opentelemetry-tracing

Instrument OpenTelemetry tracing across GraphQL, REST, and async microservices.

Updated Jan 8, 2026
One-click install
npx skills add https://github.com/wilsonmsalberto/setup-dotfiles --skill opentelemetry-tracing-wilsonmsalberto
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: opentelemetry-tracing
Source: https://github.com/wilsonmsalberto/setup-dotfiles/tree/main/config/claude-code/work/skills/opentelemetry-tracing
Command: npx skills add https://github.com/wilsonmsalberto/setup-dotfiles --skill opentelemetry-tracing-wilsonmsalberto

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This guidance helps engineering teams instrument applications with OpenTelemetry to achieve consistent traces, improved debugging, and better system observability.

Core Features & Use Cases

  • Auto-instrumentation coverage for HTTP, GraphQL resolvers, and REST data sources
  • Manual span creation and attribute enrichment for complex operations
  • DataSource and HTTP request tracing patterns with contextual propagation
  • Guidance for exporting traces to collectors and dashboards (Jaeger, OpenTelemetry Collector, Prometheus)

Quick Start

Configure your services to emit traces with OpenTelemetry and verify end-to-end observability across HTTP, GraphQL, and data sources.

Frequently Asked Questions about opentelemetry-tracing

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

FAQPage Schema
How do I add OpenTelemetry tracing to GraphQL resolvers and REST data sources?

You can instrument OpenTelemetry tracing across GraphQL resolvers and REST data sources using provided auto-instrumentation patterns and manual span creation for complex operations. Contextual propagation ensures end-to-end visibility across microservices.

What is the best way to propagate traces across async operations in microservices?

Propagating traces across async operations in microservices requires contextual propagation patterns. This guidance provides manual span creation and attribute enrichment to maintain trace continuity throughout asynchronous workflows.

Does this OpenTelemetry tracing guidance support exporting to Jaeger and Prometheus?

Yes, this OpenTelemetry tracing guidance supports exporting traces to collectors and dashboards. It includes specific integration patterns for Jaeger, OpenTelemetry Collector, and Prometheus to visualize system observability.

Can I use automatic instrumentation for HTTP requests in a microservices architecture?

Yes, you can use automatic instrumentation for HTTP requests. The guidance covers auto-instrumentation for HTTP, GraphQL resolvers, and REST data sources, alongside manual span creation for custom or complex operations.

How do I enrich OpenTelemetry spans with custom attributes for complex operations?

You enrich OpenTelemetry spans by using manual span creation and attribute enrichment patterns. This allows you to attach custom contextual data to complex operations that automatic instrumentation does not cover by default.

When should I use manual instrumentation instead of auto-instrumentation for tracing?

You should use manual instrumentation when auto-instrumentation lacks coverage for complex operations. Manual span creation and attribute enrichment provide deeper observability for custom logic beyond standard HTTP, GraphQL, and REST data sources.