Application Logging

This gets you structured logging set up properly with Winston for Node.js or Python's standard logging library, plus the full ELK stack integration if you need centralized log aggregation. It covers the basics like log levels, JSON formatting, request ID tracing, and context enrichment, along with practical patterns for Express and Flask. The reference guides walk through Logstash configuration and Elasticsearch setup, which saves you from piecing together documentation from three different sources. Most useful when you're moving past console.log debugging or need to meet compliance requirements that demand audit trails. The best practices section is solid on what not to log, like avoiding secrets and preventing unbounded log file growth.

skills.sh installs: 501
GitHub stars: 379
last updated: Aug 21, 2026

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Install

$ npx -y skills add aj-geddes/useful-ai-prompts --skill application-logging --agent claude-code

Installs into .claude/skills of the current project.

Files

Overview

Implement comprehensive structured logging with proper levels, context, and centralized aggregation for effective debugging and monitoring.

When to Use

Application debugging
Audit trail creation
Performance analysis
Compliance requirements
Centralized log aggregation

Quick Start

Minimal working example:

// logger.js
const winston = require("winston");

const logFormat = winston.format.combine(
  winston.format.timestamp({ format: "YYYY-MM-DD HH:mm:ss" }),
  winston.format.errors({ stack: true }),
  winston.format.json(),
);

SKILL.md on GitHub

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