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Aws Cloudformation S3

Community
giuseppe-trisciuoglio
aws-cloudformation-s3

Provides AWS CloudFormation patterns for Amazon S3. Use when creating S3 buckets, policies, versioning, lifecycle rules, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.

Overview

Publishergiuseppe-trisciuoglio
Repositorydeveloper-kit
Skill nameaws-cloudformation-s3
Stars
345
Forks
41
Bundled files
4
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by giuseppe-trisciuoglio on GitHub. Read the source before you install it.

Installation

Install the Aws Cloudformation S3 AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git /tmp/developer-kit
mkdir -p .claude/skills
cp -r /tmp/developer-kit/plugins/developer-kit-aws/skills/aws-cloudformation/aws-cloudformation-s3 .claude/skills/aws-cloudformation-s3
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Aws Cloudformation S3 in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Aws Cloudformation S3 on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Aws Cloudformation S3 is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

AWS CloudFormation S3 Patterns

Provides S3 bucket configurations, policies, versioning, lifecycle rules, and CloudFormation template structure best practices for production-ready infrastructure.

When to Use

  • Creating S3 buckets with custom configurations
  • Implementing bucket policies for access control
  • Configuring S3 versioning for data protection
  • Setting up lifecycle rules for data management
  • Creating Outputs for cross-stack references
  • Using Parameters with AWS-specific types
  • Organizing templates with Mappings and Conditions

Overview

S3 bucket configurations, policies, versioning, lifecycle rules, and CloudFormation template structure for production-ready infrastructure.

Instructions

  1. Define Bucket Resources: Create AWS::S3::Bucket with versioning, encryption, PublicAccessBlock
  2. Configure Bucket Policy: Set up IAM policies for access control
  3. Set Up Lifecycle Rules: Define transitions and expiration policies
  4. Configure CORS: Allow cross-origin requests if needed
  5. Add Outputs: Export bucket names/ARNs for cross-stack references

Validate before deploy:

bash
aws cloudformation validate-template --template-body file://template.yaml

Deploy with rollback on failure:

bash
aws cloudformation deploy \
  --template-file template.yaml \
  --stack-name my-s3-stack \
  --capabilities CAPABILITY_IAM

If deployment fails, CloudFormation automatically rolls back. Check failures with:

bash
aws cloudformation describe-stack-events --stack-name my-s3-stack

Quick Reference

Resource TypePurpose
AWS::S3::BucketCreate S3 bucket
AWS::S3::BucketPolicySet bucket-level policies
AWS::S3::BucketReplicationCross-region replication
ParametersInput values for customization
MappingsStatic configuration tables
ConditionsConditional resource creation
OutputsReturn values for cross-stack references

Examples

Basic S3 Bucket

yaml
Resources:
  DataBucket:
    Type: AWS::S3::Bucket
    Properties:
      BucketName: my-data-bucket

Bucket with Versioning and Encryption

yaml
DataBucket:
  Type: AWS::S3::Bucket
  Properties:
    BucketName: !Sub "${AWS::StackName}-data"
    VersioningConfiguration:
      Status: Enabled
    BucketEncryption:
      ServerSideEncryptionConfiguration:
        - ServerSideEncryptionByDefault:
            SSEAlgorithm: AES256
    PublicAccessBlockConfiguration:
      BlockPublicAcls: true
      BlockPublicPolicy: true

Lifecycle Rule

yaml
DataBucket:
  Type: AWS::S3::Bucket
  Properties:
    LifecycleConfiguration:
      Rules:
        - Id: ArchiveOldData
          Status: Enabled
          Transitions:
            - StorageClass: GLACIER
              TransitionInDays: 365

Bucket Policy

yaml
BucketPolicy:
  Type: AWS::S3::BucketPolicy
  Properties:
    Bucket: !Ref DataBucket
    PolicyDocument:
      Statement:
        - Effect: Allow
          Principal:
            AWS: !Ref RoleArn
          Action:
            - s3:GetObject
          Resource: !Sub "${DataBucket.Arn}/*"

See references/complete-examples.md for more complete examples including CORS, static websites, replication, and production-ready configurations.

Template Structure

Template Sections

yaml
AWSTemplateFormatVersion: 2010-09-09
Description: Template description

Mappings: {}       # Static configuration tables
Metadata: {}       # Additional information
Parameters: {}     # Input values
Conditions: {}     # Conditional creation
Transform: {}      # Macro processing
Resources: {}      # AWS resources (REQUIRED)
Outputs: {}        # Return values

Parameters

yaml
Parameters:
  BucketName:
    Type: String
    Description: S3 bucket name
    Default: my-bucket
    MinLength: 3
    MaxLength: 63
    AllowedPattern: '^[a-z0-9-]+$'

Conditions

yaml
Conditions:
  IsProduction: !Equals [!Ref Environment, prod]
  ShouldEnableVersioning: !Equals [!Ref EnableVersioning, 'true']

Resources:
  DataBucket:
    Type: AWS::S3::Bucket
    Properties:
      VersioningConfiguration:
        Status: !If [ShouldEnableVersioning, Enabled, Suspended]

Outputs

yaml
Outputs:
  BucketName:
    Description: Name of the S3 bucket
    Value: !Ref DataBucket
    Export:
      Name: !Sub '${AWS::StackName}-BucketName'

See references/advanced-configuration.md for detailed Mappings, Conditions, Parameters, and cross-stack references.

Best Practices

  1. Public Access Block: Always enable for non-static website buckets
  2. Versioning: Enable for critical data to prevent accidental deletion
  3. Bucket Policies: Use instead of ACLs for access control
  4. Lifecycle Rules: Implement cost optimization with tiering
  5. Encryption: Enable default encryption (SSE-KMS or AES256)
  6. Tags: Tag all resources for organization and cost allocation
  7. Outputs: Export bucket names/ARNs for cross-stack references
  8. Parameters: Use parameters for reusability across environments

Common Troubleshooting

Bucket already exists: Use unique bucket names with CloudFormation stack name Access denied: Verify bucket policy and IAM permissions Versioning conflicts: Cannot suspend versioning once objects exist Lifecycle not working: Check rule status and prefix filters Cross-stack references: Ensure outputs are exported before importing

Related Skills

References

Complete Examples

  • references/complete-examples.md - Basic buckets, versioning, lifecycle, CORS, policies, production stacks, event notifications, static websites, replication

Advanced Configuration

Constraints and Warnings

  • Bucket names: Must be globally unique (across all AWS accounts)
  • Versioning: Cannot be suspended once objects exist in bucket
  • Lifecycle rules: Minimum 1 day for expiration, 0 days for transitions
  • Bucket policies: Limited to 20 KB in size
  • Public access: Blocked by default; requires explicit configuration
  • CORS: Limited to 100 rules per bucket
  • Replication: Versioning must be enabled on both source and destination
  • Encryption: KMS keys must be in same region as bucket
  • Tags: Maximum 50 tags per resource
  • Stack limits: CloudFormation limits resources per stack (200 default)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Aws Cloudformation S3 AI skill do?

Provides AWS CloudFormation patterns for Amazon S3. Use when creating S3 buckets, policies, versioning, lifecycle rules, and implementing template structure with Parameters, Outputs, Mappings, Conditions, and cross-stack references.

Why use Aws Cloudformation S3 on TypingMind?

Because you install it once and use it with any model. Aws Cloudformation S3 is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Aws Cloudformation S3 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-aws/skills/aws-cloudformation/aws-cloudformation-s3. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Aws Cloudformation S3?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Aws Cloudformation S3?

As many as you like. As long as a model supports skills, you can use Aws Cloudformation S3 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Aws Cloudformation S3 AI skill free?

Yes. It is published on GitHub by giuseppe-trisciuoglio under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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