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Found 62 Skills
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".
Modern, powerful structured logging for Python using structlog. Use when adding or improving logging in Python projects, configuring structlog for dev/production, working with contextvars for request-scoped logging, integrating structlog with stdlib logging, or writing tests for logging behavior.
Python observability patterns including structured logging, metrics, and distributed tracing. Use when adding logging, implementing metrics collection, setting up tracing, or debugging production systems.
Setup Sentry Logging in any project. Use when asked to add Sentry logs, enable structured logging, capture console logs, or integrate logging libraries (Pino, Winston, Loguru) with Sentry. Supports JavaScript, Python, and Ruby.
Idiomatic Golang error handling — creation, wrapping with %w, errors.Is/As, errors.Join, custom error types, sentinel errors, panic/recover, the single handling rule, structured logging with slog, HTTP request logging middleware, and samber/oops for production errors. Built to make logs usable at scale with log aggregation 3rd-party tools. Apply when creating, wrapping, inspecting, or logging errors in Go code.
Review code for logging patterns and suggest evlog adoption. Detects console.log spam, unstructured errors, and missing context. Guides wide event design, structured error handling, request-scoped logging, and log draining with adapters (Axiom, OTLP).
Instrumenting Go applications with OpenTelemetry for distributed tracing, Prometheus for metrics, and structured logging with slog
Configures structured logging (Serilog/.NET, structlog/Python)
Production-grade logging and observability patterns for ASP.NET Core Razor Pages. Covers structured logging with Serilog, correlation IDs, health checks, request logging, OpenTelemetry integration, and diagnostic best practices. Use when setting up structured logging in ASP.NET Core applications, implementing distributed tracing with OpenTelemetry, or configuring health checks and observability.
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.
Golang everyday observability — the always-on signals in production. Covers structured logging with slog, Prometheus metrics, OpenTelemetry distributed tracing, continuous profiling with pprof/Pyroscope, server-side RUM event tracking, alerting, and Grafana dashboards. Apply when instrumenting Go services for production monitoring, setting up metrics or alerting, adding OpenTelemetry tracing, correlating logs with traces, migrating legacy loggers (zap/logrus/zerolog) to slog, adding observability to new features, or implementing GDPR/CCPA-compliant tracking with Customer Data Platforms (CDP). Not for temporary deep-dive performance investigation (→ See golang-benchmark and golang-performance skills).
Logging best practices focused on wide events (canonical log lines) for powerful debugging and analytics