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Found 465 Skills
Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability. Masters log analysis, distributed tracing, Kubernetes debugging, performance optimization, and root cause analysis. Handles production outages, system reliability, and preventive monitoring. Use PROACTIVELY for debugging, incident response, or system troubleshooting.
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.
Guidelines for structured logging, distributed tracing, and debugging patterns across languages. Covers logging best practices, observability, security considerations, and performance analysis.
Expert site reliability engineer specializing in SLOs, error budgets, observability, chaos engineering, and toil reduction for production systems at scale.
Build production-ready multi-agent AI systems with security, observability, and scalability using LangGraph and FastAPI
PostgreSQL monitoring - metrics, alerting, observability
Use the `datadog` CLI to manage Datadog resources — monitors, metrics, events, logs, services, errors, and pipelines. Invoke this skill whenever the user asks to query, create, update, or delete Datadog monitors, search logs or errors, check metric values, list APM services, or manage log pipelines. Also trigger when the user mentions Datadog observability tasks like "check the error rate", "look at monitors", "search logs for errors", "list services", or "set up a log pipeline".
Investigates a triggered observability alert and returns a structured diagnosis with likely cause, scope, and next steps.
Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.
Audit and optimize an existing Convex app: security, scale, upgrades, observability.
Use when you need to implement or improve Java metrics observability with Micrometer — including meter design, naming/tag conventions, cardinality control, timers/counters/gauges/distribution summaries, percentiles/histograms, Actuator/Prometheus integration, and metrics validation through tests. This should trigger for requests such as Improve metrics; Apply Micrometer; Add metrics observability; Refactor Micrometer instrumentation. Part of cursor-rules-java project
Create and manage SLOs in Elastic Observability using the Kibana API. Use when defining SLIs, setting error budgets, or managing SLO lifecycle.