saga-orchestration

wshobson/agents · updated Apr 8, 2026

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$npx skills add https://github.com/wshobson/agents --skill saga-orchestration
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summary

Orchestrate distributed transactions and long-running workflows with saga patterns for multi-service coordination.

  • Supports both orchestration (centralized coordinator) and choreography (event-driven) saga patterns with step-by-step execution and automatic compensation on failure
  • Includes base orchestrator class with saga state management (started, pending, compensating, completed, failed) and built-in step tracking with results and error handling
  • Provides ready-to-use templates for
skill.md

Saga Orchestration

Patterns for managing distributed transactions and long-running business processes without two-phase commit.

Inputs and Outputs

What you provide:

  • Service boundaries and ownership (which service owns which step)
  • Transaction requirements (which steps must be atomic, which can be eventual)
  • Failure modes for each step (transient vs. permanent, retry policy)
  • SLA requirements per step (informs timeout configuration)
  • Existing event/messaging infrastructure (Kafka, RabbitMQ, SQS, etc.)

What this skill produces:

  • Saga definition with ordered steps, action commands, and compensation commands
  • Orchestrator or choreography implementation for your chosen pattern
  • Compensation logic for each participant service (idempotent, always-succeeds)
  • Step timeout configuration with per-step deadlines
  • Monitoring setup: state machine metrics, stuck saga detection, DLQ recovery

When to Use This Skill

  • Coordinating multi-service transactions without distributed locks
  • Implementing compensating transactions for partial failures
  • Managing long-running business workflows (minutes to hours)
  • Handling failures in distributed systems where atomicity is required
  • Building order fulfillment, approval, or booking processes
  • Replacing fragile two-phase commit with async compensation

Core Concepts

Saga Pattern Types

Choreography                        Orchestration
┌─────┐  ┌─────┐  ┌─────┐         ┌─────────────┐
│Svc A│─►│Svc B│─►│Svc C│         │ Orchestrator│
└─────┘  └─────┘  └─────┘         └──────┬──────┘
   │        │        │                   │
   ▼        ▼        ▼             ┌─────┼─────┐
 Event    Event    Event           ▼     ▼     ▼
                                ┌────┐┌────┐┌────┐
Each service reacts to the      │Svc1││Svc2││Svc3│
previous service's event.       └────┘└────┘└────┘
No central coordinator.    Central coordinator sends
                           commands and tracks state.

Choose orchestration when: You need explicit step tracking, retries, and centralized visibility. Easier to debug.

Choose choreography when: You want loose coupling and services that can evolve independently. Harder to trace.

Saga Execution States

State Description
Started Saga initiated, first step dispatched
Pending Waiting for a step reply from a participant
Compensating A step failed; rolling back completed steps
Completed All forward steps succeeded
Failed Saga failed and all compensations have finished

Compensation Rules

Situation Handling
Step never started No compensation needed (skip)
Step completed successfully Run compensation command
Step failed before completion No compensation needed; mark failed
Compensation itself fails Retry with backoff → DLQ → manual intervention alert
Step result no longer exists Treat compensation as success (idempotency)

Templates

Template 1: Order Fulfillment Saga (Orchestration)

Concrete subclass of the base orchestrator. Defines four steps spanning inventory, payment, shipping, and notification. See references/advanced-patterns.md for the full abstract SagaOrchestrator base class.

from saga_orchestrator import SagaOrchestrator, SagaStep
from typing import Dict, List


class OrderFulfillmentSaga(SagaOrchestrator):
    """Orchestrates order fulfillment across four participant services."""

    @property
    def saga_type(self) -> str:
        return "OrderFulfillment"

    def define_steps(self, data: Dict) -> List[SagaStep]:
        return [
            SagaStep(
                name="reserve_inventory",
                action="InventoryService.ReserveItems",
                compensation="InventoryService.ReleaseReservation"
            ),
            SagaStep(
                name="process_payment",
                action="PaymentService.ProcessPayment",
                compensation="PaymentService.RefundPayment"
            ),
            SagaStep(
                name="create_shipment",
                action="ShippingService.CreateShipment",
                compensation="ShippingService.CancelShipment"
            ),
            SagaStep(
                name="send_confirmation",
                action="NotificationService.SendOrderConfirmation",
                compensation="NotificationService.SendCancellationNotice"
            ),
        ]


# Start a saga
async def create_order(order_data: Dict, saga_store, event_publisher):
    saga = OrderFulfillmentSaga(saga_store, event_publisher)
    return await saga.start({
        "order_id": order_data["order_id"],
        "customer_id": order_data["customer_id"],
        "items": order_data["items"],
        "payment_method": order_data["payment_method"],
        "shipping_address": order_data["shipping_address"],
    })


# Participant service — handles command and publishes reply
class InventoryService:
    async def handle_reserve_items(self, command: Dict):
        try:
            reservation = await self.reserve(command["items"], command["order_id"])
            await self.event_publisher.publish("SagaStepCompleted", {
                "saga_id": command["saga_id"],
                "step_name": "reserve_inventory",
                "result": {"reservation_id": reservation.id}
            })
        except InsufficientInventoryError as e:
            await self.event_publisher.publish("SagaStepFailed", {
                "saga_id": command["saga_id"],
                "step_name": "reserve_inventory",
                "error": str(e)
            })

    async def handle_release_reservation(self, command: Dict):
        """Compensation — idempotent, always publishes completion."""
        try:
            await self.release_reservation(
                command["original_result"]["reservation_id"]
            )
        except ReservationNotFoundError:
            pass  # Already released — treat as success
        await self.event_publisher.publish("SagaCompensationCompleted", {
            "saga_id": command["saga_id"],
            "step_name": "reserve_inventory"
        })

Template 2: Choreography-Based Saga

Each service listens for the previous service's event and reacts. No central coordinator. Compensation is triggered by failure events propagating backward.

from dataclasses import dataclass
from typing import Dict, Any


@dataclass
class SagaContext:
    """Carried through all events in a choreographed saga."""
    saga_id: str
    step: int
    data: Dict[str, Any]
    completed_steps: list


class OrderChoreographySaga:
    """Choreography-based saga — services react to each other's events."""

    def __init__(self, event_bus):
        self.event_bus = event_bus
        self._register_handlers()

    def _register_handlers(self):
        # Forward path
        self.event_bus.subscribe("OrderCreated",       self._on_order_created)
        self.event_bus.subscribe("InventoryReserved",  self._on_inventory_reserved)
        self.event_bus.subscribe("PaymentProcessed",   self._on_payment_processed)
        self.event_bus.subscribe("ShipmentCreated",    self._on_shipment_created)
how to use saga-orchestration

How to use saga-orchestration 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 saga-orchestration
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 saga-orchestration

The skills CLI fetches saga-orchestration 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/saga-orchestration

Reload or restart Cursor to activate saga-orchestration. Access the skill through slash commands (e.g., /saga-orchestration) 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)
  • No comments yet — start the thread.
general reviews

Ratings

4.562 reviews
  • Pratham Ware· Dec 28, 2024

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

  • Chen Rao· Dec 28, 2024

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

  • Xiao Gupta· Dec 24, 2024

    saga-orchestration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Min Mehta· Dec 24, 2024

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

  • Noor Kapoor· Dec 20, 2024

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

  • Min Chawla· Dec 20, 2024

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

  • Noor Malhotra· Dec 16, 2024

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

  • Dhruvi Jain· Dec 4, 2024

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

  • Oshnikdeep· Nov 23, 2024

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

  • Min Malhotra· Nov 19, 2024

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

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