Agent Skills: Application Logging

Implement structured logging across applications with log aggregation and centralized analysis. Use when setting up application logging, implementing ELK stack, or analyzing application behavior.

UncategorizedID: aj-geddes/useful-ai-prompts/application-logging

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pnpm dlx add-skill https://github.com/aj-geddes/useful-ai-prompts/tree/HEAD/skills/application-logging

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skills/application-logging/SKILL.md

Skill Metadata

Name
application-logging
Description
>

Application Logging

Table of Contents

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(),
);

const logger = winston.createLogger({
  level: process.env.LOG_LEVEL || "info",
  format: logFormat,
  defaultMeta: {
    service: "api-service",
    environment: process.env.NODE_ENV || "development",
  },
  transports: [
    new winston.transports.Console({
      format: winston.format.combine(
        winston.format.colorize(),
        winston.format.simple(),
      ),
    }),
    new winston.transports.File({
      filename: "logs/error.log",
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

| Guide | Contents | |---|---| | Node.js Structured Logging with Winston | Node.js Structured Logging with Winston | | Express HTTP Request Logging | Express HTTP Request Logging | | Python Structured Logging | Python Structured Logging | | Flask Integration | Flask Integration | | ELK Stack Setup | ELK Stack Setup | | Logstash Configuration | Logstash Configuration |

Best Practices

✅ DO

  • Use structured JSON logging
  • Include request IDs for tracing
  • Log at appropriate levels
  • Add context to error logs
  • Implement log rotation
  • Use timestamps consistently
  • Aggregate logs centrally
  • Filter sensitive data

❌ DON'T

  • Log passwords or secrets
  • Log at INFO for every operation
  • Use unstructured messages
  • Ignore log storage limits
  • Skip context information
  • Log to stdout in production
  • Create unbounded log files