aj-geddes/useful-ai-prompts

correlation-tracing

Implement distributed tracing with correlation IDs, trace propagation, and span tracking across microservices. Use when debugging distributed systems, monitoring request flows, or implementing observability.

First seen Jan 21, 2026

Installation

$ npx skills add aj-geddes/useful-ai-prompts --skill correlation-tracing

Similar popular skills

Related neighbors and high-traction skills in the same topics — useful to compare before installing.

Also in this package

Other skills from aj-geddes/useful-ai-prompts · top by installs.

npx skills add aj-geddes/useful-ai-prompts

Browse all from aj-geddes/useful-ai-prompts

More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Not declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Also listed on

Alternate registries and mirrors of this skill.

Repository health

Stars 334
License LICENSE
Default branch main
Open issues 1
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 2,673 B
  • docs SUMMARY.md 2,585 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 409 installs

SKILL.md

Correlation & Distributed Tracing

Table of Contents

  • [Overview](#overview)
  • [When to Use](#when-to-use)
  • [Quick Start](#quick-start)
  • [Reference Guides](#reference-guides)
  • [Best Practices](#best-practices)

Overview

Implement correlation IDs and distributed tracing to track requests across multiple services and understand system behavior.

When to Use

  • Microservices architectures
  • Debugging distributed systems
  • Performance monitoring
  • Request flow visualization
  • Error tracking across services
  • Dependency analysis
  • Latency optimization

Quick Start

Minimal working example:

import express from "express";
import { v4 as uuidv4 } from "uuid";

// Async local storage for context
import { AsyncLocalStorage } from "async_hooks";

const traceContext = new AsyncLocalStorage<Map<string, any>>();

interface TraceContext {
  traceId: string;
  spanId: string;
  parentSpanId?: string;
  serviceName: string;
}

function correlationMiddleware(serviceName: string) {
  return (
    req: express.Request,
    res: express.Response,
    next: express.NextFunction,
  ) => {
    // Extract or generate trace ID
    const traceId = (req.headers["x-trace-id"] as string) || uuidv4();
    const parentSpanId = req.headers["x-span-id"] as string;
    const spanId = uuidv4();
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide Contents
[Correlation ID Middleware (Express)](references/correlation-id-middleware-express.md) Correlation ID Middleware (Express)
[OpenTelemetry Integration](references/opentelemetry-integration.md) OpenTelemetry Integration
[Python Distributed Tracing](references/python-distributed-tracing.md) Python Distributed Tracing
[Manual Trace Propagation](references/manual-trace-propagation.md) Manual Trace Propagation

Best Practices

✅ DO

  • Generate trace IDs at entry points
  • Propagate trace context across services
  • Include correlation IDs in logs
  • Use structured logging
  • Set appropriate span attributes
  • Sample traces in high-traffic systems
  • Monitor trace collection overhead
  • Implement context propagation

❌ DON'T

  • Skip trace propagation
  • Log without correlation context
  • Create too many spans
  • Store sensitive data in spans
  • Block on trace reporting
  • Forget error tracking