microservices-patterns

wshobson/agents · updated May 11, 2026

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$npx skills add https://github.com/wshobson/agents --skill microservices-patterns
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summary

Comprehensive guide to designing distributed systems with service boundaries, communication patterns, and resilience strategies.

  • Covers service decomposition by business capability and domain-driven design, with the Strangler Fig pattern for gradual monolith migration
  • Includes synchronous (REST, gRPC) and asynchronous (Kafka, message queues) communication patterns with event-driven architecture examples
  • Provides Saga pattern implementation for distributed transactions with compensati
skill.md

Microservices Patterns

Master microservices architecture patterns including service boundaries, inter-service communication, data management, and resilience patterns for building distributed systems.

When to Use This Skill

  • Decomposing monoliths into microservices
  • Designing service boundaries and contracts
  • Implementing inter-service communication
  • Managing distributed data and transactions
  • Building resilient distributed systems
  • Implementing service discovery and load balancing
  • Designing event-driven architectures

Core Concepts

1. Service Decomposition Strategies

By Business Capability

  • Organize services around business functions
  • Each service owns its domain
  • Example: OrderService, PaymentService, InventoryService

By Subdomain (DDD)

  • Core domain, supporting subdomains
  • Bounded contexts map to services
  • Clear ownership and responsibility

Strangler Fig Pattern

  • Gradually extract from monolith
  • New functionality as microservices
  • Proxy routes to old/new systems

2. Communication Patterns

Synchronous (Request/Response)

  • REST APIs
  • gRPC
  • GraphQL

Asynchronous (Events/Messages)

  • Event streaming (Kafka)
  • Message queues (RabbitMQ, SQS)
  • Pub/Sub patterns

3. Data Management

Database Per Service

  • Each service owns its data
  • No shared databases
  • Loose coupling

Saga Pattern

  • Distributed transactions
  • Compensating actions
  • Eventual consistency

4. Resilience Patterns

Circuit Breaker

  • Fail fast on repeated errors
  • Prevent cascade failures

Retry with Backoff

  • Transient fault handling
  • Exponential backoff

Bulkhead

  • Isolate resources
  • Limit impact of failures

Service Decomposition Patterns

Pattern 1: By Business Capability

# E-commerce example

# Order Service
class OrderService:
    """Handles order lifecycle."""

    async def create_order(self, order_data: dict) -> Order:
        order = Order.create(order_data)

        # Publish event for other services
        await self.event_bus.publish(
            OrderCreatedEvent(
                order_id=order.id,
                customer_id=order.customer_id,
                items=order.items,
                total=order.total
            )
        )

        return order

# Payment Service (separate service)
class PaymentService:
    """Handles payment processing."""

    async def process_payment(self, payment_request: PaymentRequest) -> PaymentResult:
        # Process payment
        result = await self.payment_gateway.charge(
            amount=payment_request.amount,
            customer=payment_request.customer_id
        )

        if result.success:
            await self.event_bus.publish(
                PaymentCompletedEvent(
                    order_id=payment_request.order_id,
                    transaction_id=result.transaction_id
                )
            )

        return result

# Inventory Service (separate service)
class InventoryService:
    """Handles inventory management."""

    async def reserve_items(self, order_id: str, items: List[OrderItem]) -> ReservationResult:
        # Check availability
        for item in items:
            available = await self.inventory_repo.get_available(item.product_id)
            if available < item.quantity:
                return ReservationResult(
                    success=False,
                    error=f"Insufficient inventory for {item.product_id}"
                )

        # Reserve items
        reservation = await self.create_reservation(order_id, items)

        await self.event_bus.publish(
            InventoryReservedEvent(
                order_id=order_id,
                reservation_id=reservation.id
            )
        )

        return ReservationResult(success=True, reservation=reservation)

Pattern 2: API Gateway

from fastapi import FastAPI, HTTPException, Depends
import httpx
from circuitbreaker import circuit

app = FastAPI()

class APIGateway:
    """Central entry point for all client requests."""

    def __init__(self):
        self.order_service_url = "http://order-service:8000"
        self.payment_service_url = "http://payment-service:8001"
        self.inventory_service_url = "http://inventory-service:8002"
        self.http_client = httpx.AsyncClient(timeout=5.0)

    @circuit(failure_threshold=5, recovery_timeout=30)
    async def call_order_service(self, path: str, method: str = "GET", **kwargs):
        """Call order service with circuit breaker."""
        response = await self.http_client.request(
            method,
            f"{self.order_service_url}{path}",
            **kwargs
        )
        response.raise_for_status()
        return response.json()

    async def create_order_aggregate(self, order_id: str) -> dict:
        """Aggregate data from multiple services."""
        # Parallel requests
        order, payment, inventory = await asyncio.gather(
            self.call_order_service(f"/orders/{order_id}"),
            self.call_payment_service(f"/payments/order/{order_id}"),
            self.call_inventory_service(f"/reservations/order/{order_id}"),
            return_exceptions=True
        )

        # Handle partial failures
        result = {"order": order}
        if not isinstance(payment, Exception):
            result["payment"] = payment
        if not isinstance(inventory, Exception):
            result["inventory"] = inventory

        return result

@app.post("/api/orders")
async def create_order(
    order_data: dict,
    gateway: APIGateway = Depends()
):
    """API Gateway endpoint."""
    try:
        # Route to order service
        order = await gateway.call_order_service(
            "/orders",
            method="POST",
            json
how to use microservices-patterns

How to use microservices-patterns 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 microservices-patterns
2

Execute installation command

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

$npx skills add https://github.com/wshobson/agents --skill microservices-patterns

The skills CLI fetches microservices-patterns from GitHub repository wshobson/agents 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/microservices-patterns

Reload or restart Cursor to activate microservices-patterns. Access the skill through slash commands (e.g., /microservices-patterns) 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.

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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

4.460 reviews
  • Emma Thomas· Dec 20, 2024

    Registry listing for microservices-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ama Johnson· Dec 20, 2024

    microservices-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ama Brown· Dec 20, 2024

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

  • Ama Smith· Dec 16, 2024

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

  • Kwame Anderson· Dec 16, 2024

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

  • Layla Abebe· Dec 12, 2024

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

  • Charlotte White· Nov 23, 2024

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

  • Emma Rao· Nov 11, 2024

    We added microservices-patterns from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • James Torres· Nov 7, 2024

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

  • Kwame Thompson· Nov 7, 2024

    microservices-patterns has been reliable in day-to-day use. Documentation quality is above average for community skills.

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