Copilot commented on code in PR #1319:
URL: https://github.com/apache/dubbo-admin/pull/1319#discussion_r2313485913


##########
ai/internal/schema/llm_schema.go:
##########
@@ -0,0 +1,102 @@
+package schema
+
+import (
+       "dubbo-admin-ai/internal/tools"
+       "encoding/json"
+       "fmt"
+)
+
+// 表示 LLM 的响应结构
+type ReActIn = ReActInput
+type ReActOut = string
+
+type ThinkIn = ReActInput
+type ThinkOut = ThinkAggregation
+
+type ActIn = ThinkOut
+type ActOut = []string
+
+type ReActInput struct {
+       UserInput string `json:"userInput"`
+       // 移除SessionID和SessionMemory,这些由Session管理
+}
+
+type Status string
+
+const (
+       Continued Status = "CONTINUED"
+       Finished  Status = "FINISHED"
+       Pending   Status = "PENDING"
+)
+
+type ToolRequest struct {
+       Thought  string         `json:"thought"`
+       ToolDesc tools.ToolDesc `json:"tool_desc"`
+}
+
+type ThinkAggregation struct {
+       ToolRequests []ToolRequest `json:"tool_requests"`
+       Status       Status        `json:"status" 
jsonschema:"enum=CONTINUED,enum=FINISHED,enum=PENDING"`
+       Thought      string        `json:"thought"`
+       FinalAnswer  string        `json:"final_answer,omitempty" 
jsonschema:"required=false"`
+}
+
+// ReActInput
+func (a ReActInput) String() string {
+       data, err := json.MarshalIndent(a, "", "  ")
+       if err != nil {
+               return fmt.Sprintf("ReActInput{error: %v}", err)
+       }
+       return string(data)
+}
+
+// ToolRequest
+// HasAction 检查是否包含行动指令
+func (tr ToolRequest) HasAction() bool {
+       return tr.ToolDesc.ToolInput != nil && tr.ToolDesc.ToolName != ""
+}
+
+// ValidateToolDesc 验证行动指令的有效性
+func (tr ToolRequest) ValidateToolDesc() error {
+       if !tr.HasAction() {
+               return fmt.Errorf("no valid action found")
+       }
+
+       if tr.ToolDesc.ToolName == "" {
+               return fmt.Errorf("tool_name cannot be empty")
+       }
+
+       // 验证支持的工具名称
+       supportedTools, err := tools.AllMockToolNames()
+       if err != nil {
+               return fmt.Errorf("failed to get supported tools: %w", err)
+       }
+
+       if _, ok := supportedTools[tr.ToolDesc.ToolName]; !ok {
+               return fmt.Errorf("unsupported tool: %s", tr.ToolDesc.ToolName)
+       }
+
+       return nil
+}
+
+// String 实现 fmt.Stringer 接口,返回格式化的 JSON
+func (tr ToolRequest) String() string {
+       data, err := json.MarshalIndent(tr, "", "  ")
+       if err != nil {
+               return fmt.Sprintf("ThinkAggregation{error: %v}", err)

Review Comment:
   The error message incorrectly references 'ThinkAggregation' but this is the 
String() method for ToolRequest. It should return 'ToolRequest{error: %v}' 
instead.
   ```suggestion
                return fmt.Sprintf("ToolRequest{error: %v}", err)
   ```



##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+       "fmt"
+       "log"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+       Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+       ServiceName      string  `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int     `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+       Quantile         float64 `json:"quantile" 
jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+       ToolName    string  `json:"toolName"`
+       Quantile    float64 `json:"quantile"`
+       ValueMillis int     `json:"valueMillis"`
+       Summary     string  `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input 
PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_latency' called for service: 
%s", input.ServiceName)
+
+       // Mock data based on the example in prompt
+       valueMillis := 3500
+       if input.ServiceName != "order-service" {
+               valueMillis = 850
+       }
+
+       return PrometheusServiceLatencyOutput{
+               ToolName:    "prometheus_query_service_latency",
+               Quantile:    input.Quantile,
+               ValueMillis: valueMillis,
+               // Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+       }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+       ToolName            string  `json:"toolName"`
+       RequestRateQPS      float64 `json:"requestRateQPS"`
+       ErrorRatePercentage float64 `json:"errorRatePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input 
PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_traffic' called for service: 
%s", input.ServiceName)
+
+       return PrometheusServiceTrafficOutput{
+               ToolName:            "prometheus_query_service_traffic",
+               RequestRateQPS:      250.0,
+               ErrorRatePercentage: 5.2,
+               // Summary:             fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 
5.2%%", input.ServiceName),

Review Comment:
   This line is commented out but still contains the fmt.Sprintf call. Either 
remove the entire line or uncomment it if the Summary field should be populated.
   ```suggestion
                Summary:             fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 
5.2%%", input.ServiceName),
   ```



##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+       "fmt"
+       "log"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+       Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+       ServiceName      string  `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int     `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+       Quantile         float64 `json:"quantile" 
jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+       ToolName    string  `json:"toolName"`
+       Quantile    float64 `json:"quantile"`
+       ValueMillis int     `json:"valueMillis"`
+       Summary     string  `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input 
PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_latency' called for service: 
%s", input.ServiceName)
+
+       // Mock data based on the example in prompt
+       valueMillis := 3500
+       if input.ServiceName != "order-service" {
+               valueMillis = 850
+       }
+
+       return PrometheusServiceLatencyOutput{
+               ToolName:    "prometheus_query_service_latency",
+               Quantile:    input.Quantile,
+               ValueMillis: valueMillis,
+               // Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+       }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+       ToolName            string  `json:"toolName"`
+       RequestRateQPS      float64 `json:"requestRateQPS"`
+       ErrorRatePercentage float64 `json:"errorRatePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input 
PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_traffic' called for service: 
%s", input.ServiceName)
+
+       return PrometheusServiceTrafficOutput{
+               ToolName:            "prometheus_query_service_traffic",
+               RequestRateQPS:      250.0,
+               ErrorRatePercentage: 5.2,
+               // Summary:             fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 
5.2%%", input.ServiceName),
+       }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+       PromqlQuery string `json:"promqlQuery" 
jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+       Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+       Timestamp int64  `json:"timestamp"`
+       Value     string `json:"value"`
+}
+
+type TimeseriesResult struct {
+       Metric TimeseriesMetric `json:"metric"`
+       Value  TimeseriesValue  `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+       ToolName string             `json:"toolName"`
+       Query    string             `json:"query"`
+       Results  []TimeseriesResult `json:"results"`
+       Summary  string             `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+       return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input 
QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+       log.Printf("Tool 'query_timeseries_database' called with query: %s", 
input.PromqlQuery)
+
+       return QueryTimeseriesDatabaseOutput{
+               ToolName: "query_timeseries_database",
+               Query:    input.PromqlQuery,
+               Results: []TimeseriesResult{
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-1"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.5"},
+                       },
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-2"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.2"},
+                       },
+               },
+               // Summary: "查询返回了 2 个时间序列",
+       }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+       ServiceName     string `json:"serviceName" 
jsonschema:"required,description=The name of the service to profile"`
+       PodName         string `json:"podName" 
jsonschema:"required,description=The specific pod name to profile"`
+       DurationSeconds int    `json:"durationSeconds" 
jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+       CPUTimePercentage float64  `json:"cpuTimePercentage"`
+       StackTrace        []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+       ToolName     string               `json:"toolName"`
+       Status       string               `json:"status"`
+       TotalSamples int                  `json:"totalSamples"`
+       Hotspots     []PerformanceHotspot `json:"hotspots"`
+       Summary      string               `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+       return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input 
ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, 
error) {
+       log.Printf("Tool 'application_performance_profiling' called for 
service: %s, pod: %s", input.ServiceName, input.PodName)
+
+       return ApplicationPerformanceProfilingOutput{
+               ToolName:     "application_performance_profiling",
+               Status:       "completed",
+               TotalSamples: 10000,
+               Hotspots: []PerformanceHotspot{
+                       {
+                               CPUTimePercentage: 45.5,
+                               StackTrace: []string{
+                                       
"com.example.OrderService.processOrder()",
+                                       "com.example.DatabaseClient.query()",
+                                       
"java.sql.PreparedStatement.executeQuery()",
+                               },
+                       },
+               },
+               // Summary: "性能分析显示,45.5%的CPU时间消耗在数据库查询调用链上",
+       }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the Java service to analyze"`
+       PodName     string `json:"podName" jsonschema:"required,description=The 
specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+       ToolName            string  `json:"toolName"`
+       FullGcCountLastHour int     `json:"fullGcCountLastHour"`
+       FullGcTimeAvgMillis int     `json:"fullGcTimeAvgMillis"`
+       HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input 
JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+       log.Printf("Tool 'jvm_performance_analysis' called for service: %s, 
pod: %s", input.ServiceName, input.PodName)
+
+       return JVMPerformanceAnalysisOutput{
+               ToolName:            "jvm_performance_analysis",
+               FullGcCountLastHour: 15,
+               FullGcTimeAvgMillis: 1200,
+               HeapUsagePercentage: 85.5,
+               // Summary:             "GC activity is high, average Full GC 
time is 1200ms",
+       }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze 
dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+       ToolName           string   `json:"toolName"`
+       UpstreamServices   []string `json:"upstreamServices"`
+       DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+       return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) 
(TraceDependencyViewOutput, error) {
+       log.Printf("Tool 'trace_dependency_view' called for service: %s", 
input.ServiceName)
+
+       return TraceDependencyViewOutput{
+               ToolName:           "trace_dependency_view",
+               UpstreamServices:   []string{"api-gateway", "user-service"},
+               DownstreamServices: []string{"mysql-orders-db", "redis-cache", 
"payment-service"},
+       }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+       DownstreamService      string  `json:"downstreamService"`
+       LatencyAvgMillis       int     `json:"latencyAvgMillis"`
+       ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+       ToolName              string              `json:"toolName"`
+       TotalLatencyAvgMillis int                 `json:"totalLatencyAvgMillis"`
+       Bottlenecks           []LatencyBottleneck `json:"bottlenecks"`
+       Summary               string              `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input 
TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+       log.Printf("Tool 'trace_latency_analysis' called for service: %s", 
input.ServiceName)
+
+       return TraceLatencyAnalysisOutput{
+               ToolName:              "trace_latency_analysis",
+               TotalLatencyAvgMillis: 3200,
+               Bottlenecks: []LatencyBottleneck{
+                       {
+                               DownstreamService:      "mysql-orders-db",
+                               LatencyAvgMillis:       3050,
+                               ContributionPercentage: 95.3,
+                       },
+                       {
+                               DownstreamService:      "user-service",
+                               LatencyAvgMillis:       150,
+                               ContributionPercentage: 4.7,
+                       },
+               },
+               // Summary: "平均总延迟为 3200ms。瓶颈已定位,95.3% 的延迟来自对下游 
'mysql-orders-db' 的调用",

Review Comment:
   This line is commented out but still contains a string literal. Either 
remove the entire line or uncomment it if the Summary field should be populated.
   ```suggestion
                Summary: "平均总延迟为 3200ms。瓶颈已定位,95.3% 的延迟来自对下游 'mysql-orders-db' 
的调用",
   ```



##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+       "fmt"
+       "log"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+       Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+       ServiceName      string  `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int     `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+       Quantile         float64 `json:"quantile" 
jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+       ToolName    string  `json:"toolName"`
+       Quantile    float64 `json:"quantile"`
+       ValueMillis int     `json:"valueMillis"`
+       Summary     string  `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input 
PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_latency' called for service: 
%s", input.ServiceName)
+
+       // Mock data based on the example in prompt
+       valueMillis := 3500
+       if input.ServiceName != "order-service" {
+               valueMillis = 850
+       }
+
+       return PrometheusServiceLatencyOutput{
+               ToolName:    "prometheus_query_service_latency",
+               Quantile:    input.Quantile,
+               ValueMillis: valueMillis,
+               // Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+       }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+       ToolName            string  `json:"toolName"`
+       RequestRateQPS      float64 `json:"requestRateQPS"`
+       ErrorRatePercentage float64 `json:"errorRatePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input 
PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_traffic' called for service: 
%s", input.ServiceName)
+
+       return PrometheusServiceTrafficOutput{
+               ToolName:            "prometheus_query_service_traffic",
+               RequestRateQPS:      250.0,
+               ErrorRatePercentage: 5.2,
+               // Summary:             fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 
5.2%%", input.ServiceName),
+       }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+       PromqlQuery string `json:"promqlQuery" 
jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+       Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+       Timestamp int64  `json:"timestamp"`
+       Value     string `json:"value"`
+}
+
+type TimeseriesResult struct {
+       Metric TimeseriesMetric `json:"metric"`
+       Value  TimeseriesValue  `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+       ToolName string             `json:"toolName"`
+       Query    string             `json:"query"`
+       Results  []TimeseriesResult `json:"results"`
+       Summary  string             `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+       return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input 
QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+       log.Printf("Tool 'query_timeseries_database' called with query: %s", 
input.PromqlQuery)
+
+       return QueryTimeseriesDatabaseOutput{
+               ToolName: "query_timeseries_database",
+               Query:    input.PromqlQuery,
+               Results: []TimeseriesResult{
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-1"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.5"},
+                       },
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-2"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.2"},
+                       },
+               },
+               // Summary: "查询返回了 2 个时间序列",
+       }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+       ServiceName     string `json:"serviceName" 
jsonschema:"required,description=The name of the service to profile"`
+       PodName         string `json:"podName" 
jsonschema:"required,description=The specific pod name to profile"`
+       DurationSeconds int    `json:"durationSeconds" 
jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+       CPUTimePercentage float64  `json:"cpuTimePercentage"`
+       StackTrace        []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+       ToolName     string               `json:"toolName"`
+       Status       string               `json:"status"`
+       TotalSamples int                  `json:"totalSamples"`
+       Hotspots     []PerformanceHotspot `json:"hotspots"`
+       Summary      string               `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+       return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input 
ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, 
error) {
+       log.Printf("Tool 'application_performance_profiling' called for 
service: %s, pod: %s", input.ServiceName, input.PodName)
+
+       return ApplicationPerformanceProfilingOutput{
+               ToolName:     "application_performance_profiling",
+               Status:       "completed",
+               TotalSamples: 10000,
+               Hotspots: []PerformanceHotspot{
+                       {
+                               CPUTimePercentage: 45.5,
+                               StackTrace: []string{
+                                       
"com.example.OrderService.processOrder()",
+                                       "com.example.DatabaseClient.query()",
+                                       
"java.sql.PreparedStatement.executeQuery()",
+                               },
+                       },
+               },
+               // Summary: "性能分析显示,45.5%的CPU时间消耗在数据库查询调用链上",
+       }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the Java service to analyze"`
+       PodName     string `json:"podName" jsonschema:"required,description=The 
specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+       ToolName            string  `json:"toolName"`
+       FullGcCountLastHour int     `json:"fullGcCountLastHour"`
+       FullGcTimeAvgMillis int     `json:"fullGcTimeAvgMillis"`
+       HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input 
JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+       log.Printf("Tool 'jvm_performance_analysis' called for service: %s, 
pod: %s", input.ServiceName, input.PodName)
+
+       return JVMPerformanceAnalysisOutput{
+               ToolName:            "jvm_performance_analysis",
+               FullGcCountLastHour: 15,
+               FullGcTimeAvgMillis: 1200,
+               HeapUsagePercentage: 85.5,
+               // Summary:             "GC activity is high, average Full GC 
time is 1200ms",

Review Comment:
   This line is commented out but still contains a string literal. Either 
remove the entire line or uncomment it if the Summary field should be populated.
   ```suggestion
   
   ```



##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+       "fmt"
+       "log"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+       Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+       ServiceName      string  `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int     `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+       Quantile         float64 `json:"quantile" 
jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+       ToolName    string  `json:"toolName"`
+       Quantile    float64 `json:"quantile"`
+       ValueMillis int     `json:"valueMillis"`
+       Summary     string  `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input 
PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_latency' called for service: 
%s", input.ServiceName)
+
+       // Mock data based on the example in prompt
+       valueMillis := 3500
+       if input.ServiceName != "order-service" {
+               valueMillis = 850
+       }
+
+       return PrometheusServiceLatencyOutput{
+               ToolName:    "prometheus_query_service_latency",
+               Quantile:    input.Quantile,
+               ValueMillis: valueMillis,
+               // Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+       }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+       ToolName            string  `json:"toolName"`
+       RequestRateQPS      float64 `json:"requestRateQPS"`
+       ErrorRatePercentage float64 `json:"errorRatePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input 
PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_traffic' called for service: 
%s", input.ServiceName)
+
+       return PrometheusServiceTrafficOutput{
+               ToolName:            "prometheus_query_service_traffic",
+               RequestRateQPS:      250.0,
+               ErrorRatePercentage: 5.2,
+               // Summary:             fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 
5.2%%", input.ServiceName),
+       }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+       PromqlQuery string `json:"promqlQuery" 
jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+       Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+       Timestamp int64  `json:"timestamp"`
+       Value     string `json:"value"`
+}
+
+type TimeseriesResult struct {
+       Metric TimeseriesMetric `json:"metric"`
+       Value  TimeseriesValue  `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+       ToolName string             `json:"toolName"`
+       Query    string             `json:"query"`
+       Results  []TimeseriesResult `json:"results"`
+       Summary  string             `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+       return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input 
QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+       log.Printf("Tool 'query_timeseries_database' called with query: %s", 
input.PromqlQuery)
+
+       return QueryTimeseriesDatabaseOutput{
+               ToolName: "query_timeseries_database",
+               Query:    input.PromqlQuery,
+               Results: []TimeseriesResult{
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-1"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.5"},
+                       },
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-2"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.2"},
+                       },
+               },
+               // Summary: "查询返回了 2 个时间序列",
+       }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+       ServiceName     string `json:"serviceName" 
jsonschema:"required,description=The name of the service to profile"`
+       PodName         string `json:"podName" 
jsonschema:"required,description=The specific pod name to profile"`
+       DurationSeconds int    `json:"durationSeconds" 
jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+       CPUTimePercentage float64  `json:"cpuTimePercentage"`
+       StackTrace        []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+       ToolName     string               `json:"toolName"`
+       Status       string               `json:"status"`
+       TotalSamples int                  `json:"totalSamples"`
+       Hotspots     []PerformanceHotspot `json:"hotspots"`
+       Summary      string               `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+       return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input 
ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, 
error) {
+       log.Printf("Tool 'application_performance_profiling' called for 
service: %s, pod: %s", input.ServiceName, input.PodName)
+
+       return ApplicationPerformanceProfilingOutput{
+               ToolName:     "application_performance_profiling",
+               Status:       "completed",
+               TotalSamples: 10000,
+               Hotspots: []PerformanceHotspot{
+                       {
+                               CPUTimePercentage: 45.5,
+                               StackTrace: []string{
+                                       
"com.example.OrderService.processOrder()",
+                                       "com.example.DatabaseClient.query()",
+                                       
"java.sql.PreparedStatement.executeQuery()",
+                               },
+                       },
+               },
+               // Summary: "性能分析显示,45.5%的CPU时间消耗在数据库查询调用链上",
+       }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the Java service to analyze"`
+       PodName     string `json:"podName" jsonschema:"required,description=The 
specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+       ToolName            string  `json:"toolName"`
+       FullGcCountLastHour int     `json:"fullGcCountLastHour"`
+       FullGcTimeAvgMillis int     `json:"fullGcTimeAvgMillis"`
+       HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input 
JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+       log.Printf("Tool 'jvm_performance_analysis' called for service: %s, 
pod: %s", input.ServiceName, input.PodName)
+
+       return JVMPerformanceAnalysisOutput{
+               ToolName:            "jvm_performance_analysis",
+               FullGcCountLastHour: 15,
+               FullGcTimeAvgMillis: 1200,
+               HeapUsagePercentage: 85.5,
+               // Summary:             "GC activity is high, average Full GC 
time is 1200ms",
+       }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze 
dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+       ToolName           string   `json:"toolName"`
+       UpstreamServices   []string `json:"upstreamServices"`
+       DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+       return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) 
(TraceDependencyViewOutput, error) {
+       log.Printf("Tool 'trace_dependency_view' called for service: %s", 
input.ServiceName)
+
+       return TraceDependencyViewOutput{
+               ToolName:           "trace_dependency_view",
+               UpstreamServices:   []string{"api-gateway", "user-service"},
+               DownstreamServices: []string{"mysql-orders-db", "redis-cache", 
"payment-service"},
+       }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+       DownstreamService      string  `json:"downstreamService"`
+       LatencyAvgMillis       int     `json:"latencyAvgMillis"`
+       ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+       ToolName              string              `json:"toolName"`
+       TotalLatencyAvgMillis int                 `json:"totalLatencyAvgMillis"`
+       Bottlenecks           []LatencyBottleneck `json:"bottlenecks"`
+       Summary               string              `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input 
TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+       log.Printf("Tool 'trace_latency_analysis' called for service: %s", 
input.ServiceName)
+
+       return TraceLatencyAnalysisOutput{
+               ToolName:              "trace_latency_analysis",
+               TotalLatencyAvgMillis: 3200,
+               Bottlenecks: []LatencyBottleneck{
+                       {
+                               DownstreamService:      "mysql-orders-db",
+                               LatencyAvgMillis:       3050,
+                               ContributionPercentage: 95.3,
+                       },
+                       {
+                               DownstreamService:      "user-service",
+                               LatencyAvgMillis:       150,
+                               ContributionPercentage: 4.7,
+                       },
+               },
+               // Summary: "平均总延迟为 3200ms。瓶颈已定位,95.3% 的延迟来自对下游 
'mysql-orders-db' 的调用",
+       }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+       ToolName          string `json:"toolName"`
+       MaxConnections    int    `json:"maxConnections"`
+       ActiveConnections int    `json:"activeConnections"`
+       IdleConnections   int    `json:"idleConnections"`
+       PendingRequests   int    `json:"pendingRequests"`
+       Summary           string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input 
DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, 
error) {
+       log.Printf("Tool 'database_connection_pool_analysis' called for 
service: %s", input.ServiceName)
+
+       return DatabaseConnectionPoolAnalysisOutput{
+               ToolName:          "database_connection_pool_analysis",
+               MaxConnections:    100,
+               ActiveConnections: 100,
+               IdleConnections:   0,
+               PendingRequests:   58,
+               // Summary:           "数据库连接池已完全耗尽 (100/100),当前有 58 
个请求正在排队等待连接",
+       }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service"`
+       Namespace   string `json:"namespace" 
jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+       PodName         string  `json:"podName"`
+       CPUUsageCores   float64 `json:"cpuUsageCores"`
+       CPURequestCores float64 `json:"cpuRequestCores"`
+       CPULimitCores   float64 `json:"cpuLimitCores"`
+       MemoryUsageMi   int     `json:"memoryUsageMi"`
+       MemoryRequestMi int     `json:"memoryRequestMi"`
+       MemoryLimitMi   int     `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+       ToolName string        `json:"toolName"`
+       Pods     []PodResource `json:"pods"`
+       Summary  string        `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+       return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input 
KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+       log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s 
in namespace: %s", input.ServiceName, input.Namespace)
+
+       return KubernetesGetPodResourcesOutput{
+               ToolName: "kubernetes_get_pod_resources",
+               Pods: []PodResource{
+                       {
+                               PodName:         "order-service-pod-1",
+                               CPUUsageCores:   0.8,
+                               CPURequestCores: 0.5,
+                               CPULimitCores:   1.0,
+                               MemoryUsageMi:   1800,
+                               MemoryRequestMi: 1024,
+                               MemoryLimitMi:   2048,
+                       },
+                       {
+                               PodName:         "order-service-pod-2",
+                               CPUUsageCores:   0.9,
+                               CPURequestCores: 0.5,
+                               CPULimitCores:   1.0,
+                               MemoryUsageMi:   1950,
+                               MemoryRequestMi: 1024,
+                               MemoryLimitMi:   2048,
+                       },
+               },
+               // Summary: "2 out of 2 pods are near their memory limits",
+       }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+       IP     string `json:"ip"`
+       Port   int    `json:"port"`
+       Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+       IP          string `json:"ip"`
+       Application string `json:"application"`
+       Status      string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+       ToolName  string          `json:"toolName"`
+       Providers []DubboProvider `json:"providers"`
+       Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+       return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) 
(DubboServiceStatusOutput, error) {
+       log.Printf("Tool 'dubbo_service_status' called for service: %s", 
input.ServiceName)
+
+       return DubboServiceStatusOutput{
+               ToolName: "dubbo_service_status",
+               Providers: []DubboProvider{
+                       {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+                       {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+               },
+               Consumers: []DubboConsumer{
+                       {IP: "192.168.1.20", Application: "web-frontend", 
Status: "connected"},
+                       {IP: "192.168.1.21", Application: "api-gateway", 
Status: "connected"},
+               },
+       }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service"`
+       Keyword          string `json:"keyword" 
jsonschema:"required,description=Keyword to search for"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+       Timestamp string `json:"timestamp"`
+       Level     string `json:"level"`
+       Message   string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+       ToolName  string     `json:"toolName"`
+       TotalHits int        `json:"totalHits"`
+       Logs      []LogEntry `json:"logs"`
+       Summary   string     `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+       return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) 
(QueryLogDatabaseOutput, error) {
+       log.Printf("Tool 'query_log_database' called for service: %s, keyword: 
%s", input.ServiceName, input.Keyword)
+
+       return QueryLogDatabaseOutput{
+               ToolName:  "query_log_database",
+               TotalHits: 152,
+               Logs: []LogEntry{
+                       {
+                               Timestamp: "2025-08-16T15:32:05Z",
+                               Level:     "WARN",
+                               Message:   "Timeout waiting for idle object in 
database connection pool.",
+                       },
+                       {
+                               Timestamp: "2025-08-16T15:32:08Z",
+                               Level:     "WARN",
+                               Message:   "Timeout waiting for idle object in 
database connection pool.",
+                       },
+               },
+               // Summary: fmt.Sprintf("在过去%d分钟内,发现 152 条关于 '%s' 的日志条目", 
input.TimeRangeMinutes, input.Keyword),

Review Comment:
   This line is commented out but still contains the fmt.Sprintf call. Either 
remove the entire line or uncomment it if the Summary field should be populated.
   ```suggestion
                Summary: fmt.Sprintf("在过去%d分钟内,发现 152 条关于 '%s' 的日志条目", 
input.TimeRangeMinutes, input.Keyword),
   ```



##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+       "fmt"
+       "log"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+       Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+       ServiceName      string  `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int     `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+       Quantile         float64 `json:"quantile" 
jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+       ToolName    string  `json:"toolName"`
+       Quantile    float64 `json:"quantile"`
+       ValueMillis int     `json:"valueMillis"`
+       Summary     string  `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input 
PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_latency' called for service: 
%s", input.ServiceName)
+
+       // Mock data based on the example in prompt
+       valueMillis := 3500
+       if input.ServiceName != "order-service" {
+               valueMillis = 850
+       }
+
+       return PrometheusServiceLatencyOutput{
+               ToolName:    "prometheus_query_service_latency",
+               Quantile:    input.Quantile,
+               ValueMillis: valueMillis,
+               // Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+       }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+       ToolName            string  `json:"toolName"`
+       RequestRateQPS      float64 `json:"requestRateQPS"`
+       ErrorRatePercentage float64 `json:"errorRatePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input 
PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_traffic' called for service: 
%s", input.ServiceName)
+
+       return PrometheusServiceTrafficOutput{
+               ToolName:            "prometheus_query_service_traffic",
+               RequestRateQPS:      250.0,
+               ErrorRatePercentage: 5.2,
+               // Summary:             fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 
5.2%%", input.ServiceName),
+       }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+       PromqlQuery string `json:"promqlQuery" 
jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+       Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+       Timestamp int64  `json:"timestamp"`
+       Value     string `json:"value"`
+}
+
+type TimeseriesResult struct {
+       Metric TimeseriesMetric `json:"metric"`
+       Value  TimeseriesValue  `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+       ToolName string             `json:"toolName"`
+       Query    string             `json:"query"`
+       Results  []TimeseriesResult `json:"results"`
+       Summary  string             `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+       return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input 
QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+       log.Printf("Tool 'query_timeseries_database' called with query: %s", 
input.PromqlQuery)
+
+       return QueryTimeseriesDatabaseOutput{
+               ToolName: "query_timeseries_database",
+               Query:    input.PromqlQuery,
+               Results: []TimeseriesResult{
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-1"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.5"},
+                       },
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-2"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.2"},
+                       },
+               },
+               // Summary: "查询返回了 2 个时间序列",
+       }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+       ServiceName     string `json:"serviceName" 
jsonschema:"required,description=The name of the service to profile"`
+       PodName         string `json:"podName" 
jsonschema:"required,description=The specific pod name to profile"`
+       DurationSeconds int    `json:"durationSeconds" 
jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+       CPUTimePercentage float64  `json:"cpuTimePercentage"`
+       StackTrace        []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+       ToolName     string               `json:"toolName"`
+       Status       string               `json:"status"`
+       TotalSamples int                  `json:"totalSamples"`
+       Hotspots     []PerformanceHotspot `json:"hotspots"`
+       Summary      string               `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+       return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input 
ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, 
error) {
+       log.Printf("Tool 'application_performance_profiling' called for 
service: %s, pod: %s", input.ServiceName, input.PodName)
+
+       return ApplicationPerformanceProfilingOutput{
+               ToolName:     "application_performance_profiling",
+               Status:       "completed",
+               TotalSamples: 10000,
+               Hotspots: []PerformanceHotspot{
+                       {
+                               CPUTimePercentage: 45.5,
+                               StackTrace: []string{
+                                       
"com.example.OrderService.processOrder()",
+                                       "com.example.DatabaseClient.query()",
+                                       
"java.sql.PreparedStatement.executeQuery()",
+                               },
+                       },
+               },
+               // Summary: "性能分析显示,45.5%的CPU时间消耗在数据库查询调用链上",
+       }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the Java service to analyze"`
+       PodName     string `json:"podName" jsonschema:"required,description=The 
specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+       ToolName            string  `json:"toolName"`
+       FullGcCountLastHour int     `json:"fullGcCountLastHour"`
+       FullGcTimeAvgMillis int     `json:"fullGcTimeAvgMillis"`
+       HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input 
JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+       log.Printf("Tool 'jvm_performance_analysis' called for service: %s, 
pod: %s", input.ServiceName, input.PodName)
+
+       return JVMPerformanceAnalysisOutput{
+               ToolName:            "jvm_performance_analysis",
+               FullGcCountLastHour: 15,
+               FullGcTimeAvgMillis: 1200,
+               HeapUsagePercentage: 85.5,
+               // Summary:             "GC activity is high, average Full GC 
time is 1200ms",
+       }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze 
dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+       ToolName           string   `json:"toolName"`
+       UpstreamServices   []string `json:"upstreamServices"`
+       DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+       return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) 
(TraceDependencyViewOutput, error) {
+       log.Printf("Tool 'trace_dependency_view' called for service: %s", 
input.ServiceName)
+
+       return TraceDependencyViewOutput{
+               ToolName:           "trace_dependency_view",
+               UpstreamServices:   []string{"api-gateway", "user-service"},
+               DownstreamServices: []string{"mysql-orders-db", "redis-cache", 
"payment-service"},
+       }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+       DownstreamService      string  `json:"downstreamService"`
+       LatencyAvgMillis       int     `json:"latencyAvgMillis"`
+       ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+       ToolName              string              `json:"toolName"`
+       TotalLatencyAvgMillis int                 `json:"totalLatencyAvgMillis"`
+       Bottlenecks           []LatencyBottleneck `json:"bottlenecks"`
+       Summary               string              `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input 
TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+       log.Printf("Tool 'trace_latency_analysis' called for service: %s", 
input.ServiceName)
+
+       return TraceLatencyAnalysisOutput{
+               ToolName:              "trace_latency_analysis",
+               TotalLatencyAvgMillis: 3200,
+               Bottlenecks: []LatencyBottleneck{
+                       {
+                               DownstreamService:      "mysql-orders-db",
+                               LatencyAvgMillis:       3050,
+                               ContributionPercentage: 95.3,
+                       },
+                       {
+                               DownstreamService:      "user-service",
+                               LatencyAvgMillis:       150,
+                               ContributionPercentage: 4.7,
+                       },
+               },
+               // Summary: "平均总延迟为 3200ms。瓶颈已定位,95.3% 的延迟来自对下游 
'mysql-orders-db' 的调用",
+       }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+       ToolName          string `json:"toolName"`
+       MaxConnections    int    `json:"maxConnections"`
+       ActiveConnections int    `json:"activeConnections"`
+       IdleConnections   int    `json:"idleConnections"`
+       PendingRequests   int    `json:"pendingRequests"`
+       Summary           string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input 
DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, 
error) {
+       log.Printf("Tool 'database_connection_pool_analysis' called for 
service: %s", input.ServiceName)
+
+       return DatabaseConnectionPoolAnalysisOutput{
+               ToolName:          "database_connection_pool_analysis",
+               MaxConnections:    100,
+               ActiveConnections: 100,
+               IdleConnections:   0,
+               PendingRequests:   58,
+               // Summary:           "数据库连接池已完全耗尽 (100/100),当前有 58 
个请求正在排队等待连接",
+       }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service"`
+       Namespace   string `json:"namespace" 
jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+       PodName         string  `json:"podName"`
+       CPUUsageCores   float64 `json:"cpuUsageCores"`
+       CPURequestCores float64 `json:"cpuRequestCores"`
+       CPULimitCores   float64 `json:"cpuLimitCores"`
+       MemoryUsageMi   int     `json:"memoryUsageMi"`
+       MemoryRequestMi int     `json:"memoryRequestMi"`
+       MemoryLimitMi   int     `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+       ToolName string        `json:"toolName"`
+       Pods     []PodResource `json:"pods"`
+       Summary  string        `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+       return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input 
KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+       log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s 
in namespace: %s", input.ServiceName, input.Namespace)
+
+       return KubernetesGetPodResourcesOutput{
+               ToolName: "kubernetes_get_pod_resources",
+               Pods: []PodResource{
+                       {
+                               PodName:         "order-service-pod-1",
+                               CPUUsageCores:   0.8,
+                               CPURequestCores: 0.5,
+                               CPULimitCores:   1.0,
+                               MemoryUsageMi:   1800,
+                               MemoryRequestMi: 1024,
+                               MemoryLimitMi:   2048,
+                       },
+                       {
+                               PodName:         "order-service-pod-2",
+                               CPUUsageCores:   0.9,
+                               CPURequestCores: 0.5,
+                               CPULimitCores:   1.0,
+                               MemoryUsageMi:   1950,
+                               MemoryRequestMi: 1024,
+                               MemoryLimitMi:   2048,
+                       },
+               },
+               // Summary: "2 out of 2 pods are near their memory limits",

Review Comment:
   This line is commented out but still contains a string literal. Either 
remove the entire line or uncomment it if the Summary field should be populated.
   ```suggestion
   
   ```



##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+       "fmt"
+       "log"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+       Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+       ServiceName      string  `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int     `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+       Quantile         float64 `json:"quantile" 
jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+       ToolName    string  `json:"toolName"`
+       Quantile    float64 `json:"quantile"`
+       ValueMillis int     `json:"valueMillis"`
+       Summary     string  `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input 
PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_latency' called for service: 
%s", input.ServiceName)
+
+       // Mock data based on the example in prompt
+       valueMillis := 3500
+       if input.ServiceName != "order-service" {
+               valueMillis = 850
+       }
+
+       return PrometheusServiceLatencyOutput{
+               ToolName:    "prometheus_query_service_latency",
+               Quantile:    input.Quantile,
+               ValueMillis: valueMillis,
+               // Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),

Review Comment:
   This line is commented out but still contains the fmt.Sprintf call. Either 
remove the entire line or uncomment it if the Summary field should be populated.
   ```suggestion
                Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
   ```



##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+       "fmt"
+       "log"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+       Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+       ServiceName      string  `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int     `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+       Quantile         float64 `json:"quantile" 
jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+       ToolName    string  `json:"toolName"`
+       Quantile    float64 `json:"quantile"`
+       ValueMillis int     `json:"valueMillis"`
+       Summary     string  `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input 
PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_latency' called for service: 
%s", input.ServiceName)
+
+       // Mock data based on the example in prompt
+       valueMillis := 3500
+       if input.ServiceName != "order-service" {
+               valueMillis = 850
+       }
+
+       return PrometheusServiceLatencyOutput{
+               ToolName:    "prometheus_query_service_latency",
+               Quantile:    input.Quantile,
+               ValueMillis: valueMillis,
+               // Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+       }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+       ToolName            string  `json:"toolName"`
+       RequestRateQPS      float64 `json:"requestRateQPS"`
+       ErrorRatePercentage float64 `json:"errorRatePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input 
PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_traffic' called for service: 
%s", input.ServiceName)
+
+       return PrometheusServiceTrafficOutput{
+               ToolName:            "prometheus_query_service_traffic",
+               RequestRateQPS:      250.0,
+               ErrorRatePercentage: 5.2,
+               // Summary:             fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 
5.2%%", input.ServiceName),
+       }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+       PromqlQuery string `json:"promqlQuery" 
jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+       Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+       Timestamp int64  `json:"timestamp"`
+       Value     string `json:"value"`
+}
+
+type TimeseriesResult struct {
+       Metric TimeseriesMetric `json:"metric"`
+       Value  TimeseriesValue  `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+       ToolName string             `json:"toolName"`
+       Query    string             `json:"query"`
+       Results  []TimeseriesResult `json:"results"`
+       Summary  string             `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+       return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input 
QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+       log.Printf("Tool 'query_timeseries_database' called with query: %s", 
input.PromqlQuery)
+
+       return QueryTimeseriesDatabaseOutput{
+               ToolName: "query_timeseries_database",
+               Query:    input.PromqlQuery,
+               Results: []TimeseriesResult{
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-1"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.5"},
+                       },
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-2"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.2"},
+                       },
+               },
+               // Summary: "查询返回了 2 个时间序列",

Review Comment:
   This line is commented out but still contains a string literal. Either 
remove the entire line or uncomment it if the Summary field should be populated.
   ```suggestion
                Summary: "查询返回了 2 个时间序列",
   ```



##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+       "fmt"
+       "log"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+       Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+       ServiceName      string  `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int     `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+       Quantile         float64 `json:"quantile" 
jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+       ToolName    string  `json:"toolName"`
+       Quantile    float64 `json:"quantile"`
+       ValueMillis int     `json:"valueMillis"`
+       Summary     string  `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input 
PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_latency' called for service: 
%s", input.ServiceName)
+
+       // Mock data based on the example in prompt
+       valueMillis := 3500
+       if input.ServiceName != "order-service" {
+               valueMillis = 850
+       }
+
+       return PrometheusServiceLatencyOutput{
+               ToolName:    "prometheus_query_service_latency",
+               Quantile:    input.Quantile,
+               ValueMillis: valueMillis,
+               // Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+       }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+       ToolName            string  `json:"toolName"`
+       RequestRateQPS      float64 `json:"requestRateQPS"`
+       ErrorRatePercentage float64 `json:"errorRatePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input 
PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_traffic' called for service: 
%s", input.ServiceName)
+
+       return PrometheusServiceTrafficOutput{
+               ToolName:            "prometheus_query_service_traffic",
+               RequestRateQPS:      250.0,
+               ErrorRatePercentage: 5.2,
+               // Summary:             fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 
5.2%%", input.ServiceName),
+       }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+       PromqlQuery string `json:"promqlQuery" 
jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+       Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+       Timestamp int64  `json:"timestamp"`
+       Value     string `json:"value"`
+}
+
+type TimeseriesResult struct {
+       Metric TimeseriesMetric `json:"metric"`
+       Value  TimeseriesValue  `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+       ToolName string             `json:"toolName"`
+       Query    string             `json:"query"`
+       Results  []TimeseriesResult `json:"results"`
+       Summary  string             `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+       return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input 
QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+       log.Printf("Tool 'query_timeseries_database' called with query: %s", 
input.PromqlQuery)
+
+       return QueryTimeseriesDatabaseOutput{
+               ToolName: "query_timeseries_database",
+               Query:    input.PromqlQuery,
+               Results: []TimeseriesResult{
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-1"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.5"},
+                       },
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-2"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.2"},
+                       },
+               },
+               // Summary: "查询返回了 2 个时间序列",
+       }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+       ServiceName     string `json:"serviceName" 
jsonschema:"required,description=The name of the service to profile"`
+       PodName         string `json:"podName" 
jsonschema:"required,description=The specific pod name to profile"`
+       DurationSeconds int    `json:"durationSeconds" 
jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+       CPUTimePercentage float64  `json:"cpuTimePercentage"`
+       StackTrace        []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+       ToolName     string               `json:"toolName"`
+       Status       string               `json:"status"`
+       TotalSamples int                  `json:"totalSamples"`
+       Hotspots     []PerformanceHotspot `json:"hotspots"`
+       Summary      string               `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+       return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input 
ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, 
error) {
+       log.Printf("Tool 'application_performance_profiling' called for 
service: %s, pod: %s", input.ServiceName, input.PodName)
+
+       return ApplicationPerformanceProfilingOutput{
+               ToolName:     "application_performance_profiling",
+               Status:       "completed",
+               TotalSamples: 10000,
+               Hotspots: []PerformanceHotspot{
+                       {
+                               CPUTimePercentage: 45.5,
+                               StackTrace: []string{
+                                       
"com.example.OrderService.processOrder()",
+                                       "com.example.DatabaseClient.query()",
+                                       
"java.sql.PreparedStatement.executeQuery()",
+                               },
+                       },
+               },
+               // Summary: "性能分析显示,45.5%的CPU时间消耗在数据库查询调用链上",

Review Comment:
   This line is commented out but still contains a string literal. Either 
remove the entire line or uncomment it if the Summary field should be populated.
   ```suggestion
                Summary: "性能分析显示,45.5%的CPU时间消耗在数据库查询调用链上",
   ```



##########
ai/internal/agent/flow.go:
##########
@@ -0,0 +1,157 @@
+package agent
+
+import (
+       "context"
+       "dubbo-admin-ai/config"
+       "dubbo-admin-ai/internal/schema"
+       "dubbo-admin-ai/internal/tools"
+       "errors"
+       "fmt"
+       "log"
+       "os"
+
+       "github.com/firebase/genkit/go/core/logger"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/core"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// 公开的 Flow 变量,以便在编排器中调用
+var (
+       ReActFlow    *core.Flow[schema.ReActIn, schema.ReActOut, struct{}]
+       ThinkingFlow *core.Flow[schema.ThinkIn, *schema.ThinkOut, struct{}]
+       ActFlow      *core.Flow[*schema.ActIn, schema.ActOut, struct{}]
+
+       ThinkPrompt *ai.Prompt
+)
+
+var g *genkit.Genkit
+
+func InitFlows(registry *genkit.Genkit) error {
+       if registry == nil {
+               return fmt.Errorf("registry is nil")
+       }
+       g = registry
+
+       data, err := os.ReadFile(config.PROMPT_DIR_PATH + "/agentSystem.prompt")
+       if err != nil {
+               return fmt.Errorf("failed to read agentSystem prompt: %w", err)
+       }
+       systemPromptText := string(data)
+
+       mockTools, err := tools.AllMockToolRef()
+       if err != nil {
+               log.Fatalf("failed to get mock mock_tools: %v", err)
+       }
+       ThinkPrompt, err = genkit.DefinePrompt(g, "agentThinking",
+               ai.WithSystem(systemPromptText),
+               ai.WithInputType(schema.ThinkIn{}),
+               ai.WithOutputType(schema.ThinkOut{}),
+               ai.WithPrompt("{{userInput}}"),
+               ai.WithTools(mockTools...),
+               ai.WithToolChoice(ai.ToolChoiceNone),
+       )
+
+       if err != nil {
+               return fmt.Errorf("failed to define agentThink prompt: %w", err)
+       }
+
+       ReActFlow = genkit.DefineFlow(g, "reAct", reAct)
+       ThinkingFlow = genkit.DefineFlow(g, "thinking", thinking)
+       ActFlow = genkit.DefineFlow(g, "act", act)
+
+       return nil
+}
+
+// Flow 的核心函数实现 `fn` (不对外导出)
+// ----------------------------------------------------------------------------
+// 1. agentOrchestrator: 总指挥/编排器的核心逻辑
+// ----------------------------------------------------------------------------
+func reAct(ctx context.Context, reActInput schema.ReActIn) (reActOut 
schema.ReActOut, err error) {
+       //TODO: 输入数据意图解析
+
+       thinkingInput := reActInput
+       // 主协调循环 (Reconciliation Loop)
+       for range 5 { // 设置最大循环次数

Review Comment:
   The magic number 5 should be defined as a named constant to improve code 
readability and maintainability. Consider defining something like `const 
maxReActIterations = 5`.



##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+       "fmt"
+       "log"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+       Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+       ServiceName      string  `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int     `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+       Quantile         float64 `json:"quantile" 
jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+       ToolName    string  `json:"toolName"`
+       Quantile    float64 `json:"quantile"`
+       ValueMillis int     `json:"valueMillis"`
+       Summary     string  `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input 
PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_latency' called for service: 
%s", input.ServiceName)
+
+       // Mock data based on the example in prompt
+       valueMillis := 3500
+       if input.ServiceName != "order-service" {
+               valueMillis = 850
+       }
+
+       return PrometheusServiceLatencyOutput{
+               ToolName:    "prometheus_query_service_latency",
+               Quantile:    input.Quantile,
+               ValueMillis: valueMillis,
+               // Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+       }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+       ToolName            string  `json:"toolName"`
+       RequestRateQPS      float64 `json:"requestRateQPS"`
+       ErrorRatePercentage float64 `json:"errorRatePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input 
PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_traffic' called for service: 
%s", input.ServiceName)
+
+       return PrometheusServiceTrafficOutput{
+               ToolName:            "prometheus_query_service_traffic",
+               RequestRateQPS:      250.0,
+               ErrorRatePercentage: 5.2,
+               // Summary:             fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 
5.2%%", input.ServiceName),
+       }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+       PromqlQuery string `json:"promqlQuery" 
jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+       Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+       Timestamp int64  `json:"timestamp"`
+       Value     string `json:"value"`
+}
+
+type TimeseriesResult struct {
+       Metric TimeseriesMetric `json:"metric"`
+       Value  TimeseriesValue  `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+       ToolName string             `json:"toolName"`
+       Query    string             `json:"query"`
+       Results  []TimeseriesResult `json:"results"`
+       Summary  string             `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+       return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input 
QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+       log.Printf("Tool 'query_timeseries_database' called with query: %s", 
input.PromqlQuery)
+
+       return QueryTimeseriesDatabaseOutput{
+               ToolName: "query_timeseries_database",
+               Query:    input.PromqlQuery,
+               Results: []TimeseriesResult{
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-1"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.5"},
+                       },
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-2"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.2"},
+                       },
+               },
+               // Summary: "查询返回了 2 个时间序列",
+       }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+       ServiceName     string `json:"serviceName" 
jsonschema:"required,description=The name of the service to profile"`
+       PodName         string `json:"podName" 
jsonschema:"required,description=The specific pod name to profile"`
+       DurationSeconds int    `json:"durationSeconds" 
jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+       CPUTimePercentage float64  `json:"cpuTimePercentage"`
+       StackTrace        []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+       ToolName     string               `json:"toolName"`
+       Status       string               `json:"status"`
+       TotalSamples int                  `json:"totalSamples"`
+       Hotspots     []PerformanceHotspot `json:"hotspots"`
+       Summary      string               `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+       return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input 
ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, 
error) {
+       log.Printf("Tool 'application_performance_profiling' called for 
service: %s, pod: %s", input.ServiceName, input.PodName)
+
+       return ApplicationPerformanceProfilingOutput{
+               ToolName:     "application_performance_profiling",
+               Status:       "completed",
+               TotalSamples: 10000,
+               Hotspots: []PerformanceHotspot{
+                       {
+                               CPUTimePercentage: 45.5,
+                               StackTrace: []string{
+                                       
"com.example.OrderService.processOrder()",
+                                       "com.example.DatabaseClient.query()",
+                                       
"java.sql.PreparedStatement.executeQuery()",
+                               },
+                       },
+               },
+               // Summary: "性能分析显示,45.5%的CPU时间消耗在数据库查询调用链上",
+       }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the Java service to analyze"`
+       PodName     string `json:"podName" jsonschema:"required,description=The 
specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+       ToolName            string  `json:"toolName"`
+       FullGcCountLastHour int     `json:"fullGcCountLastHour"`
+       FullGcTimeAvgMillis int     `json:"fullGcTimeAvgMillis"`
+       HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input 
JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+       log.Printf("Tool 'jvm_performance_analysis' called for service: %s, 
pod: %s", input.ServiceName, input.PodName)
+
+       return JVMPerformanceAnalysisOutput{
+               ToolName:            "jvm_performance_analysis",
+               FullGcCountLastHour: 15,
+               FullGcTimeAvgMillis: 1200,
+               HeapUsagePercentage: 85.5,
+               // Summary:             "GC activity is high, average Full GC 
time is 1200ms",
+       }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze 
dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+       ToolName           string   `json:"toolName"`
+       UpstreamServices   []string `json:"upstreamServices"`
+       DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+       return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) 
(TraceDependencyViewOutput, error) {
+       log.Printf("Tool 'trace_dependency_view' called for service: %s", 
input.ServiceName)
+
+       return TraceDependencyViewOutput{
+               ToolName:           "trace_dependency_view",
+               UpstreamServices:   []string{"api-gateway", "user-service"},
+               DownstreamServices: []string{"mysql-orders-db", "redis-cache", 
"payment-service"},
+       }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+       DownstreamService      string  `json:"downstreamService"`
+       LatencyAvgMillis       int     `json:"latencyAvgMillis"`
+       ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+       ToolName              string              `json:"toolName"`
+       TotalLatencyAvgMillis int                 `json:"totalLatencyAvgMillis"`
+       Bottlenecks           []LatencyBottleneck `json:"bottlenecks"`
+       Summary               string              `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input 
TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+       log.Printf("Tool 'trace_latency_analysis' called for service: %s", 
input.ServiceName)
+
+       return TraceLatencyAnalysisOutput{
+               ToolName:              "trace_latency_analysis",
+               TotalLatencyAvgMillis: 3200,
+               Bottlenecks: []LatencyBottleneck{
+                       {
+                               DownstreamService:      "mysql-orders-db",
+                               LatencyAvgMillis:       3050,
+                               ContributionPercentage: 95.3,
+                       },
+                       {
+                               DownstreamService:      "user-service",
+                               LatencyAvgMillis:       150,
+                               ContributionPercentage: 4.7,
+                       },
+               },
+               // Summary: "平均总延迟为 3200ms。瓶颈已定位,95.3% 的延迟来自对下游 
'mysql-orders-db' 的调用",
+       }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+       ToolName          string `json:"toolName"`
+       MaxConnections    int    `json:"maxConnections"`
+       ActiveConnections int    `json:"activeConnections"`
+       IdleConnections   int    `json:"idleConnections"`
+       PendingRequests   int    `json:"pendingRequests"`
+       Summary           string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input 
DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, 
error) {
+       log.Printf("Tool 'database_connection_pool_analysis' called for 
service: %s", input.ServiceName)
+
+       return DatabaseConnectionPoolAnalysisOutput{
+               ToolName:          "database_connection_pool_analysis",
+               MaxConnections:    100,
+               ActiveConnections: 100,
+               IdleConnections:   0,
+               PendingRequests:   58,
+               // Summary:           "数据库连接池已完全耗尽 (100/100),当前有 58 
个请求正在排队等待连接",

Review Comment:
   This line is commented out but still contains a string literal. Either 
remove the entire line or uncomment it if the Summary field should be populated.
   ```suggestion
   
   ```



##########
ai/internal/tools/mock_tools.go:
##########
@@ -0,0 +1,623 @@
+package tools
+
+import (
+       "fmt"
+       "log"
+
+       "github.com/firebase/genkit/go/ai"
+       "github.com/firebase/genkit/go/genkit"
+)
+
+// ================================================
+// Prometheus Query Service Latency Tool
+// ================================================
+type ToolOutput interface {
+       Tool() string
+}
+
+type PrometheusServiceLatencyInput struct {
+       ServiceName      string  `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int     `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+       Quantile         float64 `json:"quantile" 
jsonschema:"required,description=Quantile to query (e.g., 0.99 or 0.95)"`
+}
+
+type PrometheusServiceLatencyOutput struct {
+       ToolName    string  `json:"toolName"`
+       Quantile    float64 `json:"quantile"`
+       ValueMillis int     `json:"valueMillis"`
+       Summary     string  `json:"summary"`
+}
+
+func (o PrometheusServiceLatencyOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceLatency(ctx *ai.ToolContext, input 
PrometheusServiceLatencyInput) (PrometheusServiceLatencyOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_latency' called for service: 
%s", input.ServiceName)
+
+       // Mock data based on the example in prompt
+       valueMillis := 3500
+       if input.ServiceName != "order-service" {
+               valueMillis = 850
+       }
+
+       return PrometheusServiceLatencyOutput{
+               ToolName:    "prometheus_query_service_latency",
+               Quantile:    input.Quantile,
+               ValueMillis: valueMillis,
+               // Summary:     fmt.Sprintf("服务 %s 在过去%d分钟内的 P%.0f 延迟为 %dms", 
input.ServiceName, input.TimeRangeMinutes, input.Quantile*100, valueMillis),
+       }, nil
+}
+
+// ================================================
+// Prometheus Query Service Traffic Tool
+// ================================================
+
+type PrometheusServiceTrafficInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to query"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type PrometheusServiceTrafficOutput struct {
+       ToolName            string  `json:"toolName"`
+       RequestRateQPS      float64 `json:"requestRateQPS"`
+       ErrorRatePercentage float64 `json:"errorRatePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o PrometheusServiceTrafficOutput) Tool() string {
+       return o.ToolName
+}
+
+func prometheusQueryServiceTraffic(ctx *ai.ToolContext, input 
PrometheusServiceTrafficInput) (PrometheusServiceTrafficOutput, error) {
+       log.Printf("Tool 'prometheus_query_service_traffic' called for service: 
%s", input.ServiceName)
+
+       return PrometheusServiceTrafficOutput{
+               ToolName:            "prometheus_query_service_traffic",
+               RequestRateQPS:      250.0,
+               ErrorRatePercentage: 5.2,
+               // Summary:             fmt.Sprintf("服务 %s 的 QPS 为 250, 错误率为 
5.2%%", input.ServiceName),
+       }, nil
+}
+
+// ================================================
+// Query Timeseries Database Tool
+// ================================================
+
+type QueryTimeseriesDatabaseInput struct {
+       PromqlQuery string `json:"promqlQuery" 
jsonschema:"required,description=PromQL query to execute"`
+}
+
+type TimeseriesMetric struct {
+       Pod string `json:"pod"`
+}
+
+type TimeseriesValue struct {
+       Timestamp int64  `json:"timestamp"`
+       Value     string `json:"value"`
+}
+
+type TimeseriesResult struct {
+       Metric TimeseriesMetric `json:"metric"`
+       Value  TimeseriesValue  `json:"value"`
+}
+
+type QueryTimeseriesDatabaseOutput struct {
+       ToolName string             `json:"toolName"`
+       Query    string             `json:"query"`
+       Results  []TimeseriesResult `json:"results"`
+       Summary  string             `json:"summary"`
+}
+
+func (o QueryTimeseriesDatabaseOutput) Tool() string {
+       return o.ToolName
+}
+
+func queryTimeseriesDatabase(ctx *ai.ToolContext, input 
QueryTimeseriesDatabaseInput) (QueryTimeseriesDatabaseOutput, error) {
+       log.Printf("Tool 'query_timeseries_database' called with query: %s", 
input.PromqlQuery)
+
+       return QueryTimeseriesDatabaseOutput{
+               ToolName: "query_timeseries_database",
+               Query:    input.PromqlQuery,
+               Results: []TimeseriesResult{
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-1"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.5"},
+                       },
+                       {
+                               Metric: TimeseriesMetric{Pod: 
"order-service-pod-2"},
+                               Value:  TimeseriesValue{Timestamp: 1692192000, 
Value: "3.2"},
+                       },
+               },
+               // Summary: "查询返回了 2 个时间序列",
+       }, nil
+}
+
+// ================================================
+// Application Performance Profiling Tool
+// ================================================
+
+type ApplicationPerformanceProfilingInput struct {
+       ServiceName     string `json:"serviceName" 
jsonschema:"required,description=The name of the service to profile"`
+       PodName         string `json:"podName" 
jsonschema:"required,description=The specific pod name to profile"`
+       DurationSeconds int    `json:"durationSeconds" 
jsonschema:"required,description=Duration of profiling in seconds"`
+}
+
+type PerformanceHotspot struct {
+       CPUTimePercentage float64  `json:"cpuTimePercentage"`
+       StackTrace        []string `json:"stackTrace"`
+}
+
+type ApplicationPerformanceProfilingOutput struct {
+       ToolName     string               `json:"toolName"`
+       Status       string               `json:"status"`
+       TotalSamples int                  `json:"totalSamples"`
+       Hotspots     []PerformanceHotspot `json:"hotspots"`
+       Summary      string               `json:"summary"`
+}
+
+func (o ApplicationPerformanceProfilingOutput) Tool() string {
+       return o.ToolName
+}
+
+func applicationPerformanceProfiling(ctx *ai.ToolContext, input 
ApplicationPerformanceProfilingInput) (ApplicationPerformanceProfilingOutput, 
error) {
+       log.Printf("Tool 'application_performance_profiling' called for 
service: %s, pod: %s", input.ServiceName, input.PodName)
+
+       return ApplicationPerformanceProfilingOutput{
+               ToolName:     "application_performance_profiling",
+               Status:       "completed",
+               TotalSamples: 10000,
+               Hotspots: []PerformanceHotspot{
+                       {
+                               CPUTimePercentage: 45.5,
+                               StackTrace: []string{
+                                       
"com.example.OrderService.processOrder()",
+                                       "com.example.DatabaseClient.query()",
+                                       
"java.sql.PreparedStatement.executeQuery()",
+                               },
+                       },
+               },
+               // Summary: "性能分析显示,45.5%的CPU时间消耗在数据库查询调用链上",
+       }, nil
+}
+
+// ================================================
+// JVM Performance Analysis Tool
+// ================================================
+
+type JVMPerformanceAnalysisInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the Java service to analyze"`
+       PodName     string `json:"podName" jsonschema:"required,description=The 
specific pod name to analyze"`
+}
+
+type JVMPerformanceAnalysisOutput struct {
+       ToolName            string  `json:"toolName"`
+       FullGcCountLastHour int     `json:"fullGcCountLastHour"`
+       FullGcTimeAvgMillis int     `json:"fullGcTimeAvgMillis"`
+       HeapUsagePercentage float64 `json:"heapUsagePercentage"`
+       Summary             string  `json:"summary"`
+}
+
+func (o JVMPerformanceAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func jvmPerformanceAnalysis(ctx *ai.ToolContext, input 
JVMPerformanceAnalysisInput) (JVMPerformanceAnalysisOutput, error) {
+       log.Printf("Tool 'jvm_performance_analysis' called for service: %s, 
pod: %s", input.ServiceName, input.PodName)
+
+       return JVMPerformanceAnalysisOutput{
+               ToolName:            "jvm_performance_analysis",
+               FullGcCountLastHour: 15,
+               FullGcTimeAvgMillis: 1200,
+               HeapUsagePercentage: 85.5,
+               // Summary:             "GC activity is high, average Full GC 
time is 1200ms",
+       }, nil
+}
+
+// ================================================
+// Trace Dependency View Tool
+// ================================================
+
+type TraceDependencyViewInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze 
dependencies"`
+}
+
+type TraceDependencyViewOutput struct {
+       ToolName           string   `json:"toolName"`
+       UpstreamServices   []string `json:"upstreamServices"`
+       DownstreamServices []string `json:"downstreamServices"`
+}
+
+func (o TraceDependencyViewOutput) Tool() string {
+       return o.ToolName
+}
+
+func traceDependencyView(ctx *ai.ToolContext, input TraceDependencyViewInput) 
(TraceDependencyViewOutput, error) {
+       log.Printf("Tool 'trace_dependency_view' called for service: %s", 
input.ServiceName)
+
+       return TraceDependencyViewOutput{
+               ToolName:           "trace_dependency_view",
+               UpstreamServices:   []string{"api-gateway", "user-service"},
+               DownstreamServices: []string{"mysql-orders-db", "redis-cache", 
"payment-service"},
+       }, nil
+}
+
+// ================================================
+// Trace Latency Analysis Tool
+// ================================================
+
+type TraceLatencyAnalysisInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type LatencyBottleneck struct {
+       DownstreamService      string  `json:"downstreamService"`
+       LatencyAvgMillis       int     `json:"latencyAvgMillis"`
+       ContributionPercentage float64 `json:"contributionPercentage"`
+}
+
+type TraceLatencyAnalysisOutput struct {
+       ToolName              string              `json:"toolName"`
+       TotalLatencyAvgMillis int                 `json:"totalLatencyAvgMillis"`
+       Bottlenecks           []LatencyBottleneck `json:"bottlenecks"`
+       Summary               string              `json:"summary"`
+}
+
+func (o TraceLatencyAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func traceLatencyAnalysis(ctx *ai.ToolContext, input 
TraceLatencyAnalysisInput) (TraceLatencyAnalysisOutput, error) {
+       log.Printf("Tool 'trace_latency_analysis' called for service: %s", 
input.ServiceName)
+
+       return TraceLatencyAnalysisOutput{
+               ToolName:              "trace_latency_analysis",
+               TotalLatencyAvgMillis: 3200,
+               Bottlenecks: []LatencyBottleneck{
+                       {
+                               DownstreamService:      "mysql-orders-db",
+                               LatencyAvgMillis:       3050,
+                               ContributionPercentage: 95.3,
+                       },
+                       {
+                               DownstreamService:      "user-service",
+                               LatencyAvgMillis:       150,
+                               ContributionPercentage: 4.7,
+                       },
+               },
+               // Summary: "平均总延迟为 3200ms。瓶颈已定位,95.3% 的延迟来自对下游 
'mysql-orders-db' 的调用",
+       }, nil
+}
+
+// ================================================
+// Database Connection Pool Analysis Tool
+// ================================================
+
+type DatabaseConnectionPoolAnalysisInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service to analyze"`
+}
+
+type DatabaseConnectionPoolAnalysisOutput struct {
+       ToolName          string `json:"toolName"`
+       MaxConnections    int    `json:"maxConnections"`
+       ActiveConnections int    `json:"activeConnections"`
+       IdleConnections   int    `json:"idleConnections"`
+       PendingRequests   int    `json:"pendingRequests"`
+       Summary           string `json:"summary"`
+}
+
+func (o DatabaseConnectionPoolAnalysisOutput) Tool() string {
+       return o.ToolName
+}
+
+func databaseConnectionPoolAnalysis(ctx *ai.ToolContext, input 
DatabaseConnectionPoolAnalysisInput) (DatabaseConnectionPoolAnalysisOutput, 
error) {
+       log.Printf("Tool 'database_connection_pool_analysis' called for 
service: %s", input.ServiceName)
+
+       return DatabaseConnectionPoolAnalysisOutput{
+               ToolName:          "database_connection_pool_analysis",
+               MaxConnections:    100,
+               ActiveConnections: 100,
+               IdleConnections:   0,
+               PendingRequests:   58,
+               // Summary:           "数据库连接池已完全耗尽 (100/100),当前有 58 
个请求正在排队等待连接",
+       }, nil
+}
+
+// ================================================
+// Kubernetes Get Pod Resources Tool
+// ================================================
+
+type KubernetesGetPodResourcesInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the service"`
+       Namespace   string `json:"namespace" 
jsonschema:"required,description=The namespace of the service"`
+}
+
+type PodResource struct {
+       PodName         string  `json:"podName"`
+       CPUUsageCores   float64 `json:"cpuUsageCores"`
+       CPURequestCores float64 `json:"cpuRequestCores"`
+       CPULimitCores   float64 `json:"cpuLimitCores"`
+       MemoryUsageMi   int     `json:"memoryUsageMi"`
+       MemoryRequestMi int     `json:"memoryRequestMi"`
+       MemoryLimitMi   int     `json:"memoryLimitMi"`
+}
+
+type KubernetesGetPodResourcesOutput struct {
+       ToolName string        `json:"toolName"`
+       Pods     []PodResource `json:"pods"`
+       Summary  string        `json:"summary"`
+}
+
+func (o KubernetesGetPodResourcesOutput) Tool() string {
+       return o.ToolName
+}
+
+func kubernetesGetPodResources(ctx *ai.ToolContext, input 
KubernetesGetPodResourcesInput) (KubernetesGetPodResourcesOutput, error) {
+       log.Printf("Tool 'kubernetes_get_pod_resources' called for service: %s 
in namespace: %s", input.ServiceName, input.Namespace)
+
+       return KubernetesGetPodResourcesOutput{
+               ToolName: "kubernetes_get_pod_resources",
+               Pods: []PodResource{
+                       {
+                               PodName:         "order-service-pod-1",
+                               CPUUsageCores:   0.8,
+                               CPURequestCores: 0.5,
+                               CPULimitCores:   1.0,
+                               MemoryUsageMi:   1800,
+                               MemoryRequestMi: 1024,
+                               MemoryLimitMi:   2048,
+                       },
+                       {
+                               PodName:         "order-service-pod-2",
+                               CPUUsageCores:   0.9,
+                               CPURequestCores: 0.5,
+                               CPULimitCores:   1.0,
+                               MemoryUsageMi:   1950,
+                               MemoryRequestMi: 1024,
+                               MemoryLimitMi:   2048,
+                       },
+               },
+               // Summary: "2 out of 2 pods are near their memory limits",
+       }, nil
+}
+
+// ================================================
+// Dubbo Service Status Tool
+// ================================================
+
+type DubboServiceStatusInput struct {
+       ServiceName string `json:"serviceName" 
jsonschema:"required,description=The name of the Dubbo service"`
+}
+
+type DubboProvider struct {
+       IP     string `json:"ip"`
+       Port   int    `json:"port"`
+       Status string `json:"status"`
+}
+
+type DubboConsumer struct {
+       IP          string `json:"ip"`
+       Application string `json:"application"`
+       Status      string `json:"status"`
+}
+
+type DubboServiceStatusOutput struct {
+       ToolName  string          `json:"toolName"`
+       Providers []DubboProvider `json:"providers"`
+       Consumers []DubboConsumer `json:"consumers"`
+}
+
+func (o DubboServiceStatusOutput) Tool() string {
+       return o.ToolName
+}
+
+func dubboServiceStatus(ctx *ai.ToolContext, input DubboServiceStatusInput) 
(DubboServiceStatusOutput, error) {
+       log.Printf("Tool 'dubbo_service_status' called for service: %s", 
input.ServiceName)
+
+       return DubboServiceStatusOutput{
+               ToolName: "dubbo_service_status",
+               Providers: []DubboProvider{
+                       {IP: "192.168.1.10", Port: 20880, Status: "healthy"},
+                       {IP: "192.168.1.11", Port: 20880, Status: "healthy"},
+               },
+               Consumers: []DubboConsumer{
+                       {IP: "192.168.1.20", Application: "web-frontend", 
Status: "connected"},
+                       {IP: "192.168.1.21", Application: "api-gateway", 
Status: "connected"},
+               },
+       }, nil
+}
+
+// ================================================
+// Query Log Database Tool
+// ================================================
+
+type QueryLogDatabaseInput struct {
+       ServiceName      string `json:"serviceName" 
jsonschema:"required,description=The name of the service"`
+       Keyword          string `json:"keyword" 
jsonschema:"required,description=Keyword to search for"`
+       TimeRangeMinutes int    `json:"timeRangeMinutes" 
jsonschema:"required,description=Time range in minutes"`
+}
+
+type LogEntry struct {
+       Timestamp string `json:"timestamp"`
+       Level     string `json:"level"`
+       Message   string `json:"message"`
+}
+
+type QueryLogDatabaseOutput struct {
+       ToolName  string     `json:"toolName"`
+       TotalHits int        `json:"totalHits"`
+       Logs      []LogEntry `json:"logs"`
+       Summary   string     `json:"summary"`
+}
+
+func (o QueryLogDatabaseOutput) Tool() string {
+       return o.ToolName
+}
+
+func queryLogDatabase(ctx *ai.ToolContext, input QueryLogDatabaseInput) 
(QueryLogDatabaseOutput, error) {
+       log.Printf("Tool 'query_log_database' called for service: %s, keyword: 
%s", input.ServiceName, input.Keyword)
+
+       return QueryLogDatabaseOutput{
+               ToolName:  "query_log_database",
+               TotalHits: 152,
+               Logs: []LogEntry{
+                       {
+                               Timestamp: "2025-08-16T15:32:05Z",
+                               Level:     "WARN",
+                               Message:   "Timeout waiting for idle object in 
database connection pool.",
+                       },
+                       {
+                               Timestamp: "2025-08-16T15:32:08Z",
+                               Level:     "WARN",
+                               Message:   "Timeout waiting for idle object in 
database connection pool.",
+                       },
+               },
+               // Summary: fmt.Sprintf("在过去%d分钟内,发现 152 条关于 '%s' 的日志条目", 
input.TimeRangeMinutes, input.Keyword),
+       }, nil
+}
+
+// ================================================
+// Search Archived Logs Tool
+// ================================================
+
+type SearchArchivedLogsInput struct {
+       FilePathPattern string `json:"filePathPattern" 
jsonschema:"required,description=File path pattern to search"`
+       GrepKeyword     string `json:"grepKeyword" 
jsonschema:"required,description=Keyword to grep for"`
+}
+
+type MatchingLine struct {
+       FilePath    string `json:"filePath"`
+       LineNumber  int    `json:"lineNumber"`
+       LineContent string `json:"lineContent"`
+}
+
+type SearchArchivedLogsOutput struct {
+       ToolName      string         `json:"toolName"`
+       FilesSearched int            `json:"filesSearched"`
+       MatchingLines []MatchingLine `json:"matchingLines"`
+       Summary       string         `json:"summary"`
+}
+
+func (o SearchArchivedLogsOutput) Tool() string {
+       return o.ToolName
+}
+
+func searchArchivedLogs(ctx *ai.ToolContext, input SearchArchivedLogsInput) 
(SearchArchivedLogsOutput, error) {
+       log.Printf("Tool 'search_archived_logs' called with pattern: %s, 
keyword: %s", input.FilePathPattern, input.GrepKeyword)
+
+       return SearchArchivedLogsOutput{
+               ToolName:      "search_archived_logs",
+               FilesSearched: 5,
+               MatchingLines: []MatchingLine{
+                       {
+                               FilePath:    
"/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+                               LineNumber:  1024,
+                               LineContent: "Query_time: 25.3s | SELECT 
COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_123';",
+                       },
+                       {
+                               FilePath:    
"/logs/mysql-orders-db/slow-query-2025-08-16.log.gz",
+                               LineNumber:  1029,
+                               LineContent: "Query_time: 28.1s | SELECT 
COUNT(id), SUM(price) FROM orders WHERE user_id = 'VIP_USER_456';",
+                       },
+               },
+               // Summary: "在归档的日志文件中,发现了多条查询,搜索了 5 个文件,找到了 2 条匹配行",

Review Comment:
   This line is commented out but still contains a string literal. Either 
remove the entire line or uncomment it if the Summary field should be populated.
   ```suggestion
   
   ```



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