observability instrumentation

SKILL.md

You can't improve what you can't measure. You can't debug what you can't observe.

❌ Log spamming: Logging everything (noise overwhelms signal) ❌ Unstructured logs: String concatenation instead of structured fields ❌ Synchronous logging: Blocking on log writes (use async handlers) ❌ Missing context: Logs without request ID or user context ❌ Metrics explosion: Too many unique label combinations (cardinality issues)

Status: ✅ Production-ready | 23-46x speedup | 90-95% transferable | Validated in meta-cc

Comprehensive observability methodology implementing three pillars (logs, metrics, traces) with structured logging using Go slog, Prometheus-style metrics, and distributed tracing patterns. Use when adding observability from scratch, logs unstructured or inadequate, no metrics collection, debugging production issues difficult, or need performance monitoring. Provides structured logging patterns (contextual logging, log levels DEBUG/INFO/WARN/ERROR, request ID propagation), metrics instrumentation (counter/gauge/histogram patterns, Prometheus exposition), tracing setup (span creation, context propagation, sampling strategies), and Go slog best practices (JSON formatting, attribute management, handler configuration). Validated in meta-cc with 23-46x speedup vs ad-hoc logging, 90-95% transferability across languages (slog specific to Go but patterns universal). Source: zpankz/mcp-skillset.

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