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Cloudformation

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itsmostafa
cloudformation

AWS CloudFormation infrastructure as code for stack management. Use when writing templates, deploying stacks, managing drift, troubleshooting deployments, or organizing infrastructure with nested stacks.

Overview

Publisheritsmostafa
Repositoryaws-agent-skills
Skill namecloudformation
Stars
1.2K
Forks
445
Bundled files
1
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.

  • 1 bundled files

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

  • Open source

    Published by itsmostafa on GitHub. Read the source before you install it.

Installation

Install the Cloudformation 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.
    https://github.com/itsmostafa/aws-agent-skills/tree/main/skills/cloudformation
  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/itsmostafa/aws-agent-skills.git /tmp/aws-agent-skills
mkdir -p .claude/skills
cp -r /tmp/aws-agent-skills/skills/cloudformation .claude/skills/cloudformation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cloudformation 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 Cloudformation 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 Cloudformation 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

AWS CloudFormation provisions and manages AWS resources using templates. Define infrastructure as code, version control it, and deploy consistently across environments.

Table of Contents

Core Concepts

Templates

JSON or YAML files defining AWS resources. Key sections:

  • Parameters: Input values
  • Mappings: Static lookup tables
  • Conditions: Conditional resource creation
  • Resources: AWS resources (required)
  • Outputs: Return values

Stacks

Collection of resources managed as a single unit. Created from templates.

Change Sets

Preview changes before executing updates.

Stack Sets

Deploy stacks across multiple accounts and regions.

Common Patterns

Basic Template Structure

yaml
AWSTemplateFormatVersion: '2010-09-09'
Description: My infrastructure template

Parameters:
  Environment:
    Type: String
    AllowedValues: [dev, staging, prod]
    Default: dev

Mappings:
  EnvironmentConfig:
    dev:
      InstanceType: t3.micro
    prod:
      InstanceType: t3.large

Conditions:
  IsProd: !Equals [!Ref Environment, prod]

Resources:
  MyBucket:
    Type: AWS::S3::Bucket
    Properties:
      BucketName: !Sub 'my-app-${Environment}-${AWS::AccountId}'
      VersioningConfiguration:
        Status: !If [IsProd, Enabled, Suspended]

Outputs:
  BucketName:
    Description: S3 bucket name
    Value: !Ref MyBucket
    Export:
      Name: !Sub '${AWS::StackName}-BucketName'

Deploy a Stack

AWS CLI:

bash
# Create stack
aws cloudformation create-stack \
  --stack-name my-stack \
  --template-body file://template.yaml \
  --parameters ParameterKey=Environment,ParameterValue=prod \
  --capabilities CAPABILITY_IAM

# Wait for completion
aws cloudformation wait stack-create-complete --stack-name my-stack

# Update stack
aws cloudformation update-stack \
  --stack-name my-stack \
  --template-body file://template.yaml \
  --parameters ParameterKey=Environment,ParameterValue=prod

# Delete stack
aws cloudformation delete-stack --stack-name my-stack

Use Change Sets

bash
# Create change set
aws cloudformation create-change-set \
  --stack-name my-stack \
  --change-set-name my-changes \
  --template-body file://template.yaml \
  --parameters ParameterKey=Environment,ParameterValue=prod

# Describe changes
aws cloudformation describe-change-set \
  --stack-name my-stack \
  --change-set-name my-changes

# Execute change set
aws cloudformation execute-change-set \
  --stack-name my-stack \
  --change-set-name my-changes

Lambda Function

yaml
Resources:
  LambdaFunction:
    Type: AWS::Lambda::Function
    Properties:
      FunctionName: !Sub '${AWS::StackName}-function'
      Runtime: python3.12
      Handler: index.handler
      Role: !GetAtt LambdaRole.Arn
      Code:
        ZipFile: |
          def handler(event, context):
              return {'statusCode': 200, 'body': 'Hello'}
      Environment:
        Variables:
          ENVIRONMENT: !Ref Environment

  LambdaRole:
    Type: AWS::IAM::Role
    Properties:
      AssumeRolePolicyDocument:
        Version: '2012-10-17'
        Statement:
          - Effect: Allow
            Principal:
              Service: lambda.amazonaws.com
            Action: sts:AssumeRole
      ManagedPolicyArns:
        - arn:aws:iam::aws:policy/service-role/AWSLambdaBasicExecutionRole

VPC with Subnets

yaml
Resources:
  VPC:
    Type: AWS::EC2::VPC
    Properties:
      CidrBlock: 10.0.0.0/16
      EnableDnsHostnames: true
      Tags:
        - Key: Name
          Value: !Sub '${AWS::StackName}-vpc'

  PublicSubnet1:
    Type: AWS::EC2::Subnet
    Properties:
      VpcId: !Ref VPC
      AvailabilityZone: !Select [0, !GetAZs '']
      CidrBlock: 10.0.1.0/24
      MapPublicIpOnLaunch: true

  PrivateSubnet1:
    Type: AWS::EC2::Subnet
    Properties:
      VpcId: !Ref VPC
      AvailabilityZone: !Select [0, !GetAZs '']
      CidrBlock: 10.0.10.0/24

  InternetGateway:
    Type: AWS::EC2::InternetGateway

  AttachGateway:
    Type: AWS::EC2::VPCGatewayAttachment
    Properties:
      VpcId: !Ref VPC
      InternetGatewayId: !Ref InternetGateway

  PublicRouteTable:
    Type: AWS::EC2::RouteTable
    Properties:
      VpcId: !Ref VPC

  PublicRoute:
    Type: AWS::EC2::Route
    DependsOn: AttachGateway
    Properties:
      RouteTableId: !Ref PublicRouteTable
      DestinationCidrBlock: 0.0.0.0/0
      GatewayId: !Ref InternetGateway

  PublicSubnet1RouteTableAssociation:
    Type: AWS::EC2::SubnetRouteTableAssociation
    Properties:
      SubnetId: !Ref PublicSubnet1
      RouteTableId: !Ref PublicRouteTable

DynamoDB Table

yaml
Resources:
  OrdersTable:
    Type: AWS::DynamoDB::Table
    Properties:
      TableName: !Sub '${AWS::StackName}-orders'
      AttributeDefinitions:
        - AttributeName: PK
          AttributeType: S
        - AttributeName: SK
          AttributeType: S
        - AttributeName: GSI1PK
          AttributeType: S
        - AttributeName: GSI1SK
          AttributeType: S
      KeySchema:
        - AttributeName: PK
          KeyType: HASH
        - AttributeName: SK
          KeyType: RANGE
      GlobalSecondaryIndexes:
        - IndexName: GSI1
          KeySchema:
            - AttributeName: GSI1PK
              KeyType: HASH
            - AttributeName: GSI1SK
              KeyType: RANGE
          Projection:
            ProjectionType: ALL
      BillingMode: PAY_PER_REQUEST
      PointInTimeRecoverySpecification:
        PointInTimeRecoveryEnabled: true

CLI Reference

Stack Operations

CommandDescription
aws cloudformation create-stackCreate stack
aws cloudformation update-stackUpdate stack
aws cloudformation delete-stackDelete stack
aws cloudformation describe-stacksGet stack info
aws cloudformation list-stacksList stacks
aws cloudformation describe-stack-eventsGet events
aws cloudformation describe-stack-resourcesGet resources

Change Sets

CommandDescription
aws cloudformation create-change-setCreate change set
aws cloudformation describe-change-setView changes
aws cloudformation execute-change-setApply changes
aws cloudformation delete-change-setDelete change set

Template

CommandDescription
aws cloudformation validate-templateValidate template
aws cloudformation get-templateGet stack template
aws cloudformation get-template-summaryGet template info

Best Practices

Template Design

  • Use parameters for environment-specific values
  • Use mappings for static lookup tables
  • Use conditions for optional resources
  • Export outputs for cross-stack references
  • Add descriptions to parameters and outputs

Security

  • Use IAM roles instead of access keys
  • Enable termination protection for production
  • Use stack policies to protect resources
  • Never hardcode secrets — use Secrets Manager
bash
# Enable termination protection
aws cloudformation update-termination-protection \
  --stack-name my-stack \
  --enable-termination-protection

Organization

  • Use nested stacks for complex infrastructure
  • Create reusable modules
  • Version control templates
  • Use consistent naming conventions

Reliability

  • Use DependsOn for explicit dependencies
  • Configure creation policies for instances
  • Use update policies for Auto Scaling groups
  • Implement rollback triggers

Troubleshooting

Stack Creation Failed

bash
# Get failure reason
aws cloudformation describe-stack-events \
  --stack-name my-stack \
  --query 'StackEvents[?ResourceStatus==`CREATE_FAILED`]'

# Common causes:
# - IAM permissions
# - Resource limits
# - Invalid property values
# - Dependency failures

Stack Stuck in DELETE_FAILED

bash
# Identify resources that couldn't be deleted
aws cloudformation describe-stack-resources \
  --stack-name my-stack \
  --query 'StackResources[?ResourceStatus==`DELETE_FAILED`]'

# Retry with resources to skip
aws cloudformation delete-stack \
  --stack-name my-stack \
  --retain-resources ResourceLogicalId1 ResourceLogicalId2

Drift Detection

bash
# Detect drift
aws cloudformation detect-stack-drift --stack-name my-stack

# Check drift status
aws cloudformation describe-stack-drift-detection-status \
  --stack-drift-detection-id abc123

# View drifted resources
aws cloudformation describe-stack-resource-drifts \
  --stack-name my-stack

Rollback Failed

bash
# Continue update rollback
aws cloudformation continue-update-rollback \
  --stack-name my-stack \
  --resources-to-skip ResourceLogicalId1

References

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 Cloudformation AI skill do?

AWS CloudFormation infrastructure as code for stack management. Use when writing templates, deploying stacks, managing drift, troubleshooting deployments, or organizing infrastructure with nested stacks.

Why use Cloudformation on TypingMind?

Because you install it once and use it with any model. Cloudformation 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 Cloudformation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/itsmostafa/aws-agent-skills/tree/main/skills/cloudformation. 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 Cloudformation?

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 Cloudformation?

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

Is the Cloudformation AI skill free?

Yes. It is published on GitHub by itsmostafa 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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