StatsD metric instrumentation: push metrics over UDP, choose the right metric type, name consistently. Invoke whenever task involves any interaction with StatsD metrics — emitting counters, gauges, timers, histograms, sets, or distributions; configuring DogStatsD tags; tuning sampling rates; or integrating with Graphite, Prometheus, or Telegraf backends.
Create a new track with specification and phased implementation plan
Auto-instrument Node.js applications with distributed tracing, metrics, and logs.
Azure Monitor OpenTelemetry Distro for Python. Use for one-line Application Insights setup with auto-instrumentation.
Use PROACTIVELY when setting up OpenTelemetry monitoring for Claude Code usage tracking, cost analysis, or productivity metrics. Provides local PoC mode (full Docker stack with Grafana) and enterprise mode (centralized infrastructure). Configures telemetry collection, imports dashboards, and verifies data flow. Not for non-Claude telemetry or custom metric definitions.
Comprehensive observability and monitoring skill covering Prometheus, Grafana, metrics collection, alerting, exporters, PromQL, and production monitoring patterns for distributed systems and cloud-native applications
Add a new chain to the address_mapping in stables/stables_config_v2.py. Use this skill whenever the user wants to onboard a new chain for stablecoin tracking, a chain is missing from address_mapping, or the user says anything like "add chain", "new chain", or "onboard chain" in the context of stablecoins.
Create a new built-in evlog adapter to send wide events to an external observability platform. Use when adding a new drain adapter (e.g., for Datadog, Sentry, Loki, Elasticsearch, etc.) to the evlog package. Covers source code, build config, package exports, tests, and all documentation.
Best-practice guide for instrumenting Rust apps with the OpenTelemetry SDK. Use when setting up traces, metrics, logs, exporters, and lifecycle handling. For GenAI attributes and semantics, pair with the opentelemetry-genai-spec skill.
**Observability, Monitoring & SRE**: Comprehensive guide for implementing observability (logs, metrics, traces), setting up monitoring and alerting, defining SLOs/SLIs/SLAs, creating dashboards, and incident detection. Use whenever the user mentions 'observability', 'monitoring', 'alerting', 'logging', 'metrics', 'tracing', 'SLO', 'SLI', 'SLA', 'error budget', 'dashboard', 'Grafana', 'Prometheus', 'DataDog', 'CloudWatch', 'New Relic', 'Jaeger', 'OpenTelemetry', 'OTEL', 'uptime', 'latency', 'p99', 'alert fatigue', 'on-call', 'PagerDuty', or asks 'how do I know if my system is healthy', 'what should I monitor', or wants to improve production visibility.
Implement application metrics (RED, USE), alerting strategies, and monitoring dashboards
Use structured logging with Pino throughout your application. Covers log levels, context, and workflow-safe logging patterns.
Log a decision to the decision log. Supports OPERATIONAL, TACTICAL, DESIGN, and ADR types. Use when recording decisions made by human or AI. Triggers on "decision", "decided", "log decision", "record decision", "document choice".
Configure structured logging with Pino. Outputs human-readable colorized logs in development and structured JSON in production for log aggregation services.
Capture exceptions, add context, create performance spans, and use structured logging with Sentry.
Implement structured logging with appropriate levels, context, and correlation for effective debugging and monitoring
Configure structured logging with Pino. Outputs human-readable colorized logs in development and structured JSON in production for log aggregation services.
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".
Define KPIs, build performance dashboards, track metrics, and drive data-driven decisions
