chore: task management and formatting.
This commit is contained in:
Eyal Toledano
@@ -256,7 +256,7 @@ Apply telemetry pattern from telemetry.mdc:
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## 12. Telemetry Integration for analyze-task-complexity [done]
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### Dependencies: None
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### Description: Integrate AI usage telemetry capture and propagation for the analyze-task-complexity functionality.
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### Description: Integrate AI usage telemetry capture and propagation for the analyze-task-complexity functionality. [Updated: 5/9/2025]
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### Details:
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\
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Apply telemetry pattern from telemetry.mdc:
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@@ -276,6 +276,110 @@ Apply telemetry pattern from telemetry.mdc:
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3. **Tool (`mcp-server/src/tools/analyze.js`):**
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* Verify `handleApiResult` correctly passes `data.telemetryData` through.
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<info added on 2025-05-09T04:02:44.847Z>
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## Implementation Details for Telemetry Integration
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### Best Practices for Implementation
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1. **Use Structured Telemetry Objects:**
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- Create a standardized `TelemetryEvent` object with fields:
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```javascript
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{
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commandName: string, // e.g., 'analyze-complexity'
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timestamp: ISO8601 string,
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duration: number, // in milliseconds
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inputTokens: number,
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outputTokens: number,
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model: string, // e.g., 'gpt-4'
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success: boolean,
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errorType?: string, // if applicable
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metadata: object // command-specific context
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}
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```
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2. **Asynchronous Telemetry Processing:**
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- Use non-blocking telemetry submission to avoid impacting performance
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- Implement queue-based processing for reliability during network issues
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3. **Error Handling:**
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- Implement robust try/catch blocks around telemetry operations
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- Ensure telemetry failures don't affect core functionality
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- Log telemetry failures locally for debugging
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4. **Privacy Considerations:**
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- Never include PII or sensitive data in telemetry
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- Implement data minimization principles
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- Add sanitization functions for metadata fields
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5. **Testing Strategy:**
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- Create mock telemetry endpoints for testing
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- Add unit tests verifying correct telemetry data structure
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- Implement integration tests for end-to-end telemetry flow
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### Code Implementation Examples
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```javascript
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// Example telemetry submission function
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async function submitTelemetry(telemetryData, endpoint) {
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try {
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// Non-blocking submission
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fetch(endpoint, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(telemetryData)
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}).catch(err => console.error('Telemetry submission failed:', err));
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} catch (error) {
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// Log locally but don't disrupt main flow
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console.error('Telemetry error:', error);
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}
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}
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// Example integration in AI service call
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async function callAiService(params) {
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const startTime = Date.now();
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try {
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const result = await aiService.call({
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...params,
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commandName: 'analyze-complexity',
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outputType: 'mcp'
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});
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// Construct telemetry object
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const telemetryData = {
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commandName: 'analyze-complexity',
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timestamp: new Date().toISOString(),
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duration: Date.now() - startTime,
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inputTokens: result.usage?.prompt_tokens || 0,
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outputTokens: result.usage?.completion_tokens || 0,
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model: result.model || 'unknown',
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success: true,
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metadata: {
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taskId: params.taskId,
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// Add other relevant non-sensitive metadata
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}
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};
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return { mainResult: result.data, telemetryData };
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} catch (error) {
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// Error telemetry
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const telemetryData = {
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commandName: 'analyze-complexity',
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timestamp: new Date().toISOString(),
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duration: Date.now() - startTime,
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success: false,
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errorType: error.name,
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metadata: {
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taskId: params.taskId,
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errorMessage: sanitizeErrorMessage(error.message)
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}
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};
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// Re-throw the original error after capturing telemetry
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throw error;
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}
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}
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```
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</info added on 2025-05-09T04:02:44.847Z>
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## 13. Update google.js for Telemetry Compatibility [pending]
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### Dependencies: None
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@@ -5028,8 +5028,8 @@
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{
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"id": 12,
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"title": "Telemetry Integration for analyze-task-complexity",
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"description": "Integrate AI usage telemetry capture and propagation for the analyze-task-complexity functionality.",
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"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",
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"description": "Integrate AI usage telemetry capture and propagation for the analyze-task-complexity functionality. [Updated: 5/9/2025]",
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"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>",
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"status": "done",
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"dependencies": [],
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"parentTaskId": 77
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