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/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.

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useful-ai-prompts
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$ npx -y skills add aj-geddes/useful-ai-prompts --skill correlation-tracing --agent claude-code

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  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/correlation-tracing

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

SKILL.md

correlation-tracing.SKILL.md
name: correlation-tracing
description: >
  Implement distributed tracing with correlation IDs, trace propagation, and
  span tracking across microservices. Use when debugging distributed systems,
  monitoring request flows, or implementing observability.

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
Read more
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