add-observability

Instrument code with structured logging, metrics, and tracing for production observability.

1|Updated Mar 8, 2026
One-click install
npx skills add https://github.com/gjalla/gjalla-plugin --skill add-observability
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: add-observability
Source: https://github.com/gjalla/gjalla-plugin/tree/main/claude/skills/add-observability
Command: npx skills add https://github.com/gjalla/gjalla-plugin --skill add-observability

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Observability is essential for production systems, ensuring problems are detected, diagnosed, and resolved quickly by instrumenting code for visibility.

Core Features & Use Cases

  • Structured logging (JSON) to capture events with timestamps, levels, and context
  • Metrics and dashboards to monitor health, performance, and latency
  • Distributed tracing to follow request paths across services and dependencies
  • Alerts and SLOs to trigger on symptoms and guide incident response
  • Use Case: When shipping a new service, automatically instrument logging, metrics, and tracing to gain real-time visibility

Quick Start

Instrument your service by adding structured logging, metrics, and tracing per the guidelines to achieve production-ready observability.

Frequently Asked Questions about add-observability

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

FAQPage Schema
How do I add structured logging, metrics, and tracing to a web service for production observability?

To add observability, instrument your web service with structured JSON logging, consistent metrics, and distributed tracing. This captures events, monitors latency, and follows request paths to achieve production-grade visibility for reliable alerting and incident response.

What is production-ready observability and when do I need it for my APIs and background jobs?

Production-ready observability is the instrumentation of code with structured logging, metrics, and tracing to detect and resolve problems quickly. You need it for APIs and background jobs in production or pre-production environments requiring reliable monitoring and alerting.

Does production observability require JSON-formatted logs and unique trace IDs across distributed services?

Yes, production observability requires JSON-formatted logs and unique trace IDs. Structured logging captures contextual events, while trace propagation follows request paths across distributed services and dependencies to diagnose issues accurately.

What's the best way to define SLOs and alerts for monitoring service health and latency?

The best way to define SLOs and alerts is by instrumenting metrics and dashboards to monitor service health and latency. This triggers alerts on symptoms, guiding incident response and ensuring reliability for background jobs and web APIs.

Can I use this observability instrumentation for pre-production environments or is it strictly for production?

You can use this observability instrumentation for pre-production environments as well as production. It applies to web services, APIs, and background jobs, ensuring problems are detected and diagnosed quickly through structured logging and tracing.

Why does distributed tracing fail without consistent metric naming and trace propagation across dependencies?

Distributed tracing fails without trace propagation because unique trace IDs cannot follow request paths across services and dependencies. Consistent metric naming and structured logs are required to correlate events, monitor latency, and diagnose issues reliably.