Agent skill · DevOps & Cloud

aws-step-functions

Build workflows with AWS Step Functions state machines using the JSONata query language. Covers Amazon States Language (ASL) structure, state types, variables, data transformation, error handling, AWS service integration, and migrating from the JSONPath to the JSONata query language.

Amazon Web Services - Labs12,649★ · +18/wk · 2 repos on radarProfile →
claude-codeApache-2.0
Install
npx skills add awslabs/agent-plugins --skill aws-step-functions --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 16
SKILL.md size: 7 KB
Bundled scripts: none
Path: plugins/aws-serverless/skills/aws-step-functions/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 850
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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 `$states` reserved variable - Workflow variables with `Assign` - Error 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](references/asl-state-types.md) - **Error handling**, **troubleshooting**, **Retry**, **Catch**, **fallback**, **error codes**, **States.Timeout**, **States.A

What's inside
Steps it walks through
  1. Overview
  2. When to Load Reference Files
  3. Quick Reference
  4. Standard vs Express Workflows
  5. Setting the State Machine Query Language
  6. Best Practices
  7. Troubleshooting
  8. Common Errors
  9. Resources
Ships with 15 files
  • examples/compensation-saga-pattern.asl.json
  • examples/express-standard-handoff.asl.json
  • examples/human-in-the-loop-with-timeout-escalation.asl.json
  • examples/nested-map-parallel-structures.asl.json
  • examples/polling-loop-wait-check-choice.asl.json
  • examples/scatter-gather-with-partial-results.asl.json
  • examples/semaphore-concurrency-lock.asl.json
  • references/architecture-patterns.md
  • references/asl-state-types.md
  • references/error-handling.md
  • references/migrating-from-jsonpath-to-jsonata.md
  • references/processing-state-inputs-and-outputs.md
  • references/service-integrations.md
  • references/transforming-data.md
  • references/validation-and-testing.md
More from agent-plugins
All skills →
About this skill
What does the aws-step-functions skill do?

Build workflows with AWS Step Functions state machines using the JSONata query language. Covers Amazon States Language (ASL) structure, state types, variables, data transformation, error handling, AWS service integration, and migrating from the JSONPath to the JSONata query language.

How do I install it?

Run `npx skills add awslabs/agent-plugins --skill aws-step-functions --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From awslabs/agent-plugins, a repository with 850 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going