Official agent skill

Processing S3 Uploads With Step Functions

by aws in aws/agent-toolkit-for-aws

Deploy an event-driven workflow that routes S3 uploads to either Lambda or Fargate via Step Functions based on file size.

OfficialApache-2.0Auto-check passedBackend & APIs

Install Processing S3 Uploads With Step Functions

skills CLI
$ npx skills add aws/agent-toolkit-for-aws --skill processing-s3-uploads-with-step-functions -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aws/agent-toolkit-for-aws processing-s3-uploads-with-step-functions --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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/processing-s3-uploads-with-step-functions .claude/skills/processing-s3-uploads-with-step-functions && rm -rf skills-src

Use ~/.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/

Facts

Skill name
processing-s3-uploads-with-step-functions
GitHub stars
2.8k
Token cost
~4k tokens
SKILL.md length
1,563 words
Files
12 (incl. scripts, references)
Skills in repo
138
Repo updated
First seen
Licence
Apache-2.0

At a glance

Deploy an event-driven workflow that routes S3 uploads to either Lambda or Fargate via Step Functions based on file size.

  • Works in 12 steps: Verify Dependencies → Retrieve AWS Account ID → Get the Default VPC and Networking → …
  • A Step Functions state machine when objects are uploaded to S3
  • SKILL.md covers Overview, Prerequisites, Parameters and Procedures, plus 4 more sections
  • Runs Python scripts from its folder; calls aws, docker and python3

What it does

Processing S3 Uploads With Step Functions is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Deploy an event-driven workflow that routes S3 uploads to either Lambda or Fargate via Step Functions based on file size. Uses EventBridge to trigger a Step Functions state machine when objects are uploaded to S3. Small files are processed by Lambda, large files by a Fargate task. Includes VPC, ECR repository, ECS cluster, and scoped IAM roles. Trigger keywords: Step Functions, Fargate, Lambda, S3 event, EventBridge, ECS, ECR, file processing, workflow orchestration, serverless.

Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 13 other files, including scripts and reference files (for example `references/ecs-task-definition.md`, `references/iam-roles.md` and `scripts/ecs-trust-policy.json`).

It sits in Backend & APIs, covering File uploads and storage, Serverless and Event-driven systems. It works with Amazon Web Services, AWS Lambda and Amazon S3. 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.

When your agent uses it

  • A Step Functions state machine when objects are uploaded to S3
  • Keywords: Step Functions
  • File processing
  • Workflow orchestration

Example prompts

  • “/processing-s3-uploads-with-step-functions”

Requirements

  • Python 3
  • Docker

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Verify Dependencies
  2. Retrieve AWS Account ID
  3. Get the Default VPC and Networking
  4. Create the ECR Repository
  5. Build and Push the Container Image
  6. Create IAM Roles
  7. Create the Lambda Function
  8. Create the CloudWatch Log Group
  9. Create the ECS Cluster and Task Definition
  10. Create the S3 Bucket with EventBridge Notifications
  11. Create the Step Functions State Machine
  12. Create the EventBridge Rule

What it can do on your machine

Read from SKILL.md and the folder at commit bd49cc8. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Ships 9 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • aws
    • docker
    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • docs.aws.amazon.com
    • docs.docker.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Processing S3 Uploads With Step Functions loads about 4k tokens when it runs, and up to ~5.4k if it reads all its reference files. Until then it costs about 131 tokens; SKILL.md has 1,563 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~131
When it runs · the whole SKILL.md, loaded when a task matches
~4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~5.4k

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.

Safety

Auto-check passed

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); the scripts in this folder are not scanned.

SKILL.md

The full file from aws/agent-toolkit-for-aws at commit bd49cc8, republished under its Apache-2.0 licence (© aws). 1,563 words, ~3,963 tokens.

Download SKILL.mdSave it as .claude/skills/processing-s3-uploads-with-step-functions/SKILL.md (or your agent's skills folder). This skill also uses 11 other files; get the full folder from GitHub.
name
processing-s3-uploads-with-step-functions
description
Deploy an event-driven workflow that routes S3 uploads to either Lambda or Fargate via Step Functions based on file size. Uses EventBridge to trigger a Step Functions state machine when objects are uploaded to S3. Small files are processed by Lambda, large files by a Fargate task. Includes VPC, ECR repository, ECS cluster, and scoped IAM roles. Trigger keywords: Step Functions, Fargate, Lambda, S3 event, EventBridge, ECS, ECR, file processing, workflow orchestration, serverless.
version
1

Step Functions Workflow: Route S3 Uploads to Lambda or Fargate

Overview

This skill deploys an event-driven workflow using AWS CLI. When a file is uploaded to an S3 bucket, EventBridge triggers a Step Functions state machine. The state machine checks the file size and routes processing to either a Lambda function (files ≤ 6 MB) or a Fargate task (files > 6 MB).

The architecture includes:

  • An S3 bucket with EventBridge notifications enabled
  • An EventBridge rule that triggers Step Functions on S3 object creation
  • A Step Functions state machine with a Choice state for routing
  • A Lambda function for processing small files
  • An ECS Fargate task for processing large files
  • A VPC with two subnets, internet gateway, and security group
  • An ECR repository for the Fargate container image
  • Scoped IAM roles for Lambda, Step Functions, and ECS tasks

Use this skill when:

  • You need to process S3 uploads with different compute based on file size
  • You want a serverless workflow that can handle both small and large files
  • You need Step Functions orchestration with Lambda and Fargate

Do not use this skill when:

  • All files are small enough for Lambda (use S3 → Lambda directly)
  • You need real-time streaming (use Kinesis)
  • You don't need file-size-based routing

Prerequisites

  1. AWS CLI v2 — Installed and configured. Verify with aws sts get-caller-identity.
  2. Python 3.12 — For the Lambda function runtime.
  3. Docker — For building and pushing the Fargate container image.

Parameters

  • bucket_name (required): Name for the S3 bucket (globally unique, lowercase, 3-63 characters)
  • region (required): AWS region for all resources
  • ecr_repo_name (required): Name for the ECR repository
  • state_machine_name (required): Name for the Step Functions state machine
  • kms_key_arn (optional): ARN of a KMS key for CloudWatch Logs encryption. If not provided, create one with aws kms create-key --description "Key for CloudWatch Logs encryption" --region {region}

Constraints for parameter acquisition:

  • You MUST ask for all required parameters upfront in a single prompt
  • You MUST support multiple input methods (direct input, file path, URL)
  • You MUST confirm successful acquisition of all parameters before proceeding
  • You MUST validate that bucket_name follows S3 naming rules

Procedures

Step 0: Verify Dependencies

Constraints:

  • You MUST verify the following tools are available: aws-cli, python3 (3.12+), docker
  • You MUST inform the user about any missing tools with a clear message
  • You MUST ask if the user wants to proceed despite missing tools
  • You MUST respect the customer's decision to abort at any point
  • You MUST explain to the customer what step is being executed, why, and which tool is being called
Step 1: Retrieve AWS Account ID

Constraints:

  • You MUST retrieve the account ID with: aws sts get-caller-identity --query 'Account' --output text
  • You MUST store the result as {account_id} for use in all subsequent steps
  • You MUST abort if credentials are not configured
Step 2: Get the Default VPC and Networking

Constraints:

  • You MUST retrieve the default VPC ID with: aws ec2 describe-vpcs --filters Name=isDefault,Values=true --query 'Vpcs[0].VpcId' --output text --region {region}
  • If no default VPC exists, inform the user they must create one with aws ec2 create-default-vpc --region {region} or provide a VPC ID manually
  • You MUST retrieve two subnet IDs from the default VPC: aws ec2 describe-subnets --filters Name=vpc-id,Values={vpc_id} --query 'Subnets[0:2].SubnetId' --output text --region {region}
  • You MUST create a security group in the default VPC: aws ec2 create-security-group --group-name fargate-sg --description "Security group for Fargate tasks" --vpc-id {vpc_id} --region {region}
  • You MUST configure security group egress rules to allow only HTTPS and DNS outbound. First revoke the default allow-all egress rule: aws ec2 revoke-security-group-egress --group-id {sg_id} --ip-permissions IpProtocol=-1,IpRanges='[{CidrIp=0.0.0.0/0}]' --region {region} Then add scoped rules: aws ec2 authorize-security-group-egress --group-id {sg_id} --protocol tcp --port 443 --cidr 0.0.0.0/0 --region {region} and aws ec2 authorize-security-group-egress --group-id {sg_id} --protocol udp --port 53 --cidr 0.0.0.0/0 --region {region}
  • You MUST recommend VPC endpoints for S3 and CloudWatch Logs for production workloads to avoid internet-routed traffic and eliminate the need for broad egress rules
  • You MUST capture {vpc_id}, {subnet1_id}, {subnet2_id}, and {sg_id} for use in later steps
Step 3: Create the ECR Repository

Constraints:

  • You MUST create the repository with: aws ecr create-repository --repository-name {ecr_repo_name} --region {region}
  • You MUST capture the repositoryUri from the response
Step 4: Build and Push the Container Image

Constraints:

  • You MUST verify Docker is installed by running docker --version. If Docker is not installed, instruct the user to install it from https://docs.docker.com/get-docker/ and abort until it is available

  • You MUST authenticate Docker with ECR: aws ecr get-login-password --region {region} | docker login --username AWS --password-stdin {account_id}.dkr.ecr.{region}.amazonaws.com

  • The Dockerfile and processor code are in scripts/Dockerfile and scripts/fargate_processor.py

  • You MUST build and push the image from the scripts directory:

    cd scripts
    docker build --platform linux/amd64 -t {ecr_repo_name} .
    docker tag {ecr_repo_name}:latest {account_id}.dkr.ecr.{region}.amazonaws.com/{ecr_repo_name}:latest
    docker push {account_id}.dkr.ecr.{region}.amazonaws.com/{ecr_repo_name}:latest
    cd ..
Step 5: Create IAM Roles

Follow the detailed instructions in references/iam-roles.md to create all IAM roles (Lambda, ECS task execution, ECS task, Step Functions, and EventBridge roles).

  • You MUST wait at least 10 seconds for IAM role propagation
Step 6: Create the Lambda Function

Constraints:

  • The function code is in scripts/lambda_function.py

  • You MUST be in the skill root directory before packaging and creating the function

  • You MUST package it with: python3 -c "import zipfile,io; z=io.BytesIO(); f=zipfile.ZipFile(z,'w'); f.writestr('lambda_function.py', open('scripts/lambda_function.py').read()); f.close(); open('/tmp/lambda_function.zip','wb').write(z.getvalue())"

  • You MUST create the function with:

    aws lambda create-function \
        --function-name sfn-file-processor \
        --runtime python3.12 \
        --handler lambda_function.lambda_handler \
        --role arn:aws:iam::{account_id}:role/sfn-lambda-role \
        --zip-file fileb:///tmp/lambda_function.zip \
        --timeout 60 \
        --architectures x86_64 \
        --region {region}
  • You MUST verify the function was created with: aws lambda get-function --function-name sfn-file-processor --region {region}

Step 7: Create the CloudWatch Log Group

Constraints:

  • You MUST create the log group for Fargate: aws logs create-log-group --log-group-name /StepFunctionFargateTask --region {region}
  • You MUST encrypt the log group with a KMS key: aws logs associate-kms-key --log-group-name /StepFunctionFargateTask --kms-key-arn {kms_key_arn} --region {region}
Step 8: Create the ECS Cluster and Task Definition

Follow the detailed instructions in references/ecs-task-definition.md to create the ECS cluster and register the Fargate task definition.

  • You MUST capture the task definition ARN from the response
Step 9: Create the S3 Bucket with EventBridge Notifications

Constraints:

  • You MUST create the bucket with: aws s3api create-bucket --bucket {bucket_name} --region {region} --create-bucket-configuration LocationConstraint={region}
  • You MUST NOT include --create-bucket-configuration if region is us-east-1
  • You MUST enable EventBridge notifications on the bucket: aws s3api put-bucket-notification-configuration --bucket {bucket_name} --notification-configuration '{"EventBridgeConfiguration": {}}' --region {region}
  • You MUST enable default encryption on the bucket: aws s3api put-bucket-encryption --bucket {bucket_name} --server-side-encryption-configuration '{"Rules":[{"ApplyServerSideEncryptionByDefault":{"SSEAlgorithm":"aws:kms"}}]}' --region {region}
Show full SKILL.md (644 more words)Show less
Step 10: Create the Step Functions State Machine

Constraints:

  • The state machine definition is in scripts/statemachine.asl.json

  • You MUST create a working copy and replace all placeholders:

    sed -e 's|${LambdaFunction}|arn:aws:lambda:{region}:{account_id}:function:sfn-file-processor|g' \
        -e 's|${Cluster}|arn:aws:ecs:{region}:{account_id}:cluster/sfn-cluster|g' \
        -e 's|${TaskDefinition}|{task_definition_arn}|g' \
        -e 's|${Subnet1}|{subnet1_id}|g' \
        -e 's|${Subnet2}|{subnet2_id}|g' \
        -e 's|${SecurityGroup}|{sg_id}|g' \
        scripts/statemachine.asl.json > /tmp/statemachine.asl.json
  • You MUST create the state machine with:

    aws stepfunctions create-state-machine \
        --name {state_machine_name} \
        --definition file:///tmp/statemachine.asl.json \
        --role-arn arn:aws:iam::{account_id}:role/sfn-state-machine-role \
        --type STANDARD \
        --region {region}
  • You MUST capture the stateMachineArn from the response

Step 11: Create the EventBridge Rule

Constraints:

  • You MUST create the EventBridge rule to trigger on S3 object creation:

    aws events put-rule \
        --name s3-to-stepfunctions \
        --event-pattern '{
          "source": ["aws.s3"],
          "detail-type": ["Object Created"],
          "detail": {
            "bucket": {
              "name": ["{bucket_name}"]
            }
          }
        }' \
        --region {region}
  • You MUST add the state machine as a target:

    aws events put-targets \
        --rule s3-to-stepfunctions \
        --targets '[{
          "Id": "StepFunctionsTarget",
          "Arn": "{state_machine_arn}",
          "RoleArn": "arn:aws:iam::{account_id}:role/sfn-eventbridge-role"
        }]' \
        --region {region}
Step 12: Configure Monitoring

Constraints:

  • You MUST create a Dead Letter Queue for failed EventBridge invocations: aws sqs create-queue --queue-name s3-to-stepfunctions-dlq --region {region}

  • You MUST update the EventBridge target to attach the DLQ:

    aws events put-targets \
        --rule s3-to-stepfunctions \
        --targets '[{
          "Id": "StepFunctionsTarget",
          "Arn": "{state_machine_arn}",
          "RoleArn": "arn:aws:iam::{account_id}:role/sfn-eventbridge-role",
          "DeadLetterConfig": {
            "Arn": "arn:aws:sqs:{region}:{account_id}:s3-to-stepfunctions-dlq"
          }
        }]' \
        --region {region}
  • You MUST create a CloudWatch alarm for Step Functions execution failures: aws cloudwatch put-metric-alarm --alarm-name sfn-execution-failures --metric-name ExecutionsFailed --namespace AWS/States --statistic Sum --period 300 --threshold 1 --comparison-operator GreaterThanOrEqualToThreshold --evaluation-periods 1 --dimensions Name=StateMachineArn,Value={state_machine_arn} --region {region}

Step 13: Validate

Constraints:

  • You MUST test with a small file (< 6 MB) to verify Lambda processing:

    echo 'test data' > /tmp/small-file.txt
    aws s3 cp /tmp/small-file.txt s3://{bucket_name}/small-file.txt --region {region}
  • You MUST wait 15 seconds then check the Step Functions execution: aws stepfunctions list-executions --state-machine-arn {state_machine_arn} --region {region}

  • You MUST verify the execution succeeded and routed to Lambda

  • You MUST provide a summary of all created resources including: VPC ID, subnet IDs, security group ID, ECR repo URI, ECS cluster ARN, task definition ARN, Lambda function ARN, state machine ARN, bucket name, and EventBridge rule name

Troubleshooting

EventBridge rule not triggering
  • Verify EventBridge notifications are enabled on the bucket: aws s3api get-bucket-notification-configuration --bucket {bucket_name}
  • Verify the rule exists: aws events describe-rule --name s3-to-stepfunctions --region {region}
  • Check that the target has the correct state machine ARN and role
Step Functions execution fails at Fargate task
  • Verify the container image exists in ECR: aws ecr describe-images --repository-name {ecr_repo_name} --region {region}
  • Check that the subnets have internet access (route table with IGW)
  • Verify the security group allows outbound traffic
  • Check CloudWatch Logs at /StepFunctionFargateTask
Lambda invocation fails
  • Check CloudWatch Logs: aws logs tail /aws/lambda/sfn-file-processor --region {region}
  • Verify the Step Functions role has lambda:InvokeFunction permission
IAM PassRole errors
  • The Step Functions role must have iam:PassRole for both the ECS execution role and task role ARNs
Fargate task stuck in PROVISIONING
  • Verify the subnets have auto-assign public IP enabled
  • Verify the internet gateway is attached and route table has 0.0.0.0/0 route

Security Considerations

  • Fargate tasks with public IPs are exposed to the internet. Revoke the default allow-all egress rule and configure scoped egress: aws ec2 revoke-security-group-egress --group-id {sg_id} --ip-permissions IpProtocol=-1,IpRanges='[{CidrIp=0.0.0.0/0}]' then add aws ec2 authorize-security-group-egress --group-id {sg_id} --protocol tcp --port 443 --cidr 0.0.0.0/0 and aws ec2 authorize-security-group-egress --group-id {sg_id} --protocol udp --port 53 --cidr 0.0.0.0/0. For production, consider using VPC endpoints for S3 and CloudWatch Logs instead of internet-routed traffic.
  • Scan container images for vulnerabilities before pushing to ECR. Enable ECR image scanning with: aws ecr put-image-scanning-configuration --repository-name {ecr_repo_name} --image-scanning-configuration scanOnPush=true --region {region}
  • Use IAM roles for credentials — never hardcode access keys in container code.
  • Enable encryption at rest for the S3 bucket: aws s3api put-bucket-encryption --bucket {bucket_name} --server-side-encryption-configuration '{"Rules":[{"ApplyServerSideEncryptionByDefault":{"SSEAlgorithm":"aws:kms"}}]}'
  • Enable CloudWatch Logs encryption for Fargate container logs: aws logs associate-kms-key --log-group-name /StepFunctionFargateTask --kms-key-arn <KMS_KEY_ARN>
  • Configure a Dead Letter Queue on the EventBridge rule for failed invocations
  • Set up CloudWatch alarms on Step Functions execution failures for operational visibility

Version information

  • AWS CLI: 2.x
  • Python runtime: 3.12
  • Last validated: 2026-04-27

Additional Resources

© 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

Files

SKILL.md and 11 other files (scripts, references) in skills/specialized-skills/serverless-skills/processing-s3-uploads-with-step-functions of aws/agent-toolkit-for-aws.

  • SKILL.md
  • references/ecs-task-definition.md
  • references/iam-roles.md
  • scripts/Dockerfile
  • scripts/ecs-trust-policy.json
  • scripts/eventbridge-trust-policy.json
  • scripts/fargate_processor.py
  • scripts/lambda-trust-policy.json
  • scripts/lambda_function.py
  • scripts/requirements.txt
  • scripts/statemachine.asl.json
  • scripts/stepfunctions-trust-policy.json

Open the folder on GitHubat commit bd49cc8

Compare with similar skills

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Categories

Questions about Processing S3 Uploads With Step Functions

What does Processing S3 Uploads With Step Functions do?

Deploy an event-driven workflow that routes S3 uploads to either Lambda or Fargate via Step Functions based on file size. Processing S3 Uploads With Step Functions is an agent skill from aws/agent-toolkit-for-aws, published by the product's own GitHub organization. Deploy an event-driven workflow that routes S3 uploads to either Lambda or Fargate via Step Functions based on file size.

When should I use Processing S3 Uploads With Step Functions?

Processing S3 Uploads With Step Functions fits situations like: A Step Functions state machine when objects are uploaded to S3; keywords: Step Functions; file processing; workflow orchestration.

How do I install Processing S3 Uploads With Step Functions in Claude Code?

Run `npx skills add aws/agent-toolkit-for-aws --skill processing-s3-uploads-with-step-functions -a claude-code`. Or copy the skill folder (skills/specialized-skills/serverless-skills/processing-s3-uploads-with-step-functions in aws/agent-toolkit-for-aws) into .claude/skills/processing-s3-uploads-with-step-functions in your project. Claude Code loads it when a task matches its description.

How do I install Processing S3 Uploads With Step Functions in Codex?

Run `npx skills add aws/agent-toolkit-for-aws --skill processing-s3-uploads-with-step-functions -a codex`. Or copy the skill folder (skills/specialized-skills/serverless-skills/processing-s3-uploads-with-step-functions in aws/agent-toolkit-for-aws) into .agents/skills/processing-s3-uploads-with-step-functions in your project. Codex loads it when a task matches its description.

Can I use Processing S3 Uploads With Step Functions in Cursor, Gemini CLI or GitHub Copilot?

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 processing-s3-uploads-with-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/processing-s3-uploads-with-step-functions, .gemini/skills/processing-s3-uploads-with-step-functions, .github/skills/processing-s3-uploads-with-step-functions and .opencode/skills/processing-s3-uploads-with-step-functions in your project.

What does Processing S3 Uploads With Step Functions need to run?

Going by SKILL.md and its folder, Processing S3 Uploads With Step Functions needs Python for the scripts in its folder and the command-line tools its instructions call (aws, docker and python3). Our summary lists: Python 3; Docker.

Does Processing S3 Uploads With Step Functions access the network?

SKILL.md names 2 domains. As links in the text: docs.aws.amazon.com and docs.docker.com. This is read from the text; nothing was executed.

Is Processing S3 Uploads With Step Functions safe to install?

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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Processing S3 Uploads With Step Functions use?

Processing S3 Uploads With 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.

How many tokens does Processing S3 Uploads With Step Functions use?

About 4k tokens (SKILL.md is roughly 16k 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 1.4k tokens, read only when the agent opens those files.

What are the alternatives to Processing S3 Uploads With Step Functions?

Skills that share tags, products or a category with Processing S3 Uploads With Step Functions: AWS Serverless Eda (zxkane/aws-skills, 367 stars), AWS Serverless (davila7/claude-code-templates, 32k stars), AWS Lambda Microvms (awslabs/agent-plugins, 912 stars) and AWS Lambda (awslabs/agent-plugins, 912 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Processing S3 Uploads With Step Functions?

aws (a GitHub organization, an official publisher) maintains it in aws/agent-toolkit-for-aws, which has 2,816 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.