logging-best-practices

Overview

logging-best-practices is a skill that teaches AI coding assistants how to implement effective logging using wide events (canonical log lines). Instead of scattered log statements, it promotes emitting a single, context-rich event per request per service, enabling powerful debugging and analytics capabilities.

Key Features

• Wide events pattern — Consolidates all request context into a single structured event emitted at request completion, replacing scattered log lines throughout handlers
• High cardinality and dimensionality — Advocates for including user IDs, request IDs, and many fields per event to enable specific user queries and answer unanticipated questions
• Business context integration — Guides including subscription tier, cart value, feature flags, and account age so logs reveal business impact (e.g., "premium customer couldn't complete $2,499 purchase" not just "checkout failed")
• Middleware pattern and consistency — Recommends using middleware for wide event infrastructure (timing, status, environment) with handlers adding only business context, plus consistent JSON formatting and field naming

Who is this for?

Developers and engineering teams who want their AI assistant to generate production-quality logging code. Particularly useful for backend and API developers who need structured, queryable logs that support debugging, analytics, and incident investigation across distributed services.