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Found 4 Skills
Huawei Cloud CCE Metric analysis skill using the Python dispatcher with hcloud-backed cloud service queries. Use this skill when the user wants to: (1) query Pod/Node/CoreDNS/nginx-ingress/autoscaler/control-plane CPU, memory, disk, QPS, latency, request, connection, certificate, scaling, or error-rate metrics, (2) get resource usage TopN rankings, (3) query ECS/ELB/EIP/NAT cloud resource metrics, (4) aggregate cluster monitoring data with anomaly detection, (5) detect threshold-based resource anomalies. Trigger: user mentions "metric analysis", "指标分析", "CCE metrics", "CCE 指标", "AOM metrics", "AOM 指标", "CoreDNS metrics", "CoreDNS 指标", "nginx ingress metrics", "nginx-ingress 指标", "autoscaler metrics", "autoscaler 指标", "HPA metrics", "HPA 指标", "apiserver metrics", "etcd metrics", "controller manager metrics", "scheduler metrics", "control plane metrics", "控制面指标", "certificate expiration", "证书过期", "resource metrics", "资源指标", "CPU usage", "CPU 使用率", "memory usage", "内存使用率", "performance monitoring", "性能监控", "TopN", "resource ranking", "资源排名"
Investigates a single PostHog error tracking issue end-to-end. Use when the user provides an issue ID or pastes an issue URL (`/error_tracking/<id>`) and wants to understand the error — who it affects, what triggers it, when it started, whether it correlates with a release, browser, OS, or feature flag, and what the next step should be. Pulls aggregated metrics, sample exception events, segment breakdowns, linked replays, and synthesizes a hypothesis-grade summary in one pass.
Grafana Professional Services tool for identifying which Prometheus metrics drive high Data Points per Minute (DPM). Analyzes metric-level DPM with per-label breakdown to help optimize Grafana Cloud costs. Use when the user asks about DPM analysis, high-cardinality metrics, metric cost optimization, finding noisy metrics, or running dpm-finder against a Grafana Cloud Prometheus endpoint.
Diagnose why a product metric changed (dropped, spiked, or plateaued) by orchestrating breakdowns, actors, paths, lifecycle, retention, and annotations queries. Use when the user reports an anomaly, asks "why did X change?", or needs root-cause analysis for a trend, funnel, retention, stickiness, or lifecycle metric.