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Found 48 Skills
CLI for querying Prometheus and PromQL-compatible engines (Thanos, Cortex, VictoriaMetrics, Grafana Mimir, Grafana Tempo...) — instant queries, range queries, metric discovery (metrics/labels/meta subcommands), output formats (table/csv/json/graph). Apply when executing PromQL queries, troubleshooting performance issues on a software having observability, investigating latency/error rates/saturation, or analyzing time series data.
Generates valid PromQL queries from Cloud Monitoring metric descriptors and resource parameters. Use when asked to create, generate, write, or format PromQL queries, PromQL strings, or PromQL aggregations for Cloud Monitoring metrics and resources. Don't use for raw metric discovery or metric selection.
Comprehensive toolkit for generating best practice PromQL (Prometheus Query Language) queries following current standards and conventions. Use this skill when creating new PromQL queries, implementing monitoring and alerting rules, or building observability dashboards.
Write, validate, and optimise PromQL queries for Prometheus and Grafana Cloud Metrics. Use when the user asks to query metrics, write a PromQL expression, calculate rates, aggregate across labels, build histogram quantiles, create recording rules, debug query performance, or understand metric cardinality. Triggers on phrases like "PromQL", "Prometheus query", "write a metric query", "calculate rate", "histogram_quantile", "recording rule", "metric cardinality", "sum by", "rate vs irate", "absent()", or "query is slow".
Validate, lint, audit, or fix PromQL queries and alerting rules; detects anti-patterns.
Query VictoriaMetrics metrics via curl. Use when running PromQL/MetricsQL queries, discovering metrics/labels, checking alerts and rules, inspecting TSDB status, exporting raw data, checking metric usage statistics, or debugging relabeling/downsampling/retention configs. Triggers on: metric queries, PromQL, MetricsQL, label discovery, series exploration, cardinality checks, alert status, recording rules, active/top queries, export data, metric statistics, relabel debug, downsampling debug, retention debug, flags.
Execute PromQL instant and range queries against Oodle metrics using the Prometheus-compatible query API.
Query Oodle metrics, discover labels and values, and build PromQL expressions using the label discovery workflow.
Prometheus monitoring and alerting for cloud-native observability. USE WHEN: Writing PromQL queries, configuring Prometheus scrape targets, creating alerting rules, setting up recording rules, instrumenting applications with Prometheus metrics, configuring service discovery. DO NOT USE: For building dashboards (use /grafana), for log analysis (use /logging-observability), for general observability architecture (use senior-software-engineer with infrastructure focus). TRIGGERS: metrics, prometheus, promql, counter, gauge, histogram, summary, alert, alertmanager, alerting rule, recording rule, scrape, target, label, service discovery, relabeling, exporter, instrumentation, slo, error budget.
Design, refactor, and validate Grafana dashboards for OpenShift/Kubernetes platform operations. Use when users ask to improve platform health dashboards, prioritize critical tenant-impacting signals, filter noise (for example ArgoCD), add Crossplane/Keycloak health panels, validate PromQL programmatically, or apply GrafanaDashboard CR changes live then promote to GitOps.
Monitors and troubleshoots GKE TPU workloads, nodes, and node pools using GKE system metrics and PromQL. Use when monitoring TensorCore duty cycle, TPU memory, node readiness, multi-host TPU node pool availability, host maintenance or preemption interruptions, and calculating MTTR or MTBI metrics for GKE TPUs. Don't use for general non-TPU GKE workload monitoring or non-metric TPU debugging.
Use these skills when you need to troubleshoot performance bottlenecks, analyze query execution plans, identify resource-heavy processes, and monitor system-level PromQL metrics.