditService.addEntry(
         'initialization',
         'pipeline-start',
@@ -132,17 +144,15 @@ class AIPipeline {
           toolsDataHash,
           aiModel: aiConfig.model,
           embeddingsUsed: embeddingsService.isEnabled(),
-          pipelineVersion: '2.0-enhanced'
+          pipelineVersion: '2.1-enhanced'
         }
       );
 
-      // Phase 1: Get intelligent tool candidates with enhanced logging
       console.log('[AI-PIPELINE] Phase 1: Tool candidate selection');
       const candidateSelectionStart = Date.now();
       
       const candidateData = await toolSelector.getIntelligentCandidates(userQuery, toolsData, mode, context);
       
-      // AUDIT: Tool candidate selection
       auditService.addToolSelection(
         candidateData.tools.map(t => t.name),
         toolsData.tools.map(t => t.name),
@@ -159,7 +169,6 @@ class AIPipeline {
       
       context.filteredData = candidateData;
 
-      // Phase 2: Contextual analysis micro-tasks with enhanced logging
       console.log('[AI-PIPELINE] Phase 2: Contextual analysis');
       
       const analysisResult = await this.analyzeScenario(context, startTime);
@@ -177,7 +186,6 @@ class AIPipeline {
       this.trackTokenUsage(considerationsResult.aiUsage);
       await this.delay(this.config.microTaskDelay);
 
-      // Phase 3: Tool-specific analysis with enhanced logging
       console.log('[AI-PIPELINE] Phase 3: Tool-specific analysis');
       
       if (mode === 'workflow') {
@@ -190,7 +198,6 @@ class AIPipeline {
         failedTasks = toolResults.failed;
       }
 
-      // Phase 4: Knowledge and finalization with enhanced logging
       console.log('[AI-PIPELINE] Phase 4: Knowledge synthesis');
       
       const knowledgeResult = await this.selectBackgroundKnowledge(context, startTime);
@@ -202,10 +209,8 @@ class AIPipeline {
       if (finalResult.success) completedTasks++; else failedTasks++;
       this.trackTokenUsage(finalResult.aiUsage);
 
-      // Build final recommendation
       const recommendation = this.buildRecommendation(context, mode, finalResult.content);
 
-      // AUDIT: Pipeline completion
       auditService.addEntry(
         'completion',
         'pipeline-end',
@@ -235,7 +240,11 @@ class AIPipeline {
         microTasksFailed: failedTasks,
         contextContinuityUsed: true,
         totalAITokensUsed: this.totalTokensUsed,
-        auditEntriesGenerated: auditService.getCurrentAuditTrail().length
+        auditEntriesGenerated: auditService.getCurrentAuditTrail().length,
+        aiModel: aiConfig.model,
+        toolsDataHash,
+        temperature: 0.3,
+        maxTokensUsed: 2500
       };
 
       console.log('[AI-PIPELINE] Pipeline completed successfully:', {
@@ -248,13 +257,13 @@ class AIPipeline {
         auditEntries: processingStats.auditEntriesGenerated
       });
 
-      // Finalize audit trail
       const finalAuditTrail = auditService.finalizeAuditTrail();
 
       return {
         recommendation: {
           ...recommendation,
-          auditTrail: auditService.isEnabled() ? finalAuditTrail : undefined
+          auditTrail: auditService.isEnabled() ? finalAuditTrail : undefined,
+          processingStats
         },
         processingStats
       };
@@ -262,7 +271,6 @@ class AIPipeline {
     } catch (error) {
       console.error('[AI-PIPELINE] Pipeline failed:', error);
       
-      // AUDIT: Pipeline failure
       auditService.addEntry(
         'error',
         'pipeline-failure',
@@ -286,7 +294,6 @@ class AIPipeline {
   ): Promise<{ completed: number; failed: number }> {
     const phases = toolsData.phases || [];
     
-    // Select tools for each phase with enhanced logging
     for (const phase of phases) {
       const phaseStart = Date.now();
       const phaseTools = context.filteredData.tools.filter((tool: any) =>
@@ -295,7 +302,6 @@ class AIPipeline {
       
       const selections = await toolSelector.selectToolsForPhase(context.userQuery, phase, phaseTools, context);
       
-      // AUDIT: Phase tool selection
       auditService.addEntry(
         'workflow-phase',
         'phase-tool-selection',
@@ -321,21 +327,23 @@ class AIPipeline {
       selections.forEach((sel: any) => {
         const tool = phaseTools.find((t: any) => t && t.name === sel.toolName);
         if (tool) {
-          const priority = this.derivePriorityFromScore(sel.taskRelevance);
-          this.addToolToSelection(context, tool, phase.id, priority, sel.justification, sel.taskRelevance, sel.limitations);
+          const moderatedTaskRelevance = this.moderateTaskRelevance(sel.taskRelevance);
+          const priority = this.derivePriorityFromScore(moderatedTaskRelevance);
+          
+          this.addToolToSelection(context, tool, phase.id, priority, sel.justification, moderatedTaskRelevance, sel.limitations);
           
-          // AUDIT: Individual tool selection reasoning
           auditService.addEntry(
             'tool-reasoning',
             'tool-added-to-phase',
-            { toolName: tool.name, phaseId: phase.id, taskRelevance: sel.taskRelevance },
+            { toolName: tool.name, phaseId: phase.id, originalTaskRelevance: sel.taskRelevance, moderatedTaskRelevance },
             { justification: sel.justification, limitations: sel.limitations },
-            sel.taskRelevance || 70,
+            moderatedTaskRelevance || 70,
             phaseStart,
             {
               toolType: tool.type,
               priority,
-              selectionReasoning: sel.justification
+              selectionReasoning: sel.justification,
+              moderationApplied: sel.taskRelevance !== moderatedTaskRelevance
             }
           );
         }
@@ -345,8 +353,9 @@ class AIPipeline {
       await this.delay(this.config.microTaskDelay);
     }
     
-    // Complete underrepresented phases with enhanced logging
     const completionResult = await this.completeUnderrepresentedPhases(context, toolsData, pipelineStart);
+    completedTasks += completionResult.completed;
+    failedTasks += completionResult.failed;
     
     return { completed: completedTasks, failed: failedTasks };
   }
@@ -369,6 +378,267 @@ class AIPipeline {
     return { completed: completedTasks, failed: failedTasks };
   }
 
+  private async completeUnderrepresentedPhases(
+    context: PipelineContext, 
+    toolsData: any, 
+    pipelineStart: number
+  ): Promise<{ completed: number; failed: number }> {
+    const phases = toolsData.phases || [];
+    const selectedPhases = new Map<string, number>();
+    let completedTasks = 0;
+    let failedTasks = 0;
+    
+    context.selectedTools?.forEach((st: any) => {
+      const count = selectedPhases.get(st.phase) || 0;
+      selectedPhases.set(st.phase, count + 1);
+    });
+    
+    const underrepresentedPhases = phases.filter((phase: any) => {
+      const count = selectedPhases.get(phase.id) || 0;
+      return count <= 1;
+    });
+    
+    if (underrepresentedPhases.length === 0) {
+      console.log('[AI-PIPELINE] All phases adequately represented');
+      return { completed: 0, failed: 0 };
+    }
+    
+    console.log('[AI-PIPELINE] Completing underrepresented phases:', underrepresentedPhases.map((p: any) => p.id).join(', '));
+    
+    auditService.addEntry(
+      'phase-completion',
+      'underrepresented-phases-detected',
+      { 
+        underrepresentedPhases: underrepresentedPhases.map(p => p.id),
+        currentPhaseDistribution: Array.from(selectedPhases.entries())
+      },
+      { 
+        phasesToComplete: underrepresentedPhases.length,
+        completionStrategy: 'semantic-search-with-ai-reasoning'
+      },
+      70,
+      pipelineStart,
+      {
+        totalPhases: phases.length,
+        adequatelyRepresented: phases.length - underrepresentedPhases.length,
+        completionMethod: 'sophisticated-ai-reasoning'
+      }
+    );
+    
+    for (const phase of underrepresentedPhases) {
+      const result = await this.completePhaseWithSemanticSearchAndAI(context, phase, toolsData, pipelineStart);
+      if (result.success) completedTasks++; else failedTasks++;
+      await this.delay(this.config.microTaskDelay);
+    }
+    
+    return { completed: completedTasks, failed: failedTasks };
+  }
+
+  private async completePhaseWithSemanticSearchAndAI(
+    context: PipelineContext, 
+    phase: any, 
+    toolsData: any, 
+    pipelineStart: number
+  ): Promise<MicroTaskResult> {
+    const phaseStart = Date.now();
+    const phaseQuery = `forensic ${phase.name.toLowerCase()} tools methods`;
+    
+    console.log('[AI-PIPELINE] Phase completion for:', phase.id);
+    
+    try {
+      const phaseResults = await embeddingsService.findSimilar(phaseQuery, 20, 0.2);
+      
+      auditService.addEmbeddingsSearch(
+        phaseQuery,
+        phaseResults,
+        0.2,
+        phaseStart,
+        {
+          phaseId: phase.id,
+          phaseName: phase.name,
+          completionPurpose: 'underrepresented-phase-enhancement'
+        }
+      );
+      
+      if (phaseResults.length === 0) {
+        console.log('[AI-PIPELINE] No semantic results for phase:', phase.id);
+        return {
+          taskType: 'phase-completion',
+          content: '',
+          processingTimeMs: Date.now() - phaseStart,
+          success: true
+        };
+      }
+      
+      const toolsMap = new Map(toolsData.tools.map((tool: any) => [tool.name, tool]));
+      const conceptsMap = new Map(toolsData.concepts.map((concept: any) => [concept.name, concept]));
+      
+      const phaseTools = phaseResults
+        .filter((result: any) => result.type === 'tool')
+        .map((result: any) => toolsMap.get(result.name))
+        .filter((tool: any): tool is NonNullable<any> =>
+          tool !== undefined &&
+          tool !== null &&
+          tool.phases &&
+          Array.isArray(tool.phases) &&
+          tool.phases.includes(phase.id) &&
+          !context.seenToolNames.has(tool.name)
+        )
+        .slice(0, 5);
+      
+      const phaseConcepts = phaseResults
+        .filter((result: any) => result.type === 'concept')
+        .map((result: any) => conceptsMap.get(result.name))
+        .filter((concept: any): concept is NonNullable<any> => concept !== undefined && concept !== null)
+        .slice(0, 2);
+      
+      if (phaseTools.length === 0) {
+        console.log('[AI-PIPELINE] No suitable tools for phase completion:', phase.id);
+        return {
+          taskType: 'phase-completion',
+          content: '',
+          processingTimeMs: Date.now() - phaseStart,
+          success: true
+        };
+      }
+      
+      const selectionPrompt = getPrompt('generatePhaseCompletionPrompt', context.userQuery, phase, phaseTools, phaseConcepts);
+      const selectionResult = await this.callMicroTaskAI(selectionPrompt, context, 800, 'phase-completion-selection');
+      
+      if (!selectionResult.success) {
+        console.error('[AI-PIPELINE] Phase completion selection failed for:', phase.id);
+        return {
+          taskType: 'phase-completion',
+          content: '',
+          processingTimeMs: Date.now() - phaseStart,
+          success: false,
+          error: 'Selection micro-task failed'
+        };
+      }
+      
+      const selection = JSONParser.safeParseJSON(selectionResult.content, { 
+        selectedTools: [], 
+        selectedConcepts: [],
+        completionReasoning: ''
+      });
+      
+      const validTools = selection.selectedTools
+        .map((name: string) => phaseTools.find((t: any) => t && t.name === name))
+        .filter((tool: any): tool is NonNullable<any> => tool !== undefined && tool !== null)
+        .slice(0, 2);
+      
+      if (validTools.length === 0) {
+        console.log('[AI-PIPELINE] No valid tools selected for phase completion:', phase.id);
+        return {
+          taskType: 'phase-completion',
+          content: selection.completionReasoning || '',
+          processingTimeMs: Date.now() - phaseStart,
+          success: true
+        };
+      }
+      
+      for (const tool of validTools) {
+        console.log('[AI-PIPELINE] Generating AI reasoning for phase completion tool:', tool.name);
+        
+        const reasoningPrompt = getPrompt(
+          'phaseCompletionReasoning',
+          context.userQuery,
+          phase,
+          tool.name,
+          tool,
+          selection.completionReasoning || 'Nachergänzung zur Vervollständigung der Phasenabdeckung'
+        );
+        
+        const reasoningResult = await this.callMicroTaskAI(reasoningPrompt, context, 400, 'phase-completion-reasoning');
+        
+        let detailedJustification: string;
+        let moderatedTaskRelevance = 75;
+        
+        if (reasoningResult.success && reasoningResult.content.trim()) {
+          detailedJustification = reasoningResult.content.trim();
+          moderatedTaskRelevance = this.moderateTaskRelevance(80);
+        } else {
+          detailedJustification = `Nachträglich hinzugefügt zur Vervollständigung der ${phase.name}-Phase. Die ursprüngliche KI-Auswahl war zu spezifisch und hat wichtige Tools für diese Phase übersehen.`;
+          moderatedTaskRelevance = this.moderateTaskRelevance(75);
+        }
+        
+        this.addToolToSelection(
+          context,
+          tool,
+          phase.id,
+          'medium',
+          detailedJustification,
+          moderatedTaskRelevance,
+          ['Nachträgliche Ergänzung via semantische Phasensuche mit KI-Bewertung']
+        );
+        
+        auditService.addPhaseCompletion(
+          phase.id,
+          [tool.name],
+          detailedJustification,
+          phaseStart,
+          {
+            toolName: tool.name,
+            toolType: tool.type,
+            semanticSimilarity: phaseResults.find(r => r.name === tool.name)?.similarity,
+            completionReason: 'underrepresented-phase',
+            originalSelectionMissed: true,
+            aiReasoningUsed: reasoningResult.success,
+            moderatedTaskRelevance
+          }
+        );
+        
+        console.log('[AI-PIPELINE] Added phase completion tool with AI reasoning:', tool.name);
+      }
+      
+      return {
+        taskType: 'phase-completion',
+        content: selection.completionReasoning || '',
+        processingTimeMs: Date.now() - phaseStart,
+        success: true
+      };
+      
+    } catch (error) {
+      console.error('[AI-PIPELINE] Phase completion failed for:', phase.id, error);
+      
+      auditService.addEntry(
+        'phase-completion',
+        'completion-failed',
+        { phaseId: phase.id, error: error.message },
+        { success: false },
+        20,
+        phaseStart,
+        {
+          errorType: error.constructor.name,
+          phaseId: phase.id
+        }
+      );
+      
+      return {
+        taskType: 'phase-completion',
+        content: '',
+        processingTimeMs: Date.now() - phaseStart,
+        success: false,
+        error: error.message
+      };
+    }
+  }
+
+  private moderateTaskRelevance(taskRelevance: number): number {
+    if (typeof taskRelevance !== 'number') {
+      return 70;
+    }
+    
+    let moderated = Math.min(taskRelevance, this.config.taskRelevanceModeration.maxInitialScore);
+    
+    if (moderated > this.config.taskRelevanceModeration.moderationThreshold) {
+      const excess = moderated - this.config.taskRelevanceModeration.moderationThreshold;
+      moderated = this.config.taskRelevanceModeration.moderationThreshold + (excess * 0.7);
+    }
+    
+    return Math.round(Math.min(moderated, this.config.taskRelevanceModeration.maxInitialScore));
+  }
+
   private async analyzeScenario(context: PipelineContext, pipelineStart: number): Promise<MicroTaskResult> {
     console.log('[AI-PIPELINE] Micro-task: Scenario analysis');
     const taskStart = Date.now();
@@ -386,7 +656,6 @@ class AIPipeline {
       
       this.addToContextHistory(context, `${isWorkflow ? 'Szenario' : 'Problem'}-Analyse: ${result.content.slice(0, 200)}...`);
       
-      // AUDIT: Scenario analysis
       auditService.addAIDecision(
         'contextual-analysis',
         prompt,
@@ -418,7 +687,6 @@ class AIPipeline {
       context.investigationApproach = result.content;
       this.addToContextHistory(context, `${isWorkflow ? 'Untersuchungs' : 'Lösungs'}ansatz: ${result.content.slice(0, 200)}...`);
       
-      // AUDIT: Investigation approach
       auditService.addAIDecision(
         'contextual-analysis',
         prompt,
@@ -451,7 +719,6 @@ class AIPipeline {
       context.criticalConsiderations = result.content;
       this.addToContextHistory(context, `Kritische Überlegungen: ${result.content.slice(0, 200)}...`);
       
-      // AUDIT: Critical considerations
       auditService.addAIDecision(
         'contextual-analysis',
         prompt,
@@ -479,14 +746,14 @@ class AIPipeline {
     console.log('[AI-PIPELINE] Micro-task: Tool evaluation for:', tool.name);
     const taskStart = Date.now();
     const existingSelection = context.selectedTools?.find((st: any) => st.tool && st.tool.name === tool.name);
-    const taskRelevance = existingSelection?.taskRelevance || 70;
-    const priority = this.derivePriorityFromScore(taskRelevance);
+    const originalTaskRelevance = existingSelection?.taskRelevance || 70;
+    const moderatedTaskRelevance = this.moderateTaskRelevance(originalTaskRelevance);
+    const priority = this.derivePriorityFromScore(moderatedTaskRelevance);
     
-    const prompt = getPrompt('toolEvaluation', context.userQuery, tool, rank, taskRelevance);
+    const prompt = getPrompt('toolEvaluation', context.userQuery, tool, rank, moderatedTaskRelevance);
     const result = await this.callMicroTaskAI(prompt, context, 1000, 'tool-evaluation');
     
     if (result.success) {
-      // FIXED: Use centralized JSON parsing
       const evaluation = JSONParser.safeParseJSON(result.content, {
         detailed_explanation: 'Evaluation failed',
         implementation_approach: '',
@@ -500,16 +767,15 @@ class AIPipeline {
         evaluation: {
           ...evaluation,
           rank,
-          task_relevance: taskRelevance
+          task_relevance: moderatedTaskRelevance
         }
-      }, 'evaluation', priority, evaluation.detailed_explanation, taskRelevance, evaluation.limitations);
+      }, 'evaluation', priority, evaluation.detailed_explanation, moderatedTaskRelevance, evaluation.limitations);
       
-      // AUDIT: Tool evaluation
       auditService.addAIDecision(
         'tool-evaluation',
         prompt,
         result.content,
-        taskRelevance,
+        moderatedTaskRelevance,
         `Evaluated tool ${tool.name} for ${context.mode} mode`,
         taskStart,
         {
@@ -517,7 +783,9 @@ class AIPipeline {
           toolName: tool.name,
           toolType: tool.type,
           rank,
-          taskRelevance,
+          originalTaskRelevance,
+          moderatedTaskRelevance,
+          moderationApplied: originalTaskRelevance !== moderatedTaskRelevance,
           evaluationParsed: !!evaluation.detailed_explanation,
           prosCount: evaluation.pros?.length || 0,
           limitationsCount: evaluation.limitations?.length || 0,
@@ -548,7 +816,6 @@ class AIPipeline {
     const result = await this.callMicroTaskAI(prompt, context, 700, 'background-knowledge');
     
     if (result.success) {
-      // FIXED: Use centralized JSON parsing
       const selections = JSONParser.safeParseJSON(result.content, []);
       
       if (Array.isArray(selections)) {
@@ -559,7 +826,6 @@ class AIPipeline {
           relevance: sel.relevance
         }));
         
-        // AUDIT: Background knowledge selection
         auditService.addEntry(
           'knowledge-synthesis',
           'concept-selection',
@@ -596,7 +862,6 @@ class AIPipeline {
     const result = await this.callMicroTaskAI(prompt, context, 350, 'final-recommendations');
     
     if (result.success) {
-      // AUDIT: Final recommendations
       auditService.addAIDecision(
         'synthesis',
         prompt,
@@ -617,152 +882,6 @@ class AIPipeline {
     return result;
   }
 
-  private async completeUnderrepresentedPhases(context: PipelineContext, toolsData: any, pipelineStart: number): Promise<void> {
-    const phases = toolsData.phases || [];
-    const selectedPhases = new Map<string, number>();
-    
-    context.selectedTools?.forEach((st: any) => {
-      const count = selectedPhases.get(st.phase) || 0;
-      selectedPhases.set(st.phase, count + 1);
-    });
-    
-    const underrepresentedPhases = phases.filter((phase: any) => {
-      const count = selectedPhases.get(phase.id) || 0;
-      return count <= 1;
-    });
-    
-    if (underrepresentedPhases.length === 0) {
-      console.log('[AI-PIPELINE] All phases adequately represented');
-      return;
-    }
-    
-    console.log('[AI-PIPELINE] Completing underrepresented phases:', underrepresentedPhases.map((p: any) => p.id).join(', '));
-    
-    // AUDIT: Phase completion start
-    auditService.addEntry(
-      'phase-completion',
-      'underrepresented-phases-detected',
-      { 
-        underrepresentedPhases: underrepresentedPhases.map(p => p.id),
-        currentPhaseDistribution: Array.from(selectedPhases.entries())
-      },
-      { 
-        phasesToComplete: underrepresentedPhases.length,
-        completionStrategy: 'semantic-search'
-      },
-      70,
-      pipelineStart,
-      {
-        totalPhases: phases.length,
-        adequatelyRepresented: phases.length - underrepresentedPhases.length,
-        completionMethod: 'semantic-phase-search'
-      }
-    );
-    
-    for (const phase of underrepresentedPhases) {
-      await this.completePhaseWithSemanticSearch(context, phase, toolsData, pipelineStart);
-      await this.delay(this.config.microTaskDelay);
-    }
-  }
-
-  private async completePhaseWithSemanticSearch(context: PipelineContext, phase: any, toolsData: any, pipelineStart: number): Promise<void> {
-    const phaseStart = Date.now();
-    const phaseQuery = `forensic ${phase.name.toLowerCase()} tools methods`;
-    
-    console.log('[AI-PIPELINE] Phase completion for:', phase.id);
-    
-    try {
-      const phaseResults = await embeddingsService.findSimilar(phaseQuery, 20, 0.2);
-      
-      // AUDIT: Embeddings search for phase completion
-      auditService.addEmbeddingsSearch(
-        phaseQuery,
-        phaseResults,
-        0.2,
-        phaseStart,
-        {
-          phaseId: phase.id,
-          phaseName: phase.name,
-          completionPurpose: 'underrepresented-phase-enhancement'
-        }
-      );
-      
-      if (phaseResults.length === 0) {
-        console.log('[AI-PIPELINE] No semantic results for phase:', phase.id);
-        return;
-      }
-      
-      const toolsMap = new Map(toolsData.tools.map((tool: any) => [tool.name, tool]));
-      
-      const phaseTools = phaseResults
-        .filter((result: any) => result.type === 'tool')
-        .map((result: any) => toolsMap.get(result.name))
-        .filter((tool: any): tool is NonNullable<any> =>
-          tool !== undefined &&
-          tool !== null &&
-          tool.phases &&
-          Array.isArray(tool.phases) &&
-          tool.phases.includes(phase.id) &&
-          !context.seenToolNames.has(tool.name)
-        )
-        .slice(0, 2);
-      
-      if (phaseTools.length === 0) {
-        console.log('[AI-PIPELINE] No suitable tools for phase completion:', phase.id);
-        return;
-      }
-      
-      // Add tools with justification and audit each addition
-      for (const tool of phaseTools) {
-        const justification = `Nachträglich hinzugefügt zur Vervollständigung der ${phase.name}-Phase. Die ursprüngliche KI-Auswahl war zu spezifisch und hat wichtige Tools für diese Phase übersehen.`;
-        
-        this.addToolToSelection(
-          context,
-          tool,
-          phase.id,
-          'medium',
-          justification,
-          75,
-          ['Nachträgliche Ergänzung via semantische Phasensuche']
-        );
-        
-        // AUDIT: Phase completion tool addition
-        auditService.addPhaseCompletion(
-          phase.id,
-          [tool.name],
-          justification,
-          phaseStart,
-          {
-            toolName: tool.name,
-            toolType: tool.type,
-            semanticSimilarity: phaseResults.find(r => r.name === tool.name)?.similarity,
-            completionReason: 'underrepresented-phase',
-            originalSelectionMissed: true
-          }
-        );
-        
-        console.log('[AI-PIPELINE] Added phase completion tool:', tool.name);
-      }
-      
-    } catch (error) {
-      console.error('[AI-PIPELINE] Phase completion failed for:', phase.id, error);
-      
-      // AUDIT: Phase completion failure
-      auditService.addEntry(
-        'phase-completion',
-        'completion-failed',
-        { phaseId: phase.id, error: error.message },
-        { success: false },
-        20,
-        phaseStart,
-        {
-          errorType: error.constructor.name,
-          phaseId: phase.id
-        }
-      );
-    }
-  }
-
   private buildRecommendation(context: PipelineContext, mode: string, finalContent: string): any {
     const isWorkflow = mode === 'workflow';
     
@@ -795,7 +914,6 @@ class AIPipeline {
           st.limitations || []
         );
 
-        // AUDIT: Confidence calculation for each tool
         auditService.addConfidenceCalculation(
           st.tool.name,
           confidence,
@@ -803,7 +921,8 @@ class AIPipeline {
           {
             phase: st.phase,
             priority: st.priority,
-            toolType: st.tool.type
+            toolType: st.tool.type,
+            moderatedTaskRelevance: st.taskRelevance
           }
         );
 
@@ -839,14 +958,14 @@ class AIPipeline {
           st.limitations || []
         );
 
-        // AUDIT: Confidence calculation for each tool
         auditService.addConfidenceCalculation(
           st.tool.name,
           confidence,
           Date.now(),
           {
             rank: st.tool.evaluation?.rank || 1,
-            toolType: st.tool.type
+            toolType: st.tool.type,
+            moderatedTaskRelevance: st.taskRelevance
           }
         );
 
@@ -873,7 +992,6 @@ class AIPipeline {
     }
   }
 
-  // Helper methods
   private async callMicroTaskAI(
     prompt: string, 
     context: PipelineContext, 
diff --git a/src/utils/api.ts b/src/utils/api.ts
index d7b675b..390695a 100644
--- a/src/utils/api.ts
+++ b/src/utils/api.ts
@@ -83,26 +83,21 @@ export const apiServerError = {
 };
 
 export const apiSpecial = {
-  // JSON parsing error
   invalidJSON: (): Response => 
     apiError.badRequest('Invalid JSON in request body'),
   
-  // Missing required fields
   missingRequired: (fields: string[]): Response => 
     apiError.badRequest(`Missing required fields: ${fields.join(', ')}`),
   
-  // Empty request body
   emptyBody: (): Response => 
     apiError.badRequest('Request body cannot be empty'),
   
-  // File upload responses
   uploadSuccess: (data: { url: string; filename: string; size: number; storage: string }): Response => 
     apiResponse.created(data),
   
   uploadFailed: (error: string): Response => 
     apiServerError.internal(`Upload failed: ${error}`),
   
-  // Contribution responses
   contributionSuccess: (data: { prUrl?: string; branchName?: string; message: string }): Response => 
     apiResponse.created({ success: true, ...data }),
   
@@ -114,7 +109,6 @@ export const apiWithHeaders = {
   successWithHeaders: (data: any, headers: Record<string, string>): Response => 
     createAPIResponse(data, 200, headers),
   
-  // Redirect response
   redirect: (location: string, temporary: boolean = true): Response => 
     new Response(null, {
       status: temporary ? 302 : 301,
diff --git a/src/utils/auditService.ts b/src/utils/auditService.ts
index f57fb3d..6ef4df2 100644
--- a/src/utils/auditService.ts
+++ b/src/utils/auditService.ts
@@ -101,7 +101,6 @@ class AuditService {
 
     this.activeAuditTrail.push(entry);
     
-    // Enforce max entries limit
     if (this.activeAuditTrail.length > this.config.maxEntries) {
       this.activeAuditTrail.shift();
     }
@@ -109,7 +108,6 @@ class AuditService {
     console.log(`[AUDIT-SERVICE] ${phase}/${action}: ${confidence}% confidence, ${entry.processingTimeMs}ms`);
   }
 
-  // NEW: Specialized audit methods for forensic transparency
   addAIDecision(
     phase: string,
     aiPrompt: string,
@@ -162,24 +160,28 @@ class AuditService {
 
   addPhaseCompletion(
     phaseId: string,
-    toolsAdded: string[],
-    completionReasoning: string,
+    addedTools: string[],
+    reasoning: string,
     startTime: number,
     metadata: Record<string, any> = {}
   ): void {
     this.addEntry(
       'phase-completion',
       'phase-enhancement',
-      { phaseId, underrepresentedPhase: true },
-      { toolsAdded },
-      75, // Default confidence for phase completion
+      {
+        phaseId,
+        addedTools,
+        reasoning: reasoning.slice(0, 200)
+      },
+      {
+        toolsAddedCount: addedTools.length,
+        enhancementMethod: 'semantic-search-with-ai-reasoning'
+      },
+      metadata.moderatedTaskRelevance || 75,
       startTime,
       {
         ...metadata,
-        phaseId,
-        toolsAdded,
-        completionReasoning,
-        enhancementType: 'semantic-phase-completion'
+        phaseCompletionMethod: 'sophisticated-ai-reasoning'
       }
     );
   }
@@ -215,25 +217,30 @@ class AuditService {
 
   addConfidenceCalculation(
     toolName: string,
-    confidenceBreakdown: any,
+    confidence: any,
     startTime: number,
     metadata: Record<string, any> = {}
   ): void {
     this.addEntry(
       'confidence-scoring',
       'tool-confidence',
-      { toolName },
-      { confidenceBreakdown },
-      confidenceBreakdown.overall || 50,
+      {
+        toolName,
+        confidence: {
+          overall: confidence.overall,
+          semantic: confidence.semanticRelevance,
+          task: confidence.taskSuitability
+        }
+      },
+      {
+        uncertaintyFactorsCount: confidence.uncertaintyFactors?.length || 0,
+        strengthIndicatorsCount: confidence.strengthIndicators?.length || 0
+      },
+      confidence.overall,
       startTime,
       {
         ...metadata,
-        confidenceFactors: [
-          ...(confidenceBreakdown.strengthIndicators || []),
-          ...(confidenceBreakdown.uncertaintyFactors || [])
-        ],
-        semanticRelevance: confidenceBreakdown.semanticRelevance,
-        taskSuitability: confidenceBreakdown.taskSuitability
+        confidenceCalculation: true
       }
     );
   }
@@ -300,7 +307,6 @@ class AuditService {
     return { ...this.config };
   }
 
-  // Statistics and analysis methods (enhanced)
   getAuditStatistics(auditTrail: AuditEntry[]): {
     totalTime: number;
     avgConfidence: number;
@@ -346,12 +352,10 @@ class AuditService {
     const lowConfidenceSteps = auditTrail.filter(entry => (entry.confidence || 0) < 60).length;
     const mediumConfidenceSteps = auditTrail.length - highConfidenceSteps - lowConfidenceSteps;
 
-    // Enhanced metrics
     const aiDecisionCount = auditTrail.filter(entry => entry.action === 'ai-decision').length;
     const embeddingsUsageCount = auditTrail.filter(entry => entry.metadata?.embeddingsUsed).length;
     const toolSelectionCount = auditTrail.filter(entry => entry.action === 'selection-decision').length;
 
-    // Phase breakdown
     const phaseBreakdown: Record<string, { count: number; avgConfidence: number; totalTime: number }> = {};
     
     auditTrail.forEach(entry => {
@@ -364,7 +368,6 @@ class AuditService {
       phaseBreakdown[phase].totalTime += entry.processingTimeMs || 0;
     });
 
-    // Calculate average confidence per phase
     Object.keys(phaseBreakdown).forEach(phase => {
       const phaseEntries = auditTrail.filter(entry => entry.phase === phase);
       const validEntries = phaseEntries.filter(entry => typeof entry.confidence === 'number');
@@ -425,7 +428,6 @@ class AuditService {
         return;
       }
 
-      // Required fields validation
       const requiredFields = ['timestamp', 'phase', 'action'];
       requiredFields.forEach(field => {
         if (!(field in entry)) {
@@ -433,7 +435,6 @@ class AuditService {
         }
       });
 
-      // Enhanced validation for audit quality
       if (entry.action === 'ai-decision' && !entry.metadata?.aiPrompt && !entry.metadata?.reasoning) {
         warnings.push(`Entry ${index}: AI decision lacks transparency (no prompt or reasoning)`);
       }
@@ -442,7 +443,6 @@ class AuditService {
         warnings.push(`Entry ${index}: Tool selection lacks methodology info`);
       }
 
-      // Data type validation
       if (typeof entry.confidence !== 'number' || entry.confidence < 0 || entry.confidence > 100) {
         warnings.push(`Entry ${index} has invalid confidence value: ${entry.confidence}`);
       }
diff --git a/src/utils/clientUtils.ts b/src/utils/clientUtils.ts
index 3ce458c..b82c874 100644
--- a/src/utils/clientUtils.ts
+++ b/src/utils/clientUtils.ts
@@ -1,6 +1,5 @@
-// src/utils/clientUtils.ts - Consolidated (removes duplicates from toolHelpers.ts)
+// src/utils/clientUtils.ts
 
-// Tool helper functions (moved here to avoid circular imports)
 export function createToolSlug(toolName: string): string {
   if (!toolName || typeof toolName !== 'string') {
     console.warn('[CLIENT-UTILS] Invalid toolName provided to createToolSlug:', toolName);
@@ -30,7 +29,6 @@ export function isToolHosted(tool: any): boolean {
          tool.projectUrl.trim() !== "";
 }
 
-// Text and display utilities
 export function sanitizeText(text: string): string {
   if (typeof text !== 'string') return '';
   
@@ -60,7 +58,6 @@ export function truncateText(text: string, maxLength: number): string {
   return text.slice(0, maxLength) + '...';
 }
 
-// Data summarization utilities
 export function summarizeData(data: any): string {
   if (data === null || data === undefined) return 'null';
   if (typeof data === 'string') {
@@ -85,7 +82,6 @@ export function summarizeData(data: any): string {
   return String(data);
 }
 
-// Time formatting utilities
 export function formatDuration(ms: number): string {
   if (ms < 1000) return '< 1s';
   if (ms < 60000) return `${Math.ceil(ms / 1000)}s`;
@@ -94,7 +90,6 @@ export function formatDuration(ms: number): string {
   return seconds > 0 ? `${minutes}m ${seconds}s` : `${minutes}m`;
 }
 
-// DOM utilities
 export function showElement(element: HTMLElement | null): void {
   if (element) {
     element.style.display = 'block';
@@ -109,7 +104,6 @@ export function hideElement(element: HTMLElement | null): void {
   }
 }
 
-// Autocomplete functionality (kept from original clientUtils.ts as it's UI-specific)
 interface AutocompleteOptions {
   minLength?: number;
   maxResults?: number;
diff --git a/src/utils/confidenceScoring.ts b/src/utils/confidenceScoring.ts
index cc1c641..4f4fd0a 100644
--- a/src/utils/confidenceScoring.ts
+++ b/src/utils/confidenceScoring.ts
@@ -38,13 +38,13 @@ class ConfidenceScoring {
   constructor() {
     this.config = {
       semanticWeight: this.getEnvFloat('CONFIDENCE_SEMANTIC_WEIGHT', 0.3),
-      suitabilityWeight: this.getEnvFloat('CONFIDENCE_SUITABILITY_WEIGHT', 0.7),
+      suitabilityWeight: this.getEnvFloat('CONFIDENCE_SUITABILITY_WEIGHT', 0.7), 
       minimumThreshold: this.getEnvInt('CONFIDENCE_MINIMUM_THRESHOLD', 40),
       mediumThreshold: this.getEnvInt('CONFIDENCE_MEDIUM_THRESHOLD', 60),
       highThreshold: this.getEnvInt('CONFIDENCE_HIGH_THRESHOLD', 80)
     };
 
-    console.log('[CONFIDENCE-SCORING] Initialized with config:', this.config);
+    console.log('[CONFIDENCE-SCORING] Initialized with restored config:', this.config);
   }
 
   private getEnvFloat(key: string, defaultValue: number): number {
@@ -70,7 +70,6 @@ class ConfidenceScoring {
     
     let enhancedTaskSuitability = taskRelevance;
     
-    // Phase alignment bonus for workflow mode
     if (context.mode === 'workflow') {
       const toolSelection = context.selectedTools?.find((st: any) => st.tool && st.tool.name === tool.name);
       if (toolSelection && tool.phases && Array.isArray(tool.phases) && tool.phases.includes(toolSelection.phase)) {
@@ -116,18 +115,15 @@ class ConfidenceScoring {
   ): string[] {
     const factors: string[] = [];
     
-    // Add explicit limitations
     if (limitations?.length > 0) {
       factors.push(...limitations.slice(0, 2));
     }
     
-    // Semantic similarity concerns
     const similarity = context.embeddingsSimilarities.get(tool.name) || 0.5;
     if (similarity < 0.7) {
       factors.push('Geringe semantische Ähnlichkeit zur Anfrage');
     }
     
-    // Skill level vs query complexity mismatches
     if (tool.skillLevel === 'expert' && /schnell|rapid|triage|urgent|sofort/i.test(context.userQuery)) {
       factors.push('Experten-Tool für zeitkritisches Szenario');
     }
@@ -136,17 +132,14 @@ class ConfidenceScoring {
       factors.push('Einsteiger-Tool für komplexe Analyse');
     }
     
-    // Technical accessibility concerns
     if (tool.type === 'software' && !isToolHosted(tool) && tool.accessType === 'download') {
       factors.push('Installation und Setup erforderlich');
     }
     
-    // Licensing concerns
     if (tool.license === 'Proprietary') {
       factors.push('Kommerzielle Software - Lizenzkosten zu beachten');
     }
     
-    // Overall confidence concerns
     if (confidence < 60) {
       factors.push('Moderate Gesamtbewertung - alternative Ansätze empfohlen');
     }
@@ -157,28 +150,23 @@ class ConfidenceScoring {
   private identifyStrengthIndicators(tool: any, context: AnalysisContext, confidence: number): string[] {
     const indicators: string[] = [];
     
-    // High semantic relevance
     const similarity = context.embeddingsSimilarities.get(tool.name) || 0.5;
     if (similarity >= 0.7) {
       indicators.push('Sehr gute semantische Übereinstimmung mit Ihrer Anfrage');
     }
     
-    // Documentation availability
     if (tool.knowledgebase === true) {
       indicators.push('Umfassende Dokumentation und Wissensbasis verfügbar');
     }
     
-    // Immediate availability
     if (isToolHosted(tool)) {
       indicators.push('Sofort verfügbar über gehostete Lösung');
     }
     
-    // Balanced skill requirements
     if (tool.skillLevel === 'intermediate' || tool.skillLevel === 'advanced') {
       indicators.push('Ausgewogenes Verhältnis zwischen Funktionalität und Benutzerfreundlichkeit');
     }
     
-    // Method-query alignment
     if (tool.type === 'method' && /methodik|vorgehen|prozess|ansatz/i.test(context.userQuery)) {
       indicators.push('Methodischer Ansatz passt zu Ihrer prozeduralen Anfrage');
     }
@@ -197,12 +185,10 @@ class ConfidenceScoring {
     
     let confidence = 60;
     
-    // Selection ratio scoring
     if (selectionRatio > 0.05 && selectionRatio < 0.3) confidence += 20;
     else if (selectionRatio <= 0.05) confidence -= 10;
     else confidence -= 15;
     
-    // Quality indicators
     if (hasReasoning) confidence += 15;
     if (result.selectedConcepts?.length > 0) confidence += 5;
     
diff --git a/src/utils/jsonUtils.ts b/src/utils/jsonUtils.ts
index 3a5e2ac..26fc0af 100644
--- a/src/utils/jsonUtils.ts
+++ b/src/utils/jsonUtils.ts
@@ -1,10 +1,9 @@
-// src/utils/jsonUtils.ts - Centralized JSON parsing and utilities
+// src/utils/jsonUtils.ts
 export class JSONParser {
   static safeParseJSON(jsonString: string, fallback: any = null): any {
     try {
       let cleaned = jsonString.trim();
       
-      // Remove code block markers
       const jsonBlockPatterns = [
         /```json\s*([\s\S]*?)\s*```/i,
         /```\s*([\s\S]*?)\s*```/i,
@@ -19,7 +18,6 @@ export class JSONParser {
         }
       }
       
-      // Handle truncated JSON
       if (!cleaned.endsWith('}') && !cleaned.endsWith(']')) {
         console.warn('[JSON-PARSER] JSON appears truncated, attempting recovery');
         cleaned = this.repairTruncatedJSON(cleaned);
@@ -27,7 +25,6 @@ export class JSONParser {
       
       const parsed = JSON.parse(cleaned);
       
-      // Ensure proper structure for tool selection responses
       if (parsed && typeof parsed === 'object') {
         if (!parsed.selectedTools) parsed.selectedTools = [];
         if (!parsed.selectedConcepts) parsed.selectedConcepts = [];
@@ -109,7 +106,6 @@ export class JSONParser {
       }
     }
     
-    // Fallback: extract any quoted strings that look like tool names
     if (selectedTools.length === 0 && selectedConcepts.length === 0) {
       const allMatches = jsonString.match(/"([^"]+)"/g);
       if (allMatches) {
@@ -139,7 +135,6 @@ export class JSONParser {
       throw new Error(`JSON string too large (${jsonString.length} bytes, max ${maxSize})`);
     }
 
-    // Security checks for potentially malicious content
     const suspiciousPatterns = [
       /<script/i,
       /javascript:/i,
@@ -158,7 +153,6 @@ export class JSONParser {
     try {
       const parsed = JSON.parse(jsonString);
       
-      // Validate basic structure
       if (typeof parsed !== 'object' || parsed === null) {
         throw new Error('JSON must be an object');
       }
@@ -182,11 +176,9 @@ export class JSONParser {
     }
 
     if (typeof obj === 'string') {
-      // Sanitize strings that might contain sensitive data
       if (obj.length > 500) {
         return obj.slice(0, 500) + '...[truncated]';
       }
-      // Remove potential code injection patterns
       return obj.replace(/<script[\s\S]*?<\/script>/gi, '[script removed]');
     }
 
@@ -217,7 +209,6 @@ export class JSONParser {
 
       const sanitized: any = {};
       keys.forEach(key => {
-        // Skip potential dangerous properties
         if (['__proto__', 'constructor', 'prototype'].includes(key)) {
           return;
         }
@@ -237,7 +228,6 @@ export class JSONParser {
       return { isValid: false, errors };
     }
 
-    // Check required top-level properties
     const requiredProps = ['metadata', 'recommendation', 'auditTrail'];
     for (const prop of requiredProps) {
       if (!(prop in data)) {
@@ -245,7 +235,6 @@ export class JSONParser {
       }
     }
 
-    // Validate metadata
     if (data.metadata && typeof data.metadata === 'object') {
       const requiredMetadataProps = ['timestamp', 'version', 'userQuery', 'mode'];
       for (const prop of requiredMetadataProps) {
@@ -257,7 +246,6 @@ export class JSONParser {
       errors.push('Invalid metadata structure');
     }
 
-    // Validate audit trail
     if (!Array.isArray(data.auditTrail)) {
       errors.push('auditTrail must be an array');
     } else {
@@ -293,7 +281,7 @@ export class JSONParser {
       metadata: {
         timestamp: new Date().toISOString(),
         version: "1.0",
-        userQuery: userQuery.slice(0, 1000), // Truncate for security
+        userQuery: userQuery.slice(0, 1000),
         mode,
         exportedBy: 'ForensicPathways',
         toolsDataHash: additionalMetadata.toolsDataHash || 'unknown',
@@ -316,16 +304,13 @@ export class JSONParser {
     const issues: string[] = [];
     const warnings: string[] = [];
 
-    // Basic structure validation
     const structureValidation = this.validateAuditExportStructure(data);
     if (!structureValidation.isValid) {
       issues.push(...structureValidation.errors);
       return { isValid: false, issues, warnings };
     }
 
-    // Additional validation for uploaded content
     if (data.metadata) {
-      // Check timestamp validity
       const timestamp = new Date(data.metadata.timestamp);
       if (isNaN(timestamp.getTime())) {
         warnings.push('Invalid timestamp in metadata');
@@ -337,13 +322,11 @@ export class JSONParser {
         }
       }
 
-      // Validate mode
       if (!['workflow', 'tool'].includes(data.metadata.mode)) {
         warnings.push(`Unknown analysis mode: ${data.metadata.mode}`);
       }
     }
 
-    // Validate audit trail quality
     if (Array.isArray(data.auditTrail)) {
       const aiDecisions = data.auditTrail.filter(e => e.action === 'ai-decision').length;
       const toolSelections = data.auditTrail.filter(e => e.action === 'selection-decision').length;
@@ -356,7 +339,6 @@ export class JSONParser {
         warnings.push('No tool selections found in audit trail');
       }
 
-      // Check for confidence values
       const entriesWithConfidence = data.auditTrail.filter(e => typeof e.confidence === 'number').length;
       const confidenceRatio = entriesWithConfidence / data.auditTrail.length;
       
diff --git a/src/utils/toolSelector.ts b/src/utils/toolSelector.ts
index 53a3f98..20e15d9 100644
--- a/src/utils/toolSelector.ts
+++ b/src/utils/toolSelector.ts
@@ -2,7 +2,7 @@
 import { aiService } from './aiService.js';
 import { embeddingsService, type SimilarityResult } from './embeddings.js';
 import { confidenceScoring } from './confidenceScoring.js';
-import { JSONParser } from './jsonUtils.js'; // FIXED: Use centralized JSON parsing
+import { JSONParser } from './jsonUtils.js';
 import { getPrompt } from '../config/prompts.js';
 import 'dotenv/config';
 
@@ -111,7 +111,6 @@ class ToolSelector {
       
       console.log('[TOOL-SELECTOR] Embeddings found', similarItems.length, 'similar items');
       
-      // Store similarities for confidence calculation
       similarItems.forEach(item => {
         context.embeddingsSimilarities.set(item.name, item.similarity);
       });
@@ -238,7 +237,6 @@ class ToolSelector {
     const basePrompt = getPrompt('toolSelection', mode, userQuery, selectionMethod, this.config.maxSelectedItems);
     const prompt = getPrompt('toolSelectionWithData', basePrompt, toolsToSend, conceptsToSend);
 
-    // Validate prompt length
     aiService.validatePromptLength(prompt);
 
     console.log('[TOOL-SELECTOR] Sending to AI:', 
@@ -249,7 +247,6 @@ class ToolSelector {
 
     try {
       const response = await aiService.callAI(prompt, { maxTokens: 2500 });
-      // FIXED: Use centralized JSON parsing
       const result = JSONParser.safeParseJSON(response.content, null);
       
       if (!result || !Array.isArray(result.selectedTools) || !Array.isArray(result.selectedConcepts)) {
@@ -315,7 +312,6 @@ class ToolSelector {
     
     try {
       const response = await aiService.callMicroTaskAI(prompt, 1000);
-      // FIXED: Use centralized JSON parsing
       const selections = JSONParser.safeParseJSON(response.content, []);
       
       if (Array.isArray(selections)) {
@@ -368,8 +364,6 @@ class ToolSelector {
     related_software: concept.related_software || []
   });
 
-  // REMOVED: safeParseJSON method - now using centralized version from jsonUtils.ts
-
   getConfig(): ToolSelectionConfig {
     return { ...this.config };
   }