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Found 112 Skills
Perses plugin testing: CUE schema unit tests with percli plugin test-schemas, React component tests, integration testing with local Perses server, and Grafana migration compatibility testing. Use for "test perses plugin", "perses plugin test", "perses schema test". Do NOT use for dashboard validation (use perses-lint).
Use this skill whenever working with QuestDB — a high-performance time-series database. Trigger on any mention of QuestDB, time-series SQL with SAMPLE BY, LATEST ON, ASOF JOIN, ILP ingestion, or the questdb Python/Go/Java/Rust/.NET client libraries. Also trigger when writing Grafana queries against QuestDB, creating materialized views for time-series rollups, working with order book or financial market data in QuestDB, or any SQL that involves designated timestamps or time-partitioned tables. QuestDB extends SQL with unique time-series keywords — standard PostgreSQL or MySQL patterns will fail. Always read this skill before writing QuestDB SQL to avoid hallucinating incorrect syntax.
Use when writing or reviewing k6 documentation across TypeScript types, user docs, and release notes.
Best practices for working with Go codebases. Use when writing, debugging, or exploring Go code, including reading dependency sources and documentation.
Expert evaluator for Prometheus label strategy. Audits, designs, and improves label schemas using cardinality scoring, access-pattern alignment, static vs. dynamic label rules, histogram bucket discipline, instrumentation hygiene, and source-side prevention via relabel_config / metric_relabel_configs. Use when the user asks to evaluate, audit, design, or improve Prometheus labels — or asks how to prevent high cardinality at the source. For post-ingest aggregation, see the adaptive-metrics skill. For "why is my Prometheus slow / expensive right now" triage, see prometheus-cardinality-troubleshooter.
k6 performance and load testing. Covers writing test scripts in JavaScript/TypeScript, all test types (load/stress/spike/soak/smoke/breakpoint), thresholds, checks, scenarios, executors, extensions, result analysis, k6 Cloud execution, and CI/CD integration. Use when writing k6 tests, debugging test failures, setting up load testing pipelines, choosing executors/scenarios, or interpreting k6 results.
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.
OpenTelemetry, distributed tracing, structured logging, metrics (Prometheus, Grafana, Datadog). Use when implementing monitoring, tracing, or debugging production issues.
Comprehensive logging and observability patterns for production systems including structured logging, distributed tracing, metrics collection, log aggregation, and alerting. Triggers for this skill - log, logging, logs, trace, tracing, traces, metrics, observability, OpenTelemetry, OTEL, Jaeger, Zipkin, structured logging, log level, debug, info, warn, error, fatal, correlation ID, span, spans, ELK, Elasticsearch, Loki, Datadog, Prometheus, Grafana, distributed tracing, log aggregation, alerting, monitoring, JSON logs, telemetry.
Expert knowledge for Azure Monitor development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building, debugging, or optimizing Azure Monitor applications. Not for Azure Managed Grafana (use azure-managed-grafana), Azure Network Watcher (use azure-network-watcher), Azure Service Health (use azure-service-health), Azure Defender For Cloud (use azure-defender-for-cloud).
Monitoring and observability with OpenTelemetry, Prometheus, Grafana dashboards, and structured logging
Use this skill when implementing logging, metrics, distributed tracing, alerting, or defining SLOs. Triggers on structured logging, Prometheus, Grafana, OpenTelemetry, Datadog, distributed tracing, error tracking, dashboards, alert fatigue, SLIs, SLOs, error budgets, and any task requiring system observability or monitoring setup.