
Handles distributed transaction patterns when you can't use two-phase commit across microservices. Generates orchestrator implementations that coordinate multiple services with proper compensation logic, timeout handling, and failure recovery. Also covers choreography patterns where services react to each other's events without a central coordinator. The templates include concrete order fulfillment workflows spanning inventory, payment, and shipping services. Good for complex business processes that need to roll back partially completed work when something fails downstream. The compensation logic is built to be idempotent and includes monitoring for stuck saga states.
$ npx -y skills add wshobson/agents --skill saga-orchestration --agent claude-codeInstalls into .claude/skills of the current project.
Patterns for managing distributed transactions and long-running business processes without two-phase commit.
What you provide:
What this skill produces:
Moved to references/details.md.
Moved to references/details.md.
saga_id must flow through every event and logsaga_id, step_name, old_state → new_state on every changeA saga enters compensation but never reaches FAILED. This means a compensation handler is throwing an unhandled exception and never publishing SagaCompensationCompleted. Add dead-letter queue (DLQ) handling to compensation consumers and ensure every compensation action publishes a result event even when the underlying operation was already rolled back.
async def handle_release_reservation(self, command: Dict):
try:
await self.release_reservation(command["original_result"]["reservation_id"])
except ReservationNotFoundError:
pass # Already released — treat as success
# Always publish completion, regardless of outcome
await self.event_publisher.publish("SagaCompensationCompleted", {
"saga_id": command["saga_id"],
"step_name": "reserve_inventory"
})
If your orchestrator service restarts mid-saga, it may replay events and re-execute already-completed steps. Guard every step action with an idempotency key — see Template 3 above.
In a choreography-based saga, a downstream service may miss an event if it was offline when published. Use a durable message broker (Kafka with replication, RabbitMQ with persistence) and store the current saga state in a dedicated saga_log table so you can replay from the last known good step.
A step like create_shipment might take up to 15 minutes during peak load but your global timeout is 5 minutes, causing spurious compensation. Make step timeouts configurable per step type — see references/advanced-patterns.md for the TimeoutSagaOrchestrator implementation and the STEP_TIMEOUTS dict pattern.
When two steps both complete before a failure is detected, compensation must run in strict reverse order or you leave data in an inconsistent state. Verify that _compensate() iterates from current_step - 1 down to 0, and add an integration test that deliberately fails at each step index to confirm correct rollback order.
The references/ directory contains production-grade implementations not needed for most sagas:
references/advanced-patterns.md — Full SagaOrchestrator abstract base class, TimeoutSagaOrchestrator with per-step deadlines, detailed bank transfer compensating transaction chain, Prometheus instrumentation, stuck saga PromQL alerts, and DLQ recovery worker.cqrs-implementation — Pair sagas with CQRS for read-model updates after each step completesevent-store-design — Store saga events in an event store for full audit trail and replay capabilityworkflow-orchestration-patterns — Higher-level workflow engines (Temporal, Conductor) that build on saga conceptsSponsors