load-balancer-setup

aj-geddes/useful-ai-prompts · updated Apr 8, 2026

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$npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill load-balancer-setup
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summary

Deploy and configure load balancers to distribute traffic across multiple backend servers, ensuring high availability, fault tolerance, and optimal resource utilization across your infrastructure.

skill.md

Load Balancer Setup

Table of Contents

Overview

Deploy and configure load balancers to distribute traffic across multiple backend servers, ensuring high availability, fault tolerance, and optimal resource utilization across your infrastructure.

When to Use

  • Multi-server traffic distribution
  • High availability and failover
  • Session persistence and sticky sessions
  • Health checking and auto-recovery
  • SSL/TLS termination
  • Cross-region load balancing
  • API rate limiting at load balancer
  • DDoS mitigation

Quick Start

Minimal working example:

# /etc/haproxy/haproxy.cfg
global
    log stdout local0
    log stdout local1 notice
    maxconn 4096
    daemon

    # Security
    tune.ssl.default-dh-param 2048
    ssl-default-bind-ciphers ECDHE-ECDSA-AES128-GCM-SHA256:ECDHE-RSA-AES128-GCM-SHA256
    ssl-default-bind-options ssl-min-ver TLSv1.2

defaults
    log global
    mode http
    option httplog
    option denylogin
    option forwardfor
    option http-server-close

    # Timeouts
    timeout connect 5000
    timeout client 50000
    timeout server 50000

// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide Contents
HAProxy Configuration HAProxy Configuration
AWS Application Load Balancer (CloudFormation) AWS Application Load Balancer (CloudFormation)
Load Balancer Health Check Script Load Balancer Health Check Script
Load Balancer Monitoring Load Balancer Monitoring

Best Practices

✅ DO

  • Implement health checks
  • Use connection pooling
  • Enable session persistence when needed
  • Monitor load balancer metrics
  • Implement rate limiting
  • Use multiple availability zones
  • Enable SSL/TLS termination
  • Implement graceful connection draining

❌ DON'T

  • Allow single point of failure
  • Skip health check configuration
  • Mix HTTP and HTTPS without redirect
  • Ignore backend server limits
  • Over-provision without monitoring
  • Cache sensitive responses
  • Use default security groups
  • Neglect backup load balancers
how to use load-balancer-setup

How to use load-balancer-setup on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add load-balancer-setup
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/aj-geddes/useful-ai-prompts --skill load-balancer-setup

The skills CLI fetches load-balancer-setup from GitHub repository aj-geddes/useful-ai-prompts and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/load-balancer-setup

Reload or restart Cursor to activate load-balancer-setup. Access the skill through slash commands (e.g., /load-balancer-setup) or your agent's skill management interface.

Security & Verification 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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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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

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share 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

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.442 reviews
  • Neel Martin· Dec 28, 2024

    Useful defaults in load-balancer-setup — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Anaya Zhang· Dec 28, 2024

    load-balancer-setup fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Nia Bansal· Dec 8, 2024

    Keeps context tight: load-balancer-setup is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Advait Agarwal· Dec 4, 2024

    load-balancer-setup is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Liam Sanchez· Nov 27, 2024

    We added load-balancer-setup from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Emma Choi· Nov 23, 2024

    load-balancer-setup reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Omar Ramirez· Nov 19, 2024

    I recommend load-balancer-setup for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Liam Gupta· Oct 18, 2024

    Solid pick for teams standardizing on skills: load-balancer-setup is focused, and the summary matches what you get after install.

  • Isabella Garcia· Oct 14, 2024

    I recommend load-balancer-setup for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Anaya Yang· Oct 10, 2024

    load-balancer-setup reduced setup friction for our internal harness; good balance of opinion and flexibility.

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