What log levels does this skill help implement?

It provides a clear 6-level hierarchy: TRACE, DEBUG, INFO, WARN, ERROR, and FATAL, with specific rules on which levels should be active in production vs. development environments.

Is this logging guide specific to one programming language?

No, it is a universal, language-agnostic standard that can be applied to Node.js, Python, Go, Java, or any other stack requiring structured output.

Can this skill help reduce AI token usage?

Yes, it includes specialized YAML-based formats designed to convey logging standards to AI assistants efficiently, minimizing token costs during development.

How does this skill handle sensitive information?

The skill includes strict protocols for data redaction, ensuring that passwords, API keys, credit card numbers, and PII are never recorded in logs.

Structured Logging & Observability Guide

Name: Structured Logging & Observability Guide
Author: AsiaOstrich

byAsiaOstrich

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分析と監視

Implements standardized, structured logging and observability patterns with built-in PII protection and clear log hierarchies.

This skill provides Claude with comprehensive guidelines for implementing professional-grade structured logging across any software project. It defines a clear hierarchy of log levels (TRACE to FATAL), establishes standardized JSON schemas for production environments, and enforces strict security protocols for masking sensitive PII and credentials. By following these language-agnostic patterns, developers can ensure their applications are observable, searchable, and compliant with modern data privacy standards, making troubleshooting and performance monitoring significantly more efficient.

主な機能

01AI-optimized logging formats (YAML) to reduce token consumption

02Standardized log level hierarchy for consistent environment behavior

03Structured JSON logging schemas with mandatory and suggested fields

04Comprehensive PII masking and sensitive data redaction guidelines

0540 GitHub stars

06Context-rich error logging patterns including stack trace management

ユースケース

01Refactoring legacy console logs into structured, searchable observability data

02Establishing system-wide logging standards for new or existing microservices

03Securing logs by identifying and masking sensitive data like tokens and passwords

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add asiaostrich/universal-dev-standards logging-guide

For use in Claude.ai and ChatGPT

Download Skill