correlation-tracing
Implement correlation IDs and distributed tracing to track requests across multiple services and understand system behavior.
Works with
0
total installs
0
this week
161
GitHub stars
0
upvotes
Install Skill
Run in your terminal
0
installs
0
this week
161
stars
Installation Guide
How to use correlation-tracing on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
correlation-tracing
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches correlation-tracing from aj-geddes/useful-ai-prompts and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate correlation-tracing. Access via /correlation-tracing in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
Correlation & Distributed Tracing
Table of Contents
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) | Correlation ID Middleware (Express) |
| OpenTelemetry Integration | OpenTelemetry Integration |
| Python Distributed Tracing | Python Distributed Tracing |
| Manual Trace Propagation | 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
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Related Skills
grill-me
388mattpocock/skills
premortem
197parcadei/continuous-claude-v3
deslop
118cursor/plugins
framer-motion
99pproenca/dot-skills
write-a-prd
91mattpocock/skills
travel-planner
90ailabs-393/ai-labs-claude-skills
Reviews
- GGanesh Mohane★★★★★Dec 28, 2024
Solid pick for teams standardizing on skills: correlation-tracing is focused, and the summary matches what you get after install.
- KKiara Srinivasan★★★★★Dec 16, 2024
correlation-tracing has been reliable in day-to-day use. Documentation quality is above average for community skills.
- SSakshi Patil★★★★★Nov 19, 2024
We added correlation-tracing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- KKaira Lopez★★★★★Nov 7, 2024
correlation-tracing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- HHana Brown★★★★★Oct 26, 2024
We added correlation-tracing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- CChaitanya Patil★★★★★Oct 10, 2024
correlation-tracing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- MMaya Robinson★★★★★Sep 17, 2024
correlation-tracing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- AAma Reddy★★★★★Sep 17, 2024
I recommend correlation-tracing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- PPiyush G★★★★★Sep 1, 2024
Registry listing for correlation-tracing matched our evaluation — installs cleanly and behaves as described in the markdown.
- SShikha Mishra★★★★★Aug 20, 2024
correlation-tracing reduced setup friction for our internal harness; good balance of opinion and flexibility.
showing 1-10 of 33
Discussion
Comments — not star reviews- No comments yet — start the thread.