What log levels does this skill support?

It defines a standard hierarchy including TRACE, DEBUG, INFO, WARN, ERROR, and FATAL to ensure clear event categorization and filtering.

How does this skill handle sensitive data?

It provides strict guidelines and code examples for masking or redacting passwords, API keys, and PII to prevent sensitive information from leaking into logs.

Does it work with specific programming languages?

The skill is language-agnostic, focusing on universal standards and architectural patterns that can be applied to any programming language or framework.

How does it help with distributed tracing?

It enforces the use of required fields like request_id and trace_id, allowing developers to track requests across multiple services effectively.

Is this skill compatible with production environments?

Yes, it specifically recommends and helps implement structured JSON logging for production to facilitate easy parsing by modern log management tools.

Structured Logging Guide

Name: Structured Logging Guide
Author: ValorVie

byValorVie

•

Analytics & Monitoring

Implements standardized, structured logging and observability practices with proper log levels and sensitive data protection.

This skill provides comprehensive guidance for implementing professional-grade logging systems within your codebase. It establishes consistent log levels ranging from TRACE to FATAL, enforces structured JSON formatting for production observability, and provides strict protocols for handling sensitive PII and secrets. Whether you are setting up a new service or refactoring legacy logs, this skill ensures your application telemetry is actionable, secure, and compatible with modern log management stacks like ELK or Datadog.

Key Features

01Project-specific logging configuration detection and setup assistance

02Standardized log level hierarchy (TRACE, DEBUG, INFO, WARN, ERROR, FATAL)

03Automated sensitive data redaction and PII handling guidelines

04Consistent snake_case naming conventions for domain-specific fields

05Structured JSON logging templates for production observability

063 GitHub stars

Use Cases

01Standardizing log formats across a distributed microservices architecture

02Debugging complex application flows with trace-level instrumentation

03Ensuring security compliance by redacting secrets and PII from application logs

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add valorvie/custom-skills logging-guide

For use in Claude.ai and ChatGPT

Key Features

01Project-specific logging configuration detection and setup assistance

02Standardized log level hierarchy (TRACE, DEBUG, INFO, WARN, ERROR, FATAL)

03Automated sensitive data redaction and PII handling guidelines

04Consistent snake_case naming conventions for domain-specific fields

05Structured JSON logging templates for production observability

063 GitHub stars

Use Cases

01Standardizing log formats across a distributed microservices architecture

02Debugging complex application flows with trace-level instrumentation

03Ensuring security compliance by redacting secrets and PII from application logs

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add valorvie/custom-skills logging-guide

For use in Claude.ai and ChatGPT