How does this help with distributed tracing?

It provides the logic for managing context variables, correlation IDs, and parent-child span relationships to track requests across different service boundaries.

Does this skill work with OpenTelemetry?

Yes, it includes specific patterns for setting up OpenTelemetry with OTLP exporters, span processors, and auto-instrumentation for frameworks like FastAPI.

Why is structured logging better than plain text logs?

Structured JSON logs allow monitoring tools to easily parse, index, and query log data, making it significantly faster to search for specific error codes or user IDs during an incident.

What programming languages are supported by this skill?

The skill provides detailed, production-ready implementation patterns for both Python and TypeScript, including structured logging formatters and tracing wrappers.

What types of metrics can I implement with this?

The skill covers standard observability metrics including Counters for events, Gauges for resource levels, and Histograms for measuring latency and distributions.

Logging & Observability

Name: Logging & Observability
Author: cosmix

bycosmix

0•

分析と監視

Implements production-grade structured logging, distributed tracing, and metrics collection patterns for robust system monitoring.

This skill equips Claude with the domain-specific knowledge required to build highly observable production systems. It provides standardized implementations for JSON-structured logging, distributed tracing with correlation IDs, and metrics collection using OpenTelemetry or custom registries. By providing templates for both Python and TypeScript, it helps developers move beyond basic console logs to sophisticated monitoring architectures that support better debugging, performance analysis, and incident response in distributed environments.

主な機能

01Metrics collection primitives including Counters, Gauges, and Histograms

02Distributed tracing implementation with correlation IDs and spans

03Standardized log level definitions and best practice usage

04Structured JSON logging patterns for Python and TypeScript

050 GitHub stars

06OpenTelemetry integration and auto-instrumentation guides

ユースケース

01Setting up custom application metrics to monitor business logic and system health

02Modernizing legacy logging systems to structured JSON for tools like ELK or Datadog

03Implementing request tracing across microservices to identify performance bottlenecks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add cosmix/claude-code-setup logging-observability

For use in Claude.ai and ChatGPT

主な機能

01Metrics collection primitives including Counters, Gauges, and Histograms

02Distributed tracing implementation with correlation IDs and spans

03Standardized log level definitions and best practice usage

04Structured JSON logging patterns for Python and TypeScript

050 GitHub stars

06OpenTelemetry integration and auto-instrumentation guides

ユースケース

01Setting up custom application metrics to monitor business logic and system health

02Modernizing legacy logging systems to structured JSON for tools like ELK or Datadog

03Implementing request tracing across microservices to identify performance bottlenecks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add cosmix/claude-code-setup logging-observability

For use in Claude.ai and ChatGPT