skill-creator
Create new openrappter skills with proper SKILL.md format and metadata.
Create new openrappter skills with proper SKILL.md format and metadata.
Observability and monitoring patterns including logging, metrics, distributed tracing, alerting, and monitoring stack setup. Use when setting up monitoring, implementing logging strategies, configuring alerts, or debugging production issues.
Set up APM instrumentation and log shipping — framework-specific agents, Filebeat, Elastic Agent, and correlation.
Implements comprehensive observability with OpenTelemetry tracing, Prometheus metrics, and structured logging. Includes instrumentation plans, sample dashboards, and alert candidates. Use for "observability", "monitoring", "tracing", or "metrics".
OpenTelemetry - vendor-neutral observability framework for distributed systems. Provides traces, metrics, and logs with standardized instrumentation and exporters. USE WHEN: user mentions "opentelemetry", "otel", "distributed tracing", "observability", asks about "how to trace microservices", "opentelemetry setup", "jaeger integration", "prometheus metrics" DO NOT USE FOR: Application logging only - use logging skills instead, APM vendor-specific - use vendor docs, Simple monitoring - Prometheus/Grafana may be sufficient
Production server monitoring stack covering Prometheus, Node Exporter, Grafana, Alertmanager, Loki, and Promtail on bare-metal or VM Linux hosts. USE WHEN: - Setting up monitoring for a new production server or VPS - Configuring Prometheus scrape targets for application or system metrics - Creating Grafana dashboards and datasource provisioning - Writing Alertmanager routing rules with email/Slack notifications - Implementing the PLG stack (Promtail + Loki + Grafana) for log aggregation - Performing live system diagnostics with htop, iotop, nethogs, ss, vmstat, iostat - Setting up uptime monitoring with UptimeRobot or healthchecks.io DO NOT USE FOR: - Kubernetes-native observability (use the kubernetes skill instead) - Application-level APM (distributed tracing with Jaeger/Tempo — use observability skill) - Cloud-managed monitoring (CloudWatch, GCP Monitoring, Azure Monitor) - Windows Server monitoring
OpenTelemetry SDK initialization and configuration. Use when setting up or reviewing TracerProvider, MeterProvider, or LoggerProvider; choosing exporters, processors, or propagators; configuring OTLP transport; or extending an existing SDK setup for new signals. Use this skill whenever the task involves wiring up the OpenTelemetry SDK, even if the user only mentions "add tracing" or "set up metrics" without saying "SDK."
Migrate OpenTelemetry Span Events (AddEvent, RecordException) to the Logs API following the OTEP 4430 deprecation plan. Use when migrating instrumentation from span events to log-based events, reviewing code that still uses AddEvent or RecordException, or planning a migration across a codebase.
Construct telemetrygen commands for generating synthetic OpenTelemetry traces, metrics, and logs via OTLP. Use this skill whenever the user wants to generate test telemetry, load test a collector or backend, create synthetic OTLP data, send sample traces/metrics/logs to an endpoint, test collector pipelines or processors, validate OTTL transforms, test tail sampling, or mentions telemetrygen in any context. Also trigger when the user asks how to simulate telemetry traffic, stress test an observability stack, or produce sample data for dashboards.
Detects lateral movement techniques including Pass-the-Hash, PsExec, WMI execution, RDP pivoting, and SMB-based spreading using SIEM correlation of Windows event logs, network flow data, and endpoint telemetry mapped to MITRE ATT&CK Lateral Movement (TA0008) techniques.
Implement analytics, error monitoring, and performance tracking with Vercel Analytics, Google Analytics, Sentry, and custom event tracking.
This skill automates the setup of distributed tracing for microservices. It helps developers implement end-to-end request visibility by configuring context propagation, span creation, trace collection, and analysis. Use this skill when the user requests to set up distributed tracing, implement observability, or troubleshoot performance issues in a microservices architecture. The skill is triggered by phrases such as "setup tracing", "implement distributed tracing", "configure opentelemetry", or "add observability to microservices".
This skill enables Claude to collect comprehensive infrastructure performance metrics across compute, storage, network, containers, load balancers, and databases. It is triggered when the user requests "collect infrastructure metrics", "monitor server performance", "set up performance dashboards", or needs to analyze system resource utilization. The skill configures metrics collection, sets up aggregation, and helps create infrastructure dashboards for health monitoring and capacity tracking. It supports configuration for Prometheus, Datadog, and CloudWatch.
This skill sets up log aggregation solutions using ELK (Elasticsearch, Logstash, Kibana), Loki, or Splunk. It generates production-ready configurations and setup code based on specific requirements and infrastructure. Use this skill when the user requests to set up logging infrastructure, configure log aggregation, deploy ELK stack, deploy Loki, deploy Splunk, or needs help with observability. It is triggered by terms like "log aggregation," "ELK setup," "Loki configuration," "Splunk deployment," or similar requests for centralized logging solutions.
This skill automates the setup of distributed tracing for microservices. It helps developers implement end-to-end request visibility by configuring context propagation, span creation, trace collection, and analysis. Use this skill when the user requests to set up distributed tracing, implement observability, or troubleshoot performance issues in a microservices architecture. The skill is triggered by phrases such as "setup tracing", "implement distributed tracing", "configure opentelemetry", or "add observability to microservices".
This skill deploys monitoring stacks, including Prometheus, Grafana, and Datadog. It is used when the user needs to set up or configure monitoring infrastructure for applications or systems. The skill generates production-ready configurations, implements best practices, and supports multi-platform deployments. Use this when the user explicitly requests to deploy a monitoring stack, or mentions Prometheus, Grafana, or Datadog in the context of infrastructure setup.
Use when creating or updating AGENTS.md contributor guidelines for this repository.
Use when choosing or configuring Python logging, especially deciding between stdlib logging and loguru for apps or CLIs.
Real-time monitoring of ClickHouse metrics, events, and asynchronous metrics. Use for load average, connections, queue monitoring, and resource saturation.
Logging, debugging, profiling, and performance monitoring for development. Use when adding logging, debugging issues, profiling performance, or instrumenting code for observability.