What programming languages are supported?

While the principles are universal, the skill provides specific implementation examples for Node.js (using Pino and prom-client) and Python (using structlog).

How does this skill handle sensitive data?

The skill includes strict 'Never Log' guidelines for PII, passwords, and tokens to ensure security and compliance with regulations like PCI and HIPAA.

Does this help with debugging microservices?

Yes, it provides detailed patterns for implementing Correlation IDs and OpenTelemetry to trace requests as they flow through multiple services.

How do I choose the right log level?

The skill provides a rubric: use ERROR for events requiring immediate attention (paging), WARN for unexpected but non-fatal issues, and INFO for normal operational milestones.

What is the benefit of structured logging over plain text?

Structured logs (JSON) are machine-parseable, allowing logs to be easily searched, filtered, and aggregated in monitoring tools like ELK, Datadog, or Grafana Loki.

Logging & Observability

Name: Logging & Observability
Author: Claude-Code-Community-Ireland

byClaude-Code-Community-Ireland

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Analytics & Monitoring

Implements standardized structured logging, distributed tracing, and monitoring patterns for robust system observability.

This skill provides Claude with a comprehensive framework for implementing production-grade observability in software projects. It guides the creation of machine-parseable structured logs, establishes clear log level hierarchies, and ensures security by preventing the logging of sensitive data like PII or credentials. Beyond simple logging, it offers actionable patterns for correlation IDs, OpenTelemetry integration for distributed tracing, and Prometheus-based metrics, helping developers build systems that are easy to debug, monitor, and alert on effectively.

Key Features

01Comprehensive log level usage guide with severity selection rules

02Security-focused PII and sensitive data filtering policies

03Standardized structured JSON logging templates for Node.js and Python

04Request tracing and correlation ID propagation for microservices

05Prometheus metric implementation and actionable alert design principles

066 GitHub stars

Use Cases

01Implementing distributed tracing across microservices using OpenTelemetry

02Refactoring unstructured console logs into searchable, machine-parseable JSON

03Setting up a new backend service with production-ready logging and monitoring

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add claude-code-community-ireland/claude-code-resources logging-observability

For use in Claude.ai and ChatGPT

Download Skill

Key Features

01Comprehensive log level usage guide with severity selection rules

02Security-focused PII and sensitive data filtering policies

03Standardized structured JSON logging templates for Node.js and Python

04Request tracing and correlation ID propagation for microservices

05Prometheus metric implementation and actionable alert design principles

066 GitHub stars

Use Cases

01Implementing distributed tracing across microservices using OpenTelemetry

02Refactoring unstructured console logs into searchable, machine-parseable JSON

03Setting up a new backend service with production-ready logging and monitoring

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add claude-code-community-ireland/claude-code-resources logging-observability

For use in Claude.ai and ChatGPT

Download Skill