How to Get Started with Logging Observability in Your AI Workflow

Logging Observability is a powerful AI agent skill that extends your assistant with new capabilities. Structured logging, distributed tracing, and metrics collection patterns for building observable systems. Use when implementing logging infrastructure, setting up distributed tracing with OpenTelemetry, designing metrics collection (RED/USE methods), configuring alerting and dashboards, or reviewing observability practices. Covers structured JSON logging, context propagation, trace sampling, Prometheus/Grafana stack, alert design, and PII/secret scrubbing. This guide walks you through installing Logging Observability, configuring it for your setup, and running your first commands — so you can start getting value in minutes.

Step-by-Step Guide

1. 1

   Install Logging Observability: npx clawhub@latest --dir ~/.claude/skills install logging-observability

2. 2

   Restart your AI client (Claude Code, Cursor, Gemini CLI, or OpenClaw)

3. 3

   Type a natural language request related to developer & devops to trigger Logging Observability

4. 4

   Review the output and refine your prompt for better results

5. 5

   Combine Logging Observability with other skills to build multi-step workflows

Example Prompts

Copy these prompts and use them with your AI agent after installing Logging Observability

More Use Cases for Logging Observability