Discover content media monitoring skills, compare source repositories and read the instructions for each workflow.
Production observability with tracing, OpenTelemetry, and Prometheus metrics including structured logging, instrumented functions, distributed tracing, health checks, and request correlation. Use when adding lo...
Observability stack with Prometheus, Grafana, and alerting.
Enterprise Application Monitoring with AI-powered observability architecture, Context7 integration, and intelligent performance orchestration for scalable modern applications
Enterprise Go for systems and network programming Go 1.25.4, Fiber v3, gRPC, context patterns, goroutine orchestration, standard library mastery; activates for REST APIs, microservices, concurrent systems, back...
AI-powered enterprise debugging orchestrator with Context7 integration, intelligent error pattern recognition, automated root cause analysis, predictive fix suggestions, and multi-process debugging coordination...
Monitors Lighthouse scores and JavaScript bundle sizes across deployments with automated alerts when performance thresholds are exceeded. This skill should be used when setting up performance monitoring, enforc...
This skill should be used when adding error tracking and performance monitoring with Sentry and OpenTelemetry tracing to Next.js applications. Apply when setting up error monitoring, configuring tracing for Ser...
Log an observation (measurement, state, or event). Use when recording factual observations during work execution. Triggers on "log observation", "record observation", "note finding", "capture state".
Check resource usage (CPU, memory) on cluster nodes. Used to identify nodes under pressure. Keywords: node resources, cpu, memory, capacity, pressure, metrics, cluster health.
Track and analyze usage metrics with timestamped logging
Check resource usage (CPU, memory) on cluster nodes. Used to identify nodes under pressure. Keywords: node resources, cpu, memory, capacity, pressure, metrics, cluster health.
Log a daily check assessment for developer experience. Captures good/bad day indicators from C-6/C-7 research. Triggers on "daily check", "end of day check", "session check", "how was today".
Use when choosing or configuring Python logging, especially deciding between stdlib logging and loguru for apps or CLIs.
Use when adding logging, error monitoring, metrics, Sentry, debugging production issues, or improving observability
This skill should be used when the user asks to "add logging", "implement metrics", "add tracing", "configure Prometheus", "setup OpenTelemetry", "add health checks", "monitor API", or mentions observability, A...
Troubleshoot agent & tool failures in scheduling orchestration. Use when MCP tools fail, agent communication breaks, constraint engines error, or database operations timeout. Provides systematic incident respon...
Parallel metrics collection using G-6 SIGNAL. Deploy 6 probes to gather metrics from all sources for data-driven decisions.
Enforces project server-side Sentry monitoring conventions when implementing error tracking, performance monitoring, and breadcrumb logging in server actions, facades, middleware, and API routes. This skill ens...
Use this skill when running performance benchmarks, measuring API endpoint response times, detecting performance regressions, running load tests, comparing performance before/after changes, analyzing performanc...
Instantiate polymorphic analytics for multi-context analysis.
Log events using Chronicle Protocol v5 structured format.
Observability patterns for metrics, logs, and traces. Use when implementing monitoring, setting up Prometheus/Grafana, configuring logging pipelines, implementing distributed tracing, or designing alerting syst...
Posts metrics data to a reporting endpoint. Use this when users need to send metrics data that has been collected and stored in temporary files to a reporting API.
Эксперт по аудит-логам. Используй для создания систем логирования, compliance требований, структуры логов и мониторинга.
The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.