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Saga Orchestration

CommunityPopular
Dicklesworthstone
saga-orchestration

Implement saga patterns for distributed transactions and cross-aggregate workflows. Use when coordinating multi-step business processes, handling compensating transactions, or managing long-running workflows.

Overview

PublisherDicklesworthstone
Repositorypi_agent_rust
Skill namesaga-orchestration
Stars
1.7K
Forks
206
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Dicklesworthstone on GitHub. Read the source before you install it.

Installation

Install the Saga Orchestration AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Dicklesworthstone/pi_agent_rust.git /tmp/pi_agent_rust
mkdir -p .claude/skills
cp -r /tmp/pi_agent_rust/tests/ext_conformance/artifacts/agents-wshobson/backend-development/skills/saga-orchestration .claude/skills/saga-orchestration
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Saga Orchestration in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Saga Orchestration on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Saga Orchestration is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Saga Orchestration

Patterns for managing distributed transactions and long-running business processes.

When to Use This Skill

  • Coordinating multi-service transactions
  • Implementing compensating transactions
  • Managing long-running business workflows
  • Handling failures in distributed systems
  • Building order fulfillment processes
  • Implementing approval workflows

Core Concepts

1. Saga Types

Choreography                    Orchestration
┌─────┐  ┌─────┐  ┌─────┐     ┌─────────────┐
│Svc A│─►│Svc B│─►│Svc C│     │ Orchestrator│
└─────┘  └─────┘  └─────┘     └──────┬──────┘
   │        │        │               │
   ▼        ▼        ▼         ┌─────┼─────┐
 Event    Event    Event       ▼     ▼     ▼
                            ┌────┐┌────┐┌────┐
                            │Svc1││Svc2││Svc3│
                            └────┘└────┘└────┘

2. Saga Execution States

StateDescription
StartedSaga initiated
PendingWaiting for step completion
CompensatingRolling back due to failure
CompletedAll steps succeeded
FailedSaga failed after compensation

Templates

Template 1: Saga Orchestrator Base

python
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Dict, Any, Optional
from datetime import datetime
import uuid

class SagaState(Enum):
    STARTED = "started"
    PENDING = "pending"
    COMPENSATING = "compensating"
    COMPLETED = "completed"
    FAILED = "failed"


@dataclass
class SagaStep:
    name: str
    action: str
    compensation: str
    status: str = "pending"
    result: Optional[Dict] = None
    error: Optional[str] = None
    executed_at: Optional[datetime] = None
    compensated_at: Optional[datetime] = None


@dataclass
class Saga:
    saga_id: str
    saga_type: str
    state: SagaState
    data: Dict[str, Any]
    steps: List[SagaStep]
    current_step: int = 0
    created_at: datetime = field(default_factory=datetime.utcnow)
    updated_at: datetime = field(default_factory=datetime.utcnow)


class SagaOrchestrator(ABC):
    """Base class for saga orchestrators."""

    def __init__(self, saga_store, event_publisher):
        self.saga_store = saga_store
        self.event_publisher = event_publisher

    @abstractmethod
    def define_steps(self, data: Dict) -> List[SagaStep]:
        """Define the saga steps."""
        pass

    @property
    @abstractmethod
    def saga_type(self) -> str:
        """Unique saga type identifier."""
        pass

    async def start(self, data: Dict) -> Saga:
        """Start a new saga."""
        saga = Saga(
            saga_id=str(uuid.uuid4()),
            saga_type=self.saga_type,
            state=SagaState.STARTED,
            data=data,
            steps=self.define_steps(data)
        )
        await self.saga_store.save(saga)
        await self._execute_next_step(saga)
        return saga

    async def handle_step_completed(self, saga_id: str, step_name: str, result: Dict):
        """Handle successful step completion."""
        saga = await self.saga_store.get(saga_id)

        # Update step
        for step in saga.steps:
            if step.name == step_name:
                step.status = "completed"
                step.result = result
                step.executed_at = datetime.utcnow()
                break

        saga.current_step += 1
        saga.updated_at = datetime.utcnow()

        # Check if saga is complete
        if saga.current_step >= len(saga.steps):
            saga.state = SagaState.COMPLETED
            await self.saga_store.save(saga)
            await self._on_saga_completed(saga)
        else:
            saga.state = SagaState.PENDING
            await self.saga_store.save(saga)
            await self._execute_next_step(saga)

    async def handle_step_failed(self, saga_id: str, step_name: str, error: str):
        """Handle step failure - start compensation."""
        saga = await self.saga_store.get(saga_id)

        # Mark step as failed
        for step in saga.steps:
            if step.name == step_name:
                step.status = "failed"
                step.error = error
                break

        saga.state = SagaState.COMPENSATING
        saga.updated_at = datetime.utcnow()
        await self.saga_store.save(saga)

        # Start compensation from current step backwards
        await self._compensate(saga)

    async def _execute_next_step(self, saga: Saga):
        """Execute the next step in the saga."""
        if saga.current_step >= len(saga.steps):
            return

        step = saga.steps[saga.current_step]
        step.status = "executing"
        await self.saga_store.save(saga)

        # Publish command to execute step
        await self.event_publisher.publish(
            step.action,
            {
                "saga_id": saga.saga_id,
                "step_name": step.name,
                **saga.data
            }
        )

    async def _compensate(self, saga: Saga):
        """Execute compensation for completed steps."""
        # Compensate in reverse order
        for i in range(saga.current_step - 1, -1, -1):
            step = saga.steps[i]
            if step.status == "completed":
                step.status = "compensating"
                await self.saga_store.save(saga)

                await self.event_publisher.publish(
                    step.compensation,
                    {
                        "saga_id": saga.saga_id,
                        "step_name": step.name,
                        "original_result": step.result,
                        **saga.data
                    }
                )

    async def handle_compensation_completed(self, saga_id: str, step_name: str):
        """Handle compensation completion."""
        saga = await self.saga_store.get(saga_id)

        for step in saga.steps:
            if step.name == step_name:
                step.status = "compensated"
                step.compensated_at = datetime.utcnow()
                break

        # Check if all compensations complete
        all_compensated = all(
            s.status in ("compensated", "pending", "failed")
            for s in saga.steps
        )

        if all_compensated:
            saga.state = SagaState.FAILED
            await self._on_saga_failed(saga)

        await self.saga_store.save(saga)

    async def _on_saga_completed(self, saga: Saga):
        """Called when saga completes successfully."""
        await self.event_publisher.publish(
            f"{self.saga_type}Completed",
            {"saga_id": saga.saga_id, **saga.data}
        )

    async def _on_saga_failed(self, saga: Saga):
        """Called when saga fails after compensation."""
        await self.event_publisher.publish(
            f"{self.saga_type}Failed",
            {"saga_id": saga.saga_id, "error": "Saga failed", **saga.data}
        )

Template 2: Order Fulfillment Saga

python
class OrderFulfillmentSaga(SagaOrchestrator):
    """Orchestrates order fulfillment across 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"
            )
        ]


# Usage
async def create_order(order_data: Dict):
    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"]
    })


# Event handlers in each service
class InventoryService:
    async def handle_reserve_items(self, command: Dict):
        try:
            # Reserve inventory
            reservation = await self.reserve(
                command["items"],
                command["order_id"]
            )
            # Report success
            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):
        # Compensating action
        await self.release_reservation(
            command["original_result"]["reservation_id"]
        )
        await self.event_publisher.publish(
            "SagaCompensationCompleted",
            {
                "saga_id": command["saga_id"],
                "step_name": "reserve_inventory"
            }
        )

Template 3: Choreography-Based Saga

python
from dataclasses import dataclass
from typing import Dict, Any
import asyncio

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


class OrderChoreographySaga:
    """Choreography-based saga using events."""

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

    def _register_handlers(self):
        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)

        # Compensation handlers
        self.event_bus.subscribe("PaymentFailed", self._on_payment_failed)
        self.event_bus.subscribe("ShipmentFailed", self._on_shipment_failed)

    async def _on_order_created(self, event: Dict):
        """Step 1: Order created, reserve inventory."""
        await self.event_bus.publish("ReserveInventory", {
            "saga_id": event["order_id"],
            "order_id": event["order_id"],
            "items": event["items"]
        })

    async def _on_inventory_reserved(self, event: Dict):
        """Step 2: Inventory reserved, process payment."""
        await self.event_bus.publish("ProcessPayment", {
            "saga_id": event["saga_id"],
            "order_id": event["order_id"],
            "amount": event["total_amount"],
            "reservation_id": event["reservation_id"]
        })

    async def _on_payment_processed(self, event: Dict):
        """Step 3: Payment done, create shipment."""
        await self.event_bus.publish("CreateShipment", {
            "saga_id": event["saga_id"],
            "order_id": event["order_id"],
            "payment_id": event["payment_id"]
        })

    async def _on_shipment_created(self, event: Dict):
        """Step 4: Complete - send confirmation."""
        await self.event_bus.publish("OrderFulfilled", {
            "saga_id": event["saga_id"],
            "order_id": event["order_id"],
            "tracking_number": event["tracking_number"]
        })

    # Compensation handlers
    async def _on_payment_failed(self, event: Dict):
        """Payment failed - release inventory."""
        await self.event_bus.publish("ReleaseInventory", {
            "saga_id": event["saga_id"],
            "reservation_id": event["reservation_id"]
        })
        await self.event_bus.publish("OrderFailed", {
            "order_id": event["order_id"],
            "reason": "Payment failed"
        })

    async def _on_shipment_failed(self, event: Dict):
        """Shipment failed - refund payment and release inventory."""
        await self.event_bus.publish("RefundPayment", {
            "saga_id": event["saga_id"],
            "payment_id": event["payment_id"]
        })
        await self.event_bus.publish("ReleaseInventory", {
            "saga_id": event["saga_id"],
            "reservation_id": event["reservation_id"]
        })

Template 4: Saga with Timeouts

python
class TimeoutSagaOrchestrator(SagaOrchestrator):
    """Saga orchestrator with step timeouts."""

    def __init__(self, saga_store, event_publisher, scheduler):
        super().__init__(saga_store, event_publisher)
        self.scheduler = scheduler

    async def _execute_next_step(self, saga: Saga):
        if saga.current_step >= len(saga.steps):
            return

        step = saga.steps[saga.current_step]
        step.status = "executing"
        step.timeout_at = datetime.utcnow() + timedelta(minutes=5)
        await self.saga_store.save(saga)

        # Schedule timeout check
        await self.scheduler.schedule(
            f"saga_timeout_{saga.saga_id}_{step.name}",
            self._check_timeout,
            {"saga_id": saga.saga_id, "step_name": step.name},
            run_at=step.timeout_at
        )

        await self.event_publisher.publish(
            step.action,
            {"saga_id": saga.saga_id, "step_name": step.name, **saga.data}
        )

    async def _check_timeout(self, data: Dict):
        """Check if step has timed out."""
        saga = await self.saga_store.get(data["saga_id"])
        step = next(s for s in saga.steps if s.name == data["step_name"])

        if step.status == "executing":
            # Step timed out - fail it
            await self.handle_step_failed(
                data["saga_id"],
                data["step_name"],
                "Step timed out"
            )

Best Practices

Do's

  • Make steps idempotent - Safe to retry
  • Design compensations carefully - They must work
  • Use correlation IDs - For tracing across services
  • Implement timeouts - Don't wait forever
  • Log everything - For debugging failures

Don'ts

  • Don't assume instant completion - Sagas take time
  • Don't skip compensation testing - Most critical part
  • Don't couple services - Use async messaging
  • Don't ignore partial failures - Handle gracefully

Resources

Frequently asked questions

What does the Saga Orchestration AI skill do?

Implement saga patterns for distributed transactions and cross-aggregate workflows. Use when coordinating multi-step business processes, handling compensating transactions, or managing long-running workflows.

Why use Saga Orchestration on TypingMind?

Because you install it once and use it with any model. Saga Orchestration is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Saga Orchestration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dicklesworthstone/pi_agent_rust/tree/main/tests/ext_conformance/artifacts/agents-wshobson/backend-development/skills/saga-orchestration. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Saga Orchestration?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Saga Orchestration?

As many as you like. As long as a model supports skills, you can use Saga Orchestration with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Saga Orchestration AI skill free?

It is published on GitHub by Dicklesworthstone. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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