saga-orchestration

Overview of saga-orchestration skill

What saga-orchestration helps you do

The saga-orchestration skill helps you design and implement distributed transactions across multiple services when two-phase commit is not available or not desirable. Its real job is not just “draw a saga,” but turn a risky cross-service workflow into a concrete execution model with ordered steps, compensations, timeouts, and recovery paths.

Best fit for Backend Development teams

This is a strong fit for architects and backend engineers working on checkout flows, booking systems, fulfillment pipelines, account provisioning, or any workflow where one business action spans multiple services and partial failure is expected. It is especially relevant for saga-orchestration for Backend Development when you already have messaging or event infrastructure and need a safer coordination pattern.

What users care about before installing

Most users evaluating the saga-orchestration skill want to know:

• whether it gives more than a generic “use the saga pattern” prompt
• whether it supports orchestration and compensation design in practical terms
• what inputs they must prepare before asking the agent to generate anything
• whether it helps with production realities like idempotency, stuck sagas, DLQs, and retries

This skill scores well on those points because it asks for operational inputs up front and explicitly includes monitoring and recovery concerns in the output.

Main differentiators

Compared with a normal architecture prompt, saga-orchestration is more useful because it centers on:

• ordered step definitions
• explicit compensation commands
• per-step timeout thinking
• retry and failure classification
• orchestrator vs. choreography choices
• state machine observability and stuck-saga detection

The included references/advanced-patterns.md also gives you a deeper implementation path instead of stopping at conceptual guidance.

When this skill is not the right tool

Do not reach for saga-orchestration if your workflow is fully local to one database, can be solved with simple eventual consistency and no rollback semantics, or does not justify the complexity of state tracking and compensation. It is also a weak fit if you cannot define service ownership clearly; saga design breaks down fast when step boundaries are ambiguous.

How to Use saga-orchestration skill

Install context for saga-orchestration

Install the parent skill repository, then invoke the skill by name from your agent environment:

npx skills add https://github.com/wshobson/agents

Then use the saga-orchestration skill from the installed collection. The repo path is:

plugins/backend-development/skills/saga-orchestration

If your environment supports direct skill selection, choose saga-orchestration explicitly rather than hoping the model infers it from a vague backend prompt.

Read these files first

For a fast adoption decision, start here:

1. plugins/backend-development/skills/saga-orchestration/SKILL.md
2. plugins/backend-development/skills/saga-orchestration/references/advanced-patterns.md

SKILL.md tells you what inputs the skill expects and what outputs it can generate. references/advanced-patterns.md is the practical follow-up if you need an orchestrator base class, state modeling, or compensation sequencing ideas.

What input the skill needs from you

The saga-orchestration usage quality depends heavily on input quality. Provide:

• service boundaries and ownership
• ordered business steps
• which steps are mandatory vs. eventually consistent
• failure modes per step
• retry policy expectations
• timeout/SLA requirements
• current transport stack such as Kafka, RabbitMQ, or SQS
• persistence approach for saga state
• what “success” and “compensation complete” mean in business terms

If you skip these, the agent will still produce something, but it will be generic and often unsafe.

Turn a rough goal into a strong prompt

Weak prompt:

Design a saga for checkout.

Better prompt:

Use the saga-orchestration skill to design an orchestrated checkout saga for Order, Inventory, Payment, and Shipping services. We use Kafka, each service owns its own database, payment authorization must happen before shipment, inventory reservation expires after 15 minutes, and payment capture must be compensated with refund if shipment creation fails. Classify transient vs permanent failures, define retries and timeouts per step, and include stuck-saga detection and DLQ recovery.

That stronger version gives the skill enough operational context to produce a usable design.

Expected output from saga-orchestration

A good run of the saga-orchestration skill should produce:

• a step-by-step saga definition
• action and compensation commands for each participant
• orchestrator or choreography recommendation
• timeout and retry handling
• state transition logic
• observability guidance for failures and stuck flows
• participant service responsibilities

If the output lacks compensation logic or idempotency guidance, ask for a revision before implementation.

Choose orchestration vs choreography deliberately

Use orchestration when you need:

• central visibility
• clearer sequencing
• easier timeout enforcement
• simpler debugging of stuck flows

Use choreography when you need:

• looser coupling
• event-native scaling
• fewer central dependencies

The skill is most decision-useful when you ask it to justify the choice, not just implement one pattern by default.

Practical workflow for first use

A high-signal workflow is:

1. Describe the business transaction end to end.
2. List each participating service and owned data.
3. Mark the irreversible steps.
4. Define compensation for every reversible step.
5. Ask the skill to model the saga.
6. Review whether compensations are truly idempotent.
7. Add monitoring, timeout, and DLQ handling.
8. Only then generate framework-specific code.

This sequence avoids a common failure mode: generating code before the rollback semantics are sound.

Use advanced patterns when the first draft is too shallow

Open references/advanced-patterns.md when you need:

• a reusable orchestrator base class
• explicit state enums
• persisted saga-step state
• reverse-order compensation handling
• event publication around completion and failure

That file is particularly useful if your first agent output sounds architecturally correct but lacks execution details.

Tips that materially improve output quality

Ask the skill to be specific about:

• which commands are synchronous vs async
• where saga state is stored
• how duplicate messages are handled
• which compensations must always succeed
• how to recover after orchestrator restarts
• what metrics identify a stuck saga

These details change implementation quality far more than asking for extra diagrams or more pattern explanation.

Common repo-reading path for implementation

If you are deciding whether to adopt saga-orchestration install work now or later, this is the fastest path:

• skim SKILL.md for fit and required inputs
• read the advanced reference for implementation shape
• compare the generated design against your actual broker, persistence, and failure model
• only then wire it into your own stack and naming conventions

This avoids overcommitting to example structures that may not match your platform.

saga-orchestration skill FAQ

Is saga-orchestration better than a normal architecture prompt?

Yes, if your problem includes distributed failure handling. A generic prompt may suggest sagas conceptually, but saga-orchestration is stronger at forcing concrete outputs: step ordering, compensation commands, timeout reasoning, and stuck-saga recovery.

Is the saga-orchestration skill beginner friendly?

It is usable by intermediate engineers, but complete beginners may struggle if they do not already understand service ownership, messaging, and eventual consistency. The skill assumes you can describe your system boundaries and failure model.

Does saga-orchestration generate production-ready code?

Not by itself. It is best treated as a design-and-scaffolding accelerator. You still need to adapt persistence, broker integration, observability, and framework specifics to your stack.

When should I not use saga-orchestration?

Avoid it when a local transaction is enough, when compensation is impossible or undefined, or when the business process is simple enough that asynchronous rollback machinery would be overengineering.

Can I use saga-orchestration with Kafka, RabbitMQ, or SQS?

Yes. The skill explicitly expects existing messaging infrastructure as an input. You will get better results if you state delivery guarantees, retry behavior, and dead-letter handling for your chosen platform.

Does this skill support debugging stuck sagas?

Yes. That is one of its practical strengths. It includes monitoring setup, state-machine metrics, and recovery thinking, which matter more in production than the initial happy-path design.

How to Improve saga-orchestration skill

Give business invariants, not just service names

To improve saga-orchestration results, tell the agent what must never happen. Example:

• “never ship without successful payment capture”
• “inventory reservation may expire, but order record must remain”
• “refund may be delayed, but duplicate refund is unacceptable”

These invariants help the skill choose better compensations and timeout logic.

Separate transient failures from permanent ones

One of the biggest quality levers is classifying failures correctly. If you say only “payment may fail,” the output stays generic. Instead specify:

• transient: gateway timeout, broker lag, temporary downstream outage
• permanent: card declined, item discontinued, invalid address

This changes retry policy, compensation timing, and alerting design.

Force idempotency into every step

A common failure mode in first-pass saga-orchestration usage is compensation that looks correct on paper but breaks under retries or duplicate delivery. Ask the skill to define idempotency keys, deduplication strategy, and safe reprocessing behavior for both action and compensation commands.

Ask for timeout ownership and recovery ownership

Many saga designs fail because no team owns timeout decisions or replay handling. Improve output by asking:

• who starts timeout clocks
• where timeout state is persisted
• who triggers compensation
• who can manually resume or terminate a stuck saga

This moves the result from theoretical pattern to operable system.

Request a failure-table, not just a flow

A strong iteration prompt is:

Revise the saga-orchestration design and add a table for each step covering success condition, transient failures, permanent failures, retries, timeout, compensation, and observability events.

That structure exposes weak or missing logic quickly.

Iterate after the first draft with production scenarios

After the initial result, test the design with concrete incidents:

• broker redelivery after orchestrator restart
• payment succeeds but acknowledgment is lost
• compensation command fails repeatedly
• downstream service responds after timeout
• manual operator retry on a half-completed saga

If the design cannot answer these scenarios clearly, keep iterating before coding.

Compare the output against your real constraints

The best way to improve the saga-orchestration skill in practice is to pressure-test it against your own system:

• message ordering guarantees
• storage consistency model
• SLA per service
• operational tooling
• audit/compliance requirements

A saga that looks elegant but ignores these constraints will create more incidents than it prevents.