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structured-logging

Design structured JSON logging with request ID context propagation for Node.js and Python.

8|Updated Mar 8, 2026
Search Tags:#logging#observability#structured logs#pino#json logs#request correlation
One-click install
npx skills add https://github.com/SufficientDaikon/omniskill --skill structured-logging-sufficientdaikon
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: structured-logging
Source: https://github.com/SufficientDaikon/omniskill/tree/main/skills/structured-logging
Command: npx skills add https://github.com/SufficientDaikon/omniskill --skill structured-logging-sufficientdaikon

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenge of creating logging systems that are not only human-readable but also machine-parseable, contextually rich, and adaptable to different environments, ensuring better observability and easier debugging.

Core Features & Use Cases

  • Structured JSON Logging: Ensures all logs are JSON objects for easy parsing by log aggregators.
  • Context Propagation: Automatically includes essential fields like userId and requestId in every log.
  • Environment-Aware Output: Provides pretty-printed logs in development and clean JSON in production.
  • Use Case: Setting up a new Node.js application's logging infrastructure to use Pino for fast, structured logging, including request ID correlation for tracing issues across microservices.

Quick Start

Configure a new Node.js project to use Pino for structured logging with request ID correlation.

Frequently Asked Questions about structured-logging

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up structured logging in Node.js with Pino for request correlation?▼

Structured logging formats application logs as machine-parseable JSON objects rather than plain text strings, enabling log aggregators to easily parse data. It enriches logs with contextual fields like userId and requestId, adapting output to be pretty-printed in development and clean JSON in production.

Can I use structlog for Python structured logging with environment-specific formatting?▼

Yes, this Skill supports Python with structlog to implement structured logging, providing machine-parseable JSON output and context propagation via request IDs. It configures environment-specific formatting and ensures sensitive data redaction for observability platforms.

What is the best way to propagate context like userId and requestId in JSON logs?▼

The best way to propagate context in JSON logs is by automatically including essential fields like userId and requestId in every log entry. This ensures contextually rich logs and easier debugging by maintaining traceability across microservices.

Does structured logging support sensitive data redaction for observability platforms?▼

Yes, structured logging supports sensitive data redaction to ensure machine-readable JSON logs remain secure. This prevents sensitive information from leaking to observability platforms while retaining essential context like requestId for tracing issues.

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