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Found 350 Skills
OpenTelemetry, distributed tracing, structured logging, metrics (Prometheus, Grafana, Datadog). Use when implementing monitoring, tracing, or debugging production issues.
Complete observability stack with structured logging, error tracking, and web analytics.
Implement comprehensive API error handling with standardized error responses, logging, monitoring, and user-friendly messages. Use when building resilient APIs, debugging issues, or improving error reporting.
Implement structured logging across applications with log aggregation and centralized analysis. Use when setting up application logging, implementing ELK stack, or analyzing application behavior.
Use structured logging with Pino throughout your application. Covers log levels, context, and workflow-safe logging patterns.
Enforces consistent structured logging with request correlation IDs, standardized log schema, middleware integration, and best practices. Use for "structured logging", "log standardization", "request tracing", or "log correlation".
Code generator skills that produce production-ready Swift code for common app components. Use when user wants to add logging, analytics, onboarding, review prompts, networking, authentication, paywalls, settings, persistence, error monitoring, CI/CD pipelines, localization, push notifications, deep linking, testing, accessibility, widgets, or feature flags.
Use when building or reviewing service, job, or CLI runtime behavior in Python — designing startup validation, shutdown sequences, observability, and structured logging. Also use when startup crashes from late config, shutdown leaves orphaned processes, terminal states are implicit, or logs lack structure.
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.
Application monitoring and observability setup for Python/React projects. Use when configuring logging, metrics collection, health checks, alerting rules, or dashboard creation. Covers structured logging with structlog, Prometheus metrics for FastAPI, health check endpoints, alert threshold design, Grafana dashboard patterns, error tracking with Sentry, and uptime monitoring. Does NOT cover incident response procedures (use incident-response) or deployment (use deployment-pipeline).
World-class application logging - structured logs, correlation IDs, log aggregation, and the battle scars from debugging production without proper logsUse when "log, logging, logger, debug, trace, audit, structured log, correlation id, request id, log level, winston, pino, bunyan, log4j, logging, observability, debugging, monitoring, tracing, structured-logs, correlation, aggregation" mentioned.
Set up Apollo.io monitoring and observability. Use when implementing logging, metrics, tracing, and alerting for Apollo integrations. Trigger with phrases like "apollo monitoring", "apollo metrics", "apollo observability", "apollo logging", "apollo alerts".