{"record":{"id":"0dc8f31f18c730ab","repo":"flipped-aurora/gin-vue-admin","slug":"v-0dc8f3","errorCode":null,"errorMessage":"需求分析失败: %v","messagePattern":"需求分析失败: (.+?)","errorType":"exception","errorClass":null,"httpStatus":null,"severity":"error","filePath":"server/mcp/requirement_analyzer.go","lineNumber":72,"sourceCode":" `),\n\t\tmcp.WithString(\"userRequirement\",\n\t\t\tmcp.Required(),\n\t\t\tmcp.Description(\"用户的需求描述，支持自然语言，如：'我要做一个猫舍管理系统，用来录入猫的信息，并且记录每只猫每天的活动信息'\"),\n\t\t),\n\t)\n}\n\n// Handle 处理工具调用\nfunc (t *RequirementAnalyzer) Handle(ctx context.Context, request mcp.CallToolRequest) (*mcp.CallToolResult, error) {\n\tuserRequirement, ok := request.GetArguments()[\"userRequirement\"].(string)\n\tif !ok || userRequirement == \"\" {\n\t\treturn nil, errors.New(\"参数错误：userRequirement 必须是非空字符串\")\n\t}\n\n\t// 分析用户需求\n\tanalysisResponse, err := t.analyzeRequirement(userRequirement)\n\tif err != nil {\n\t\treturn nil, fmt.Errorf(\"需求分析失败: %v\", err)\n\t}\n\n\t// 序列化响应\n\treturn textResultWithJSON(\"\", analysisResponse)\n}\n\n// analyzeRequirement 分析用户需求 - 专注于AI需求传递\nfunc (t *RequirementAnalyzer) analyzeRequirement(userRequirement string) (*RequirementAnalysisResponse, error) {\n\t// 生成AI提示词 - 这是唯一功能\n\taiPrompt := t.generateAIPrompt(userRequirement)\n\n\treturn &RequirementAnalysisResponse{\n\t\tAIPrompt: aiPrompt,\n\t}, nil\n}\n\n// generateAIPrompt 生成AI提示词 - 智能分析需求并确定模块结构\nfunc (t *RequirementAnalyzer) generateAIPrompt(userRequirement string) string {","sourceCodeStart":54,"sourceCodeEnd":90,"githubUrl":"https://github.com/flipped-aurora/gin-vue-admin/blob/3136500ef380842b0eb6c4daa87c3f8a47fcf9e0/server/mcp/requirement_analyzer.go#L54-L90","documentation":"Wrap of any failure inside requirement_analyzer's analyzeRequirement, including the LLM/API call it performs. It signals that the natural-language requirement analysis step failed, before any JSON serialization happens.","triggerScenarios":"Handle receives a valid non-empty userRequirement, but analyzeRequirement errors — typically the downstream analysis backend (LLM endpoint) is unreachable, returns an error, rate-limits, or times out.","commonSituations":"Missing or invalid LLM API key in MCP server config; network egress blocked; provider rate limit/quota exhausted; prompt too long exceeding model context limit.","solutions":["Read the wrapped %v cause to identify whether it is auth, network, or quota","Check the analysis backend API key/endpoint configuration on the MCP server","Retry with a shorter userRequirement if a context/length error is reported","Handle provider rate limits with backoff before retrying"],"exampleFix":null,"handlingStrategy":"try-catch","validationCode":"if strings.TrimSpace(userRequirement) == \"\" {\n    return errors.New(\"userRequirement must be a non-empty string\")\n}\nif len(userRequirement) > maxPromptLen {\n    return fmt.Errorf(\"userRequirement too long: %d > %d\", len(userRequirement), maxPromptLen)\n}","typeGuard":null,"tryCatchPattern":"analysis, err := analyzer.Handle(ctx, args)\nif err != nil {\n    var rateLimit *RateLimitError\n    switch {\n    case errors.As(err, &rateLimit):\n        time.Sleep(rateLimit.RetryAfter); return retry(args)\n    case isAuthError(err):\n        return fmt.Errorf(\"check LLM API key config: %w\", err)\n    default:\n        return err\n    }\n}","preventionTips":["Verify the analysis backend API key and endpoint at MCP server startup","Cap userRequirement length before invoking","Implement exponential backoff for provider rate limits"],"tags":["llm","upstream-api","analysis"],"backgroundTag":"llm-backend-request-failed","analyzedSha":"3136500ef380842b0eb6c4daa87c3f8a47fcf9e0","analyzedAt":"2026-08-31T13:50:02.721Z","schemaVersion":2},"datasetVersion":"2026-08-31T19:17:28.585Z"}