AWS Cloudformation Vpc Agent Skill

Provides AWS CloudFormation patterns for VPC foundations, including subnets, route tables, internet and NAT gateways, endpoints, and reusable outputs. Use when creating a new network baseline, segmenting public and private workloads, or preparing CloudFormation networking stacks for application deployments.

13k tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

316

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill aws-cloudformation-vpc

The instruction itself

15 sections, as written by the author

AWS CloudFormation VPC Infrastructure

Overview

Build a VPC foundation with CloudFormation that stays readable, reusable, and safe to evolve. Provides a clear subnet and routing model with predictable connectivity for public and private workloads, plus outputs that downstream stacks can consume without duplicating network logic.

Use the references/ files for larger templates and extended service combinations.

When to Use

Creating a new VPC stack for an application or shared platform
Adding public and private subnets across one or more Availability Zones
Wiring internet access, NAT egress, or private endpoints
Exporting VPC, subnet, route table, and security-group-adjacent identifiers for other stacks
Preparing reusable infrastructure for ECS, EKS, Lambda, EC2, or RDS stacks

Instructions

1. Start with the address plan

Before writing resources, define:

VPC CIDR range
Number of Availability Zones
Public, private, and isolated subnet ranges
Which workloads need internet ingress, NAT egress, or only private AWS service access

This prevents route-table sprawl and painful subnet replacement later.

2. Build the core network resources in layers

Create the stack in this order:

VPC and subnets
Internet Gateway for public ingress and egress
NAT gateways if private subnets need outbound internet access
Route tables and subnet associations
Optional VPC endpoints for private access to AWS services

Keep each layer easy to inspect in the template and avoid mixing unrelated application resources into the same stack.

3. Parameterize only the environment-dependent values

Useful parameters include:

Environment name
VPC CIDR and subnet CIDRs
Number of AZs or explicit subnet IDs in nested-stack scenarios
Flags for optional endpoints or NAT layout

Do not parameterize every route or tag unless it meaningfully changes between environments.

4. Export only what consumers really need

Typical outputs:

VPC ID
Public, private, and isolated subnet IDs
Route table IDs when downstream stacks must attach routes
Security boundaries or prefix-list references only when another stack consumes them

Stable outputs make application stacks easier to compose and migrate.

5. Validate before deployment

Run these commands to validate the template and verify routing:

# Validate CloudFormation template syntax
aws cloudformation validate-template --template-body file://vpc.yaml

# Review change set before applying
aws cloudformation create-change-set \
  --stack-name my-vpc \
  --template-body file://vpc.yaml \
  --change-set-type CREATE

# Verify route table associations
aws ec2 describe-route-tables \
  --filters "Name=vpc-id,Values=<vpc-id>"

# Check subnet to route table mappings
aws ec2 describe-route-tables \
  --filters "Name=association.subnet-id,Values=<subnet-id>"

# Verify internet gateway attachment
aws ec2 describe-internet-gateways \
  --filters "Name=attachment.vpc-id,Values=<vpc-id>"

Examples

Example 1: Complete two-tier VPC with routing

This template creates a VPC with public and private subnets, internet gateway, NAT gateway, and properly configured route tables.

AWSTemplateFormatVersion: "2010-09-09"
Description: "Two-tier VPC with public and private subnets"

Resources:
  # VPC
  MainVpc:
    Type: AWS::EC2::VPC
    Properties:
      CidrBlock: 10.0.0.0/16
      EnableDnsHostnames: true
      EnableDnsSupport: true
      Tags:
        - Key: Name
          Value: !Sub "${AWS::StackName}-main"

  # Internet Gateway
  InternetGateway:
    Type: AWS::EC2::InternetGateway
    Properties:
      Tags:
        - Key: Name
          Value: !Sub "${AWS::StackName}-igw"

  # Attach IGW to VPC
  GatewayToInternet:
    Type: AWS::EC2::VPCGatewayAttachment
    Properties:
      VpcId: !Ref MainVpc
      InternetGatewayId: !Ref InternetGateway

  # Public Subnet (AZ 1)
  PublicSubnetA:
    Type: AWS::EC2::Subnet
    Properties:
      VpcId: !Ref MainVpc
      CidrBlock: 10.0.1.0/24
      AvailabilityZone: !Select [0, !GetAZs ""]
      MapPublicIpOnLaunch: true
      Tags:
        - Key: Name
          Value: !Sub "${AWS::StackName}-public-a"

  # Private Subnet (AZ 1)
  PrivateSubnetA:
    Type: AWS::EC2::Subnet
    Properties:
      VpcId: !Ref MainVpc
      CidrBlock: 10.0.11.0/24
      AvailabilityZone: !Select [0, !GetAZs ""]
      Tags:
        - Key: Name
          Value: !Sub "${AWS::StackName}-private-a"

  # Elastic IP for NAT Gateway
  NatEip:
    Type: AWS::EC2::EIP
    DependsOn: GatewayToInternet
    Properties:
      Domain: vpc

  # NAT Gateway
  NatGateway:
    Type: AWS::EC2::NatGateway
    Properties:
      SubnetId: !Ref PublicSubnetA
      AllocationId: !GetAtt NatEip.AllocationId

  # Public Route Table
  PublicRouteTable:
    Type: AWS::EC2::RouteTable
    Properties:
      VpcId: !Ref MainVpc
      Tags:
        - Key: Name
          Value: !Sub "${AWS::StackName}-public-rt"

  # Default route to IGW
  PublicDefaultRoute:
    Type: AWS::EC2::Route
    DependsOn: GatewayToInternet
    Properties:
      RouteTableId: !Ref PublicRouteTable
      DestinationCidrBlock: 0.0.0.0/0
      GatewayId: !Ref InternetGateway

  # Associate public subnet
  PublicSubnetARouteTableAssociation:
    Type: AWS::EC2::SubnetRouteTableAssociation
    Properties:
      SubnetId: !Ref PublicSubnetA
      RouteTableId: !Ref PublicRouteTable

  # Private Route Table
  PrivateRouteTable:
    Type: AWS::EC2::RouteTable
    Properties:
      VpcId: !Ref MainVpc
      Tags:
        - Key: Name
          Value: !Sub "${AWS::StackName}-private-rt"

  # Default route via NAT Gateway
  PrivateDefaultRoute:
    Type: AWS::EC2::Route
    Properties:
      RouteTableId: !Ref PrivateRouteTable
      DestinationCidrBlock: 0.0.0.0/0
      NatGatewayId: !Ref NatGateway

  # Associate private subnet
  PrivateSubnetARouteTableAssociation:
    Type: AWS::EC2::SubnetRouteTableAssociation
    Properties:
      SubnetId: !Ref PrivateSubnetA
      RouteTableId: !Ref PrivateRouteTable

Outputs:
  VpcId:
    Description: VPC ID
    Value: !Ref MainVpc
    Export:
      Name: !Sub "${AWS::StackName}-VpcId"

  PublicSubnetA:
    Description: Public subnet AZ1
    Value: !Ref PublicSubnetA
    Export:
      Name: !Sub "${AWS::StackName}-PublicSubnetA"

  PrivateSubnetA:
    Description: Private subnet AZ1
    Value: !Ref PrivateSubnetA
    Export:
      Name: !Sub "${AWS::StackName}-PrivateSubnetA"

  PublicRouteTableId:
    Description: Public route table ID
    Value: !Ref PublicRouteTable
    Export:
      Name: !Sub "${AWS::StackName}-PublicRouteTableId"

  PrivateRouteTableId:
    Description: Private route table ID
    Value: !Ref PrivateRouteTable
    Export:
      Name: !Sub "${AWS::StackName}-PrivateRouteTableId"

Example 2: VPC endpoint for private S3 access

Resources:
  # S3 VPC Endpoint
  S3Endpoint:
    Type: AWS::EC2::VPCEndpoint
    Properties:
      VpcId: !Ref MainVpc
      ServiceName: !Sub "com.amazonaws.${AWS::Region}.s3"
      RouteTableIds:
        - !Ref PrivateRouteTable
      VpcEndpointType: Gateway

Best Practices

Keep public, private, and isolated subnet purposes explicit in names and tags
Prefer one NAT gateway per AZ for resilient production environments when budget allows
Use VPC endpoints to reduce unnecessary NAT traffic for AWS service access
Export VPC and subnet identifiers from the network stack instead of recreating network assumptions elsewhere
Review network changes with dependency stacks because route and subnet changes can have broad blast radius
Keep the root skill focused and move larger networking variants to references/examples.md

Constraints and Warnings

NAT gateways incur hourly costs and data transfer charges—consider VPC endpoints for AWS service access
CIDR overlap blocks peering, transit, and future network expansion
Route-table or subnet replacements can interrupt traffic even when the template is valid
Endpoint quotas, AZ availability, and service-specific subnet requirements vary by region
Hardcoding Availability Zones can reduce portability across accounts and regions

References

references/examples.md
references/reference.md

Other skills for the same job

different authors, same section of the catalogue

Azure Kubernetes Automatic Readiness

by microsoft

vendor ×3

Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.

Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).

Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).

Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).

This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use when managing biological datasets (scRNA-seq, spatial, flow cytometry, etc.), tracking computational workflows, curating and validating data with biological ontologies, building data lakehouses, or ensuring data lineage and reproducibility in biological research. Covers data management, annotation, ontologies (genes, cell types, diseases, tissues), schema validation, integrations with workflow managers (Nextflow, Snakemake) and MLOps platforms (W&B, MLflow), and deployment strategies.

Latch platform for bioinformatics workflows. Build pipelines with Latch SDK, @workflow/@task decorators, deploy serverless workflows, LatchFile/LatchDir, Nextflow/Snakemake integration.

Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.

17k tokens

How to use it

Copy the folder

Take giuseppe-trisciuoglio/aws-cloudformation-vpc from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.