cleanup, prompt centralization

src/utils/aiPipeline.ts

@@ -470,13 +470,11 @@ class AIPipeline {
     pipelineStart: number,
     toolsDataHash: string
   ): Promise<{ completed: number; failed: number }> {
-    // Evaluate ALL candidates handed over by the embeddings pre-filter.
     const candidates = context.filteredData.tools || [];
     if (!Array.isArray(candidates) || candidates.length === 0) {
       return { completed: completedTasks, failed: failedTasks };
     }
 
-    // Evaluate every candidate (no slicing here)
     for (let i = 0; i < candidates.length; i++) {
       const evaluationResult = await this.evaluateSpecificTool(context, candidates[i], i + 1, pipelineStart, toolsDataHash);
       if (evaluationResult.success) completedTasks++; else failedTasks++;
@@ -484,15 +482,12 @@ class AIPipeline {
       await this.delay(this.config.microTaskDelay);
     }
 
-    // At this point, context.selectedTools may contain 0..N evaluated items (added by evaluateSpecificTool).
-    // Now we sort them by AI-derived taskRelevance (after moderation) and keep ONLY the top 3 for UI.
     if (Array.isArray(context.selectedTools) && context.selectedTools.length > 0) {
       context.selectedTools.sort((a: any, b: any) => {
         const ar = typeof a.taskRelevance === 'number' ? a.taskRelevance : -1;
         const br = typeof b.taskRelevance === 'number' ? b.taskRelevance : -1;
         if (br !== ar) return br - ar;
 
-        // tie-breakers without domain heuristics:
         const aLen = (a.justification || '').length;
         const bLen = (b.justification || '').length;
         if (bLen !== aLen) return bLen - aLen;
@@ -502,7 +497,6 @@ class AIPipeline {
         return aRank - bRank;
       });
 
-      // Keep top 3 only
       context.selectedTools = context.selectedTools.slice(0, 3);
     }
 
@@ -877,7 +871,6 @@ class AIPipeline {
   ): Promise<MicroTaskResult> {
     const taskStart = Date.now();
 
-    // Build prompt WITHOUT any baseline score
     const prompt = getPrompt('toolEvaluation', context.userQuery, tool, rank);
     const result = await this.callMicroTaskAI(prompt, context, 'tool-evaluation');
 
@@ -885,16 +878,13 @@ class AIPipeline {
       return result;
     }
 
-    // Parse strictly; do NOT provide a default with a score.
     const evaluation = JSONParser.safeParseJSON(result.content, null);
 
-    // Require a numeric score produced by the model; otherwise, don't add this tool.
     const aiProvided = evaluation && typeof evaluation.taskRelevance === 'number' && Number.isFinite(evaluation.taskRelevance)
       ? Math.round(evaluation.taskRelevance)
       : null;
 
     if (aiProvided === null) {
-      // Log the malformed output but avoid injecting a synthetic score.
       auditService.addAIDecision(
         'tool-evaluation',
         prompt,
@@ -920,7 +910,6 @@ class AIPipeline {
     const moderatedTaskRelevance = this.moderateTaskRelevance(aiProvided);
     const priority = this.derivePriorityFromScore(moderatedTaskRelevance);
 
-    // Keep original fields if present; coerce to strings/arrays safely.
     const detailed_explanation = String(evaluation?.detailed_explanation || '').trim();
     const implementation_approach = String(evaluation?.implementation_approach || '').trim();
     const pros = Array.isArray(evaluation?.pros) ? evaluation.pros : [];