AWS Advisor
diegosouzapw/awesome-omni-skills
AWS Advisor workflow skill. An agent skill from diegosouzapw/awesome-omni-skills.
Authors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail).
$ npx skills add aws/agent-toolkit-for-aws --skill aws-step-functions -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aws/agent-toolkit-for-aws aws-step-functions --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/specialized-skills/serverless-skills/aws-step-functions .claude/skills/aws-step-functions && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "aws-step-functions" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/serverless-skills/aws-step-functions into .claude/skills/aws-step-functions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-step-functions", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/serverless-skills/aws-step-functionsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aws/agent-toolkit-for-aws --skill aws-step-functions -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aws/agent-toolkit-for-aws aws-step-functions --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/specialized-skills/serverless-skills/aws-step-functions .agents/skills/aws-step-functions && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "aws-step-functions" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/serverless-skills/aws-step-functions into .agents/skills/aws-step-functions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-step-functions", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws/agent-toolkit-for-aws --skill aws-step-functions -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aws/agent-toolkit-for-aws aws-step-functions --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/specialized-skills/serverless-skills/aws-step-functions .cursor/skills/aws-step-functions && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "aws-step-functions" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/serverless-skills/aws-step-functions into .cursor/skills/aws-step-functions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-step-functions", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aws/agent-toolkit-for-aws.git --path skills/specialized-skills/serverless-skills/aws-step-functions--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aws/agent-toolkit-for-aws --skill aws-step-functions -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aws/agent-toolkit-for-aws aws-step-functions --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/specialized-skills/serverless-skills/aws-step-functions .gemini/skills/aws-step-functions && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "aws-step-functions" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/serverless-skills/aws-step-functions into .gemini/skills/aws-step-functions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-step-functions", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aws/agent-toolkit-for-aws aws-step-functionsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aws/agent-toolkit-for-aws --skill aws-step-functions -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/specialized-skills/serverless-skills/aws-step-functions .github/skills/aws-step-functions && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "aws-step-functions" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/serverless-skills/aws-step-functions into .github/skills/aws-step-functions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-step-functions", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aws/agent-toolkit-for-aws --skill aws-step-functions -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aws/agent-toolkit-for-aws aws-step-functions --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aws/agent-toolkit-for-aws.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/specialized-skills/serverless-skills/aws-step-functions .opencode/skills/aws-step-functions && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "aws-step-functions" agent skill from https://github.com/aws/agent-toolkit-for-aws/tree/main/skills/specialized-skills/serverless-skills/aws-step-functions into .opencode/skills/aws-step-functions/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "aws-step-functions", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
aws-step-functionsAuthors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail).
AWS Step Functions is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Authors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail). Covers ASL syntax, JSONata data transformation and variables, Retry/Catch error handling, service integrations (.sync, waitForTaskToken callbacks), Distributed Map for large-scale S3/CSV processing, saga/compensation patterns, Standard vs Express workflow choice, TestState API unit testing, and migrating state machines…
Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including reference files and assets (for example `assets/compensation-saga-pattern.asl.json`, `assets/express-standard-handoff.asl.json` and `assets/human-in-the-loop-with-timeout-escalation.asl.json`).
It sits in Backend & APIs, covering Serverless, Unit testing and Microservices. It works with Amazon Web Services, AWS Lambda and Amazon DynamoDB. The repository describes itself as: Official, AWS-supported MCP servers, skills, and plugins to help AI agents build on AWS. The licence is Apache-2.0.
Read from SKILL.md and the folder at commit 188af2f. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
awsFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
docs.aws.amazon.comstates-language.netdocs.jsonata.orgFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
AWS Step Functions loads about 3.4k tokens when it runs, and up to ~20k if it reads all its reference files. Until then it costs about 231 tokens; SKILL.md has 1,411 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from aws/agent-toolkit-for-aws at commit 188af2f, republished under its Apache-2.0 licence (© aws). 1,411 words, ~3,365 tokens.
.claude/skills/aws-step-functions/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.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:
$states reserved variableAssignThe AWS MCP server is recommended for sandboxed execution and audit logging when following this skill, but all steps use AWS CLI syntax and work without it.
Load the appropriate reference file based on what the user is working on:
references/asl-state-types.mdreferences/error-handling.mdreferences/service-integrations.mdreferences/migrating-from-jsonpath-to-jsonata.mdreferences/validation-and-testing.mdreferences/architecture-patterns.mdreferences/transforming-data.mdreferences/processing-state-inputs-and-outputs.md| 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.
When recommending Express, the single limitation you must always state — even for fire-and-forget / high-throughput pipelines — is that Express does NOT support
.syncor.waitForTaskToken(no callbacks, no nested.syncwaits, no human-approval or job-completion waits). Also note: 5-minute max duration, no queryable execution history (CloudWatch Logs only), and at-least-once (async) / at-most-once (sync) execution — so non-idempotent work can run twice. If any of these matter, choose Standard (exactly-once, up to 1 year, full history).
JSONata is the 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 supported and is the default if QueryLanguage is omitted — existing state machines do not need to be migrated.
Field mapping (JSONPath → JSONata):
| JSONPath field | JSONata equivalent |
|---|---|
Parameters (keys use key.$) | Arguments — drop the .$ suffix and wrap each value in {% %} |
ResultSelector and OutputPath | Output (reference the raw result via $states.result) |
ResultPath | Assign (preferred) or Output |
InputPath | not needed — reference $states.input directly |
A state uses one query language, not both. Never mix JSONPath fields (
InputPath/Parameters/ResultSelector/ResultPath/OutputPath) with JSONata fields (Arguments/Output) in the same state — this is the most common migration error. Seereferences/migrating-from-jsonpath-to-jsonata.mdfor full details.
Within a single state, Assign and Output are evaluated at the same time — in parallel — both reading the same data (the state input plus the task result). They are NOT evaluated one after the other. Because they run together, a variable you set in Assign is not visible in that same state's Output: there is no ordering in which Output could observe the just-assigned value. The assigned value becomes available only to subsequent states.
So if you set a variable in Assign and reference it in the same state's Output, you get the old/undefined value — not because Output runs "before" Assign, but because both evaluate concurrently from the same snapshot. To use the value immediately, reference it in the next state (variables persist across states); to shape the current state's output from the task result, use $states.result directly in Output.
Test a single state without deploying the state machine or calling the real service using the TestState API (aws stepfunctions test-state) with --mock. A complete answer covers all four points:
--mock result MUST match the target AWS service's API response schema exactly (field names are case-sensitive). For a Lambda invoke Task that is StatusCode and Payload: --mock '{"result":"{\"StatusCode\":200,\"Payload\":{...}}"}'.--inspection-level): INFO (default — output, status, nextState), DEBUG (adds data flow: afterArguments, result, variables — use to debug JSONata/data flow), TRACE (adds raw HTTP request/response, for HTTP Task)..sync and .waitForTaskToken integrations still require a mock — for .sync, mock the polling API (e.g. DescribeExecution, not the initial call); for .waitForTaskToken, also pass --context '{"Task":{"Token":"..."}}'.See references/validation-and-testing.md for per-service mock structures and error/retry/Map/Parallel testing.
"QueryLanguage": "JSONata" at the top level for new state machines unless the user wants to use JSONPathOutput minimal — only include what the state immediately after the current state needsAssign to store variables needed in later states instead of threading it through Output$states.input to reference original state inputAssign and Output are evaluated in parallel from the state's entry data, NOT sequentially — a variable set in Assign is therefore NOT visible in the same state's Output (which still sees the pre-Assign values); the new value takes effect only in the next state.$data.nonExistentField throws States.QueryEvaluationError$states.context.Execution.Input to access the original workflow input from any state.asl.json extension when working outside the consolearn:aws:states:::lambda:invoke) over the SDK integrationStates.QueryEvaluationError — JSONata expression failed. Check for type errors, undefined fields, or out-of-range values.$ or $$ at the top level of a JSONata expression — use $states.input instead.{% %} delimiters around JSONata expressions — the string will be treated as a literal.Assign and expecting them in Output of the same state — new values only take effect in the next state.*FullAccess policies and service:* wildcards.KmsMasterKeyId) on SQS queues and SNS topics, and TLS for HTTP Tasks..waitForTaskToken token is a credential — treat it as a secret. Do not place PII, financial data, or secrets in SQS/SNS message bodies or notifications; pass a reference ID and have recipients look up details through an authorized channel.$exists() and $type(), and route invalid input to a Fail state so malformed data never reaches downstream states. Protect downstream services from bursts by setting MaxConcurrency on Map states and throttling upstream (StartExecution rate limits or EventBridge).Credentials field to assume a role in another account, include condition keys such as aws:SourceArn or aws:SourceAccount in the target role's trust policy to prevent unintended assumption.ALL or ERROR; required for Express workflows, which have no queryable execution history), enable CloudTrail to audit Step Functions API calls, and set CloudWatch Alarms on execution failures. Always encrypt the execution log group with a customer-managed KMS key, since state input/output routinely flows through execution logs.© aws, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 15 other files (references, assets) in skills/specialized-skills/serverless-skills/aws-step-functions of aws/agent-toolkit-for-aws.
Open the folder on GitHubat commit 188af2f
AWS Step Functions next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AWS Step Functions this skillaws/agent-toolkit-for-aws | 2.8k | — | ~3.4k | Automated safety check: Pass | Apache-2.0 | |
| AWS Advisordiegosouzapw/awesome-omni-skills | 159 | — | ~4.3k | Automated safety check: Pass | MIT | |
| AWS Serverless Edazxkane/aws-skills | 367 | 4 repos | ~3.2k | Automated safety check: Pass | MIT | |
| AWS Solution Architectalirezarezvani/claude-skills | 28k | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| AWS Serverlessdavila7/claude-code-templates | 32k | 8 repos | ~2k | Automated safety check: Pass | MIT | |
| AWS Lambda Durable Functionsawslabs/agent-plugins | 915 | — | ~2.3k | Automated safety check: Pass | Apache-2.0 |
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Categories
Authors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail). AWS Step Functions is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Authors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail).
AWS Step Functions fits situations like: the user is building; migrating a Step Functions state machine; orchestrating multi-step workflows with branching; human-approval callbacks.
Run `npx skills add aws/agent-toolkit-for-aws --skill aws-step-functions -a claude-code`. Or copy the skill folder (skills/specialized-skills/serverless-skills/aws-step-functions in aws/agent-toolkit-for-aws) into .claude/skills/aws-step-functions in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aws/agent-toolkit-for-aws --skill aws-step-functions -a codex`. Or copy the skill folder (skills/specialized-skills/serverless-skills/aws-step-functions in aws/agent-toolkit-for-aws) into .agents/skills/aws-step-functions in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aws/agent-toolkit-for-aws --skill aws-step-functions -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/aws-step-functions, .gemini/skills/aws-step-functions, .github/skills/aws-step-functions and .opencode/skills/aws-step-functions in your project.
Going by SKILL.md and its folder, AWS Step Functions needs the command-line tools its instructions call (aws).
SKILL.md names 3 domains. As links in the text: docs.aws.amazon.com, states-language.net and docs.jsonata.org. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
AWS Step Functions is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.4k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 17k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with AWS Step Functions: AWS Advisor (diegosouzapw/awesome-omni-skills, 159 stars), AWS Serverless Eda (zxkane/aws-skills, 367 stars), AWS Solution Architect (alirezarezvani/claude-skills, 28k stars) and AWS Serverless (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aws (a GitHub organization, an official publisher) maintains it in aws/agent-toolkit-for-aws, which has 2,825 GitHub stars. The repository holds 138 skills in this directory. The repository was last updated on October 7, 2026.
Source: aws/agent-toolkit-for-aws on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.