AWS Step Functions
AWS LabsOfficialPublished by AWS Labs
- Skill
- Tool integration
- Cloud and DevOps
- Apache-2.0
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides comprehensive documentation and patterns for defining workflows in AWS Step Functions. It focuses on the Amazon States Language (ASL) and the use of JSONata for data transformation and logic. The skill covers the eight core state types, error handling, service integrations, and best practices for migrating from legacy JSONPath to JSONata. It also includes architectural patterns such as the Saga pattern, polling loops, and semaphore locks to help developers design robust distributed applications.
What it does
- Explains ASL structure and the eight available state types.
- Provides syntax guidance for JSONata expressions in state machines.
- Details error handling strategies using Retry and Catch blocks.
- Outlines patterns for AWS service integrations like Lambda, DynamoDB, and SQS.
- Offers architectural templates for common workflow challenges.
- Provides instructions for migrating existing state machines from JSONPath to JSONata.
When to use it
- When designing distributed applications or orchestrating microservices on AWS.
- When building data or machine learning pipelines that require automated processes.
- When implementing complex logic like retries, error handling, or branching in cloud workflows.
- When transitioning state machine definitions to use JSONata for data transformation.
Advantages
- Centralized reference for ASL syntax and JSONata expressions.
- Includes ready-to-use architectural patterns for common distributed system problems.
- Clear guidance on state input/output management and variable assignment.
- Provides comparative analysis between Standard and Express workflow types.
Usage examples
- “How do I implement a retry policy in a Task state?”
- The agent provides the syntax for the Retry field, explaining how to define error codes, interval seconds, and max attempts within an ASL Task state.
- “Show me how to use JSONata to transform output in a Pass state.”
- The agent provides a code example demonstrating the use of the Output field with JSONata expressions to format data dynamically.
- “What is the difference between Standard and Express workflows?”
- The agent returns a comparison table detailing differences in execution duration, throughput, pricing, and history retention.
- “How do I migrate my state machine from JSONPath to JSONata?”
- The agent explains the replacement of JSONPath fields like InputPath and ResultPath with the new Arguments and Output fields, and provides migration steps.
Install
Download the skill as a ZIP:
https://autogineer.com/agent-skills/awslabs/aws-step-functions/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip aws-step-functions.zip -d .agents/skills
Documentation by AWS Labs
AWS Step Functions
Overview
AWS Step Functions uses Amazon States Language (ASL) to define state machines as JSON. With AWS Step Functions, you can create workflows, also called State machines, to build distributed applications, automate processes, orchestrate microservices, and create data and machine learning pipelines.
This skill provides comprehensive guidance for writing state machines in ASL, covering:
ASL structure and JSONata expression syntax
Details on the eight available workflow states
The
$statesreserved variableWorkflow variables with
AssignError handling
AWS Service integration patterns
Example code for data transformation and architecture
Validation and testing of state machines
How to migrate from JSONPath to JSONata
When to Load Reference Files
Load the appropriate reference file based on what the user is working on:
ASL structure, state types, Task, Pass, Choice, Wait, Succeed, Fail, Parallel, Map → see references/asl-state-types.md
Error handling, troubleshooting, Retry, Catch, fallback, error codes, States.Timeout, States.ALL → see references/error-handling.md
Service integrations, Lambda invoke, DynamoDB, SNS, SQS, SDK integrations, Resource ARN, sync, async → see references/service-integrations.md
Migrating from JSONPath to JSONata, migration, JSONPath to JSONata, InputPath, Parameters, ResultSelector, ResultPath, OutputPath, intrinsic functions, Iterator, payload template → see references/migrating-from-jsonpath-to-jsonata.md
Validation, linting, testing, TestState, test state, mock, mocking, unit test, inspection level, DEBUG, TRACE, validate state, test in isolation → see references/validation-and-testing.md
Architecture patterns, examples, polling, saga, compensation, scatter-gather, semaphore, lock, human-in-the-loop, escalation, Express to Standard → see references/architecture-patterns.md
Data transformation, JSONata expressions, filtering, aggregation, string operations, $reduce, $lookup, $toMillis, $partition, $parse, $hash, $uuid → see references/transforming-data.md
State input/output, $states, Assign, Output, Arguments, variable scope, variable limits, evaluation order, passing data between states → see references/processing-state-inputs-and-outputs.md
Deployment, SAM, CloudFormation, IaC, DefinitionSubstitutions, X-Ray tracing, logging → see the aws-serverless-deployment skill or deploy-on-aws plugin
Quick Reference
Standard vs Express Workflows
| Standard | Express | |
|---|---|---|
| Max duration | 1 year | 5 minutes |
| Execution semantics | Exactly-once | At-least-once (async) / At-most-once (sync) |
| Execution history | Retained 90 days, queryable via API | CloudWatch Logs only |
| Max throughput | 2,000 exec/sec | 100,000 exec/sec |
| Pricing model | Per state transition | Per execution count + duration |
.sync / .waitForTaskToken | Supported | Not supported |
| Best for | Auditable, non-idempotent operations | High-volume, idempotent event processing |
Choose Standard for: payment processing, order fulfillment, compliance workflows, anything that must never execute twice.
Choose Express for: IoT data ingestion, streaming transformations, mobile backends, high-throughput short-lived processing.
Setting the State Machine Query Language
JSONata is the modern, preferred way to reference and transform data in ASL. It replaces the five JSONPath I/O fields (InputPath, Parameters, ResultSelector, ResultPath, OutputPath) with just two: Arguments (inputs) and Output.
Enable at the top level to apply to all states:
{ "QueryLanguage": "JSONata", "StartAt": "...", "States": {...} }Or per-state to migrate from JSONPath incrementally:
{ "Type": "Task", "QueryLanguage": "JSONata", ... }JSONPath is still supported and is the default if QueryLanguage is omitted — existing state machines do not need to be migrated.
Best Practices
Set
"QueryLanguage": "JSONata"at the top level for new state machines unless the user wants to use JSONPathKeep
Outputminimal — only include what the state immediately after the current state needsUse
Assignto store variables needed in later states instead of threading it through OutputUse
$states.inputto reference original state inputRemember:
AssignandOutputare evaluated in parallel — variable assignments inAssignare NOT available inOutputof the same stateAll JSONata expressions must produce a defined value —
$data.nonExistentFieldthrowsStates.QueryEvaluationErrorUse
$states.context.Execution.Inputto access the original workflow input from any stateSave state machine definitions with
.asl.jsonextension when working outside the consolePrefer the optimized Lambda integration (
arn:aws:states:::lambda:invoke) over the SDK integration
Troubleshooting
Common Errors
States.QueryEvaluationError— JSONata expression failed. Check for type errors, undefined fields, or out-of-range values.Mixing JSONPath fields with JSONata fields in the same state.
Using
$or$$at the top level of a JSONata expression — use$states.inputinstead.Forgetting
{% %}delimiters around JSONata expressions — the string will be treated as a literal.Assigning variables in
Assignand expecting them inOutputof the same state — new values only take effect in the next state.Reference references/validation-and-testing.md and references/error-handling.md for detailed troubleshooting information.
Resources
Files
- ATTRIBUTION.mdAdded by AutoGineer922 B
- LICENSELicence file added by AutoGineer9.9 KiB
- NOTICELicence file added by AutoGineer89 B
- SKILL.md7.4 KiB
- examples/compensation-saga-pattern.asl.json3.5 KiB
- examples/express-standard-handoff.asl.json2.2 KiB
- examples/human-in-the-loop-with-timeout-escalation.asl.json3.4 KiB
- examples/nested-map-parallel-structures.asl.json2.0 KiB
- examples/polling-loop-wait-check-choice.asl.json2.0 KiB
- examples/scatter-gather-with-partial-results.asl.json2.2 KiB
- examples/semaphore-concurrency-lock.asl.json3.3 KiB
- references/architecture-patterns.md3.8 KiB
- references/asl-state-types.md12.4 KiB
- references/error-handling.md6.9 KiB
- references/migrating-from-jsonpath-to-jsonata.md13.3 KiB
- references/processing-state-inputs-and-outputs.md11.2 KiB
- references/service-integrations.md6.4 KiB
- references/transforming-data.md6.2 KiB
- references/validation-and-testing.md11.0 KiB
references/architecture-patterns.md
Architecture Patterns (JSONata Mode)
Polling Loop (Wait → Check → Choice)
Some AWS operations and user-defined tasks are asynchronous. The states pattern is: Start Task → initial wait (what is the expected time it takes to complete the task?) → call describe/status API → check result → short wait → loop back.
See examples/polling-loop-wait-check-choice.asl.json
Compensation / Saga Pattern
Step Functions has no built-in rollback. The saga pattern chains compensating actions in reverse order. Each forward step has a Catch that records which step failed, then routes to the appropriate compensation entry point.
See examples/compensation-saga-pattern.asl.json
Compensation chain: ReserveInventory fails → OrderFailed. ChargePayment fails → ReleaseInventory → OrderFailed. ShipOrder fails → RefundPayment → ReleaseInventory → OrderFailed. Each Catch records $failedStep and $errorInfo. Compensation states use variables from forward steps ($chargeId, $reservedQty) to know what to undo.
Nested Map / Parallel Structures
Map and Parallel states can be nested in any order to create multiple layers. The key constraint is understanding variable scope and data flow at each nesting boundary.
See examples/nested-map-parallel-structures.asl.json
See processing-state-inputs-and-outputs.md for details about variable scopes
Scatter-Gather with Partial Results
When calling unreliable external APIs per-item, use ToleratedFailurePercentage on a Map to continue with whatever succeeded, then post-process the results to separate successes from failures. Failed iterations return objects with Error and Cause fields.
See examples/scatter-gather-with-partial-results.asl.json
Key elements:
ToleratedFailurePercentage: 100lets the Map complete even if every item fails. Lower the threshold to bail out early.Filter on
$exists(Error)to separate failed from successful iterations.Guard filtered results with the
$type/$exists/[]pattern — JSONata returns a single object (not a 1-element array) when exactly one item matches, and undefined when nothing matches.
Semaphore / Concurrency Lock
Step Functions has no native mutual exclusion. Use DynamoDB conditional writes as a distributed lock when only one execution should process a given resource at a time. Pattern: acquire lock → do work → release lock, with Catch ensuring release on failure.
See examples/semaphore-concurrency-lock.asl.json
Key elements:
ConditionExpressionwithattribute_not_existsensures only one writer wins. TheexpiresAtcheck provides stale-lock recovery if an execution crashes without releasing.executionIdon the lock item letsReleaseLockconditionally delete only its own lock.Retry on
ConditionalCheckFailedExceptionacts as a spin-wait. TuneMaxAttemptsandIntervalSecondsbased on expected hold time.Catch on
DoProtectedWorkroutes toReleaseLockso the lock is always released. After releasing,CheckWorkResultre-raises the error path.Set
expiresAtto a reasonable TTL (here 15 min). Use a DynamoDB TTL attribute to auto-clean expired locks.
Human-in-the-Loop with Timeout Escalation
Chain multiple .waitForTaskToken states with States.Timeout catches to build escalation: primary approver → manager → auto-reject.
See examples/human-in-the-loop-with-timeout-escalation.asl.json
Express → Standard Handoff
Express workflows are more cost-effective for high volume State Machine Invocations, but don't support callbacks or long waits. Standard workflows handle those but cost per state transition. Use Express for fast, high-volume ingest and kick off a Standard execution for the long-running tail.
See examples/express-standard-handoff.asl.json
Requirements and compatibility
Written for: Claude Code
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Claude Code frontmatter
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- AWS Labs
- Publisher
- AWS Labs (Official)
- Source
- awslabs/agent-plugins · plugins/aws-serverless/skills/aws-step-functions · commit fbefb37
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- NOTICE (added by AutoGineer from NOTICE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by AWS Labs or AWS Labs.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download aws-step-functions.zip