chore: task management and formatting.

tasks/task_077.txt

@@ -256,7 +256,7 @@ Apply telemetry pattern from telemetry.mdc:
 
 ## 12. Telemetry Integration for analyze-task-complexity [done]
 ### Dependencies: None
-### Description: Integrate AI usage telemetry capture and propagation for the analyze-task-complexity functionality.
+### Description: Integrate AI usage telemetry capture and propagation for the analyze-task-complexity functionality. [Updated: 5/9/2025]
 ### Details:
 \
 Apply telemetry pattern from telemetry.mdc:
@@ -276,6 +276,110 @@ Apply telemetry pattern from telemetry.mdc:
 3.  **Tool (`mcp-server/src/tools/analyze.js`):**
     *   Verify `handleApiResult` correctly passes `data.telemetryData` through.
 
+<info added on 2025-05-09T04:02:44.847Z>
+## Implementation Details for Telemetry Integration
+
+### Best Practices for Implementation
+
+1. **Use Structured Telemetry Objects:**
+   - Create a standardized `TelemetryEvent` object with fields:
+     ```javascript
+     {
+       commandName: string,       // e.g., 'analyze-complexity'
+       timestamp: ISO8601 string,
+       duration: number,          // in milliseconds
+       inputTokens: number,
+       outputTokens: number,
+       model: string,             // e.g., 'gpt-4'
+       success: boolean,
+       errorType?: string,        // if applicable
+       metadata: object           // command-specific context
+     }
+     ```
+
+2. **Asynchronous Telemetry Processing:**
+   - Use non-blocking telemetry submission to avoid impacting performance
+   - Implement queue-based processing for reliability during network issues
+
+3. **Error Handling:**
+   - Implement robust try/catch blocks around telemetry operations
+   - Ensure telemetry failures don't affect core functionality
+   - Log telemetry failures locally for debugging
+
+4. **Privacy Considerations:**
+   - Never include PII or sensitive data in telemetry
+   - Implement data minimization principles
+   - Add sanitization functions for metadata fields
+
+5. **Testing Strategy:**
+   - Create mock telemetry endpoints for testing
+   - Add unit tests verifying correct telemetry data structure
+   - Implement integration tests for end-to-end telemetry flow
+
+### Code Implementation Examples
+
+```javascript
+// Example telemetry submission function
+async function submitTelemetry(telemetryData, endpoint) {
+  try {
+    // Non-blocking submission
+    fetch(endpoint, {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify(telemetryData)
+    }).catch(err => console.error('Telemetry submission failed:', err));
+  } catch (error) {
+    // Log locally but don't disrupt main flow
+    console.error('Telemetry error:', error);
+  }
+}
+
+// Example integration in AI service call
+async function callAiService(params) {
+  const startTime = Date.now();
+  try {
+    const result = await aiService.call({
+      ...params,
+      commandName: 'analyze-complexity',
+      outputType: 'mcp'
+    });
+    
+    // Construct telemetry object
+    const telemetryData = {
+      commandName: 'analyze-complexity',
+      timestamp: new Date().toISOString(),
+      duration: Date.now() - startTime,
+      inputTokens: result.usage?.prompt_tokens || 0,
+      outputTokens: result.usage?.completion_tokens || 0,
+      model: result.model || 'unknown',
+      success: true,
+      metadata: {
+        taskId: params.taskId,
+        // Add other relevant non-sensitive metadata
+      }
+    };
+    
+    return { mainResult: result.data, telemetryData };
+  } catch (error) {
+    // Error telemetry
+    const telemetryData = {
+      commandName: 'analyze-complexity',
+      timestamp: new Date().toISOString(),
+      duration: Date.now() - startTime,
+      success: false,
+      errorType: error.name,
+      metadata: {
+        taskId: params.taskId,
+        errorMessage: sanitizeErrorMessage(error.message)
+      }
+    };
+    
+    // Re-throw the original error after capturing telemetry
+    throw error;
+  }
+}
+```
+</info added on 2025-05-09T04:02:44.847Z>
 
 ## 13. Update google.js for Telemetry Compatibility [pending]
 ### Dependencies: None

tasks/tasks.json

@@ -5028,8 +5028,8 @@
         {
           "id": 12,
           "title": "Telemetry Integration for analyze-task-complexity",
-          "description": "Integrate AI usage telemetry capture and propagation for the analyze-task-complexity functionality.",
+          "description": "Integrate AI usage telemetry capture and propagation for the analyze-task-complexity functionality. [Updated: 5/9/2025]",
-          "details": "\\\nApply telemetry pattern from telemetry.mdc:\n\n1.  **Core (`scripts/modules/task-manager/analyze-task-complexity.js`):**\n    *   Modify AI service call to include `commandName: \\'analyze-complexity\\'` and `outputType`.\n    *   Receive `{ mainResult, telemetryData }`.\n    *   Return object including `telemetryData` (perhaps alongside the complexity report data).\n    *   Handle CLI display via `displayAiUsageSummary` if applicable.\n\n2.  **Direct (`mcp-server/src/core/direct-functions/analyze-task-complexity.js`):**\n    *   Pass `commandName`, `outputType: \\'mcp\\'` to core.\n    *   Pass `outputFormat: \\'json\\'` if applicable.\n    *   Receive `{ ..., telemetryData }` from core.\n    *   Return `{ success: true, data: { ..., telemetryData } }`.\n\n3.  **Tool (`mcp-server/src/tools/analyze.js`):**\n    *   Verify `handleApiResult` correctly passes `data.telemetryData` through.\n",
+          "details": "\\\nApply telemetry pattern from telemetry.mdc:\n\n1.  **Core (`scripts/modules/task-manager/analyze-task-complexity.js`):**\n    *   Modify AI service call to include `commandName: \\'analyze-complexity\\'` and `outputType`.\n    *   Receive `{ mainResult, telemetryData }`.\n    *   Return object including `telemetryData` (perhaps alongside the complexity report data).\n    *   Handle CLI display via `displayAiUsageSummary` if applicable.\n\n2.  **Direct (`mcp-server/src/core/direct-functions/analyze-task-complexity.js`):**\n    *   Pass `commandName`, `outputType: \\'mcp\\'` to core.\n    *   Pass `outputFormat: \\'json\\'` if applicable.\n    *   Receive `{ ..., telemetryData }` from core.\n    *   Return `{ success: true, data: { ..., telemetryData } }`.\n\n3.  **Tool (`mcp-server/src/tools/analyze.js`):**\n    *   Verify `handleApiResult` correctly passes `data.telemetryData` through.\n\n<info added on 2025-05-09T04:02:44.847Z>\n## Implementation Details for Telemetry Integration\n\n### Best Practices for Implementation\n\n1. **Use Structured Telemetry Objects:**\n   - Create a standardized `TelemetryEvent` object with fields:\n     ```javascript\n     {\n       commandName: string,       // e.g., 'analyze-complexity'\n       timestamp: ISO8601 string,\n       duration: number,          // in milliseconds\n       inputTokens: number,\n       outputTokens: number,\n       model: string,             // e.g., 'gpt-4'\n       success: boolean,\n       errorType?: string,        // if applicable\n       metadata: object           // command-specific context\n     }\n     ```\n\n2. **Asynchronous Telemetry Processing:**\n   - Use non-blocking telemetry submission to avoid impacting performance\n   - Implement queue-based processing for reliability during network issues\n\n3. **Error Handling:**\n   - Implement robust try/catch blocks around telemetry operations\n   - Ensure telemetry failures don't affect core functionality\n   - Log telemetry failures locally for debugging\n\n4. **Privacy Considerations:**\n   - Never include PII or sensitive data in telemetry\n   - Implement data minimization principles\n   - Add sanitization functions for metadata fields\n\n5. **Testing Strategy:**\n   - Create mock telemetry endpoints for testing\n   - Add unit tests verifying correct telemetry data structure\n   - Implement integration tests for end-to-end telemetry flow\n\n### Code Implementation Examples\n\n```javascript\n// Example telemetry submission function\nasync function submitTelemetry(telemetryData, endpoint) {\n  try {\n    // Non-blocking submission\n    fetch(endpoint, {\n      method: 'POST',\n      headers: { 'Content-Type': 'application/json' },\n      body: JSON.stringify(telemetryData)\n    }).catch(err => console.error('Telemetry submission failed:', err));\n  } catch (error) {\n    // Log locally but don't disrupt main flow\n    console.error('Telemetry error:', error);\n  }\n}\n\n// Example integration in AI service call\nasync function callAiService(params) {\n  const startTime = Date.now();\n  try {\n    const result = await aiService.call({\n      ...params,\n      commandName: 'analyze-complexity',\n      outputType: 'mcp'\n    });\n    \n    // Construct telemetry object\n    const telemetryData = {\n      commandName: 'analyze-complexity',\n      timestamp: new Date().toISOString(),\n      duration: Date.now() - startTime,\n      inputTokens: result.usage?.prompt_tokens || 0,\n      outputTokens: result.usage?.completion_tokens || 0,\n      model: result.model || 'unknown',\n      success: true,\n      metadata: {\n        taskId: params.taskId,\n        // Add other relevant non-sensitive metadata\n      }\n    };\n    \n    return { mainResult: result.data, telemetryData };\n  } catch (error) {\n    // Error telemetry\n    const telemetryData = {\n      commandName: 'analyze-complexity',\n      timestamp: new Date().toISOString(),\n      duration: Date.now() - startTime,\n      success: false,\n      errorType: error.name,\n      metadata: {\n        taskId: params.taskId,\n        errorMessage: sanitizeErrorMessage(error.message)\n      }\n    };\n    \n    // Re-throw the original error after capturing telemetry\n    throw error;\n  }\n}\n```\n</info added on 2025-05-09T04:02:44.847Z>",
           "status": "done",
           "dependencies": [],
           "parentTaskId": 77