Agent skill

Infrastructure As Code

by seb1n in seb1n/awesome-ai-agent-skills

Define, deploy, and manage cloud infrastructure as code using tools like Terraform, Pulumi, CloudFormation, and CDK, ensuring consistency, repeatability, and version control.

MITAuto-check passedDevOps & Cloud

Install Infrastructure As Code

skills CLI
$ npx skills add seb1n/awesome-ai-agent-skills --skill infrastructure-as-code -a claude-code

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

GitHub CLI
$ gh skill install seb1n/awesome-ai-agent-skills infrastructure-as-code --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/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/devops-and-infrastructure/infrastructure-as-code .claude/skills/infrastructure-as-code && 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
infrastructure-as-code
GitHub stars
206
Token cost
~3.3k tokens
SKILL.md length
902 words
Files
1
Skills in repo
92
Repo updated
First seen
Licence
MIT

At a glance

Define, deploy, and manage cloud infrastructure as code using tools like Terraform, Pulumi, CloudFormation, and CDK, ensuring consistency, repeatability, and version control.

  • Works in 6 steps: Gather Infrastructure Requirements: The… → Select IaC Tool and Initialize Project:… → Generate Infrastructure Code with… → …
  • The user requests infrastructure as code
  • SKILL.md covers Workflow, Supported Technologies, Usage and Examples, plus 2 more sections
  • Calls terraform and pulumi

What it does

Infrastructure As Code is an agent skill from seb1n/awesome-ai-agent-skills. Define, deploy, and manage cloud infrastructure as code using tools like Terraform, Pulumi, CloudFormation, and CDK, ensuring consistency, repeatability, and version control. Use when the user requests infrastructure as code or provides relevant inputs for this workflow.

Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Infrastructure as code. It works with Pulumi, Terraform, AWS CloudFormation and Amazon Web Services. The repository describes itself as: 103 ready-to-use AI agent skills for Claude Code, OpenAI Codex, Gemini CLI, Cursor, GitHub Copilot, Windsurf, and other Agent Skills-compatible tools. Complete SKILL.md… The licence is MIT.

When your agent uses it

  • The user requests infrastructure as code
  • Provides relevant inputs for this workflow

Example prompts

  • “/infrastructure-as-code”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Gather Infrastructure Requirements: The agent collects details about the desired infrastructure including the cloud provider (AWS, GCP…
  2. Select IaC Tool and Initialize Project: Based on team expertise and project constraints, the agent recommends an IaC tool. Terraform is…
  3. Generate Infrastructure Code with Modules: The agent produces well-structured IaC code using reusable modules. Networking (VPC, subnets…
  4. Configure State Management: The agent sets up remote state storage (e.g., S3 + DynamoDB for Terraform, Pulumi Cloud for Pulumi) with state…
  5. Execute Plan and Apply: The agent runs the plan step (terraform plan, pulumi preview) to generate a detailed diff of proposed changes…
  6. Detect and Remediate Drift: The agent periodically runs drift detection (terraform plan, pulumi refresh) to compare actual infrastructure…

What it can do on your machine

Read from SKILL.md and the folder at commit 75865a5. 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

    Shell commands in SKILL.md call:

    • terraform
    • pulumi

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

  • Network

    No URLs in SKILL.md.

    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

Infrastructure As Code loads about 3.3k tokens when it runs. Until then it costs about 74 tokens; SKILL.md has 902 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~74
When it runs · the whole SKILL.md, loaded when a task matches
~3.3k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from seb1n/awesome-ai-agent-skills at commit 75865a5, republished under its MIT licence (© seb1n). 902 words, ~3,252 tokens.

Download SKILL.mdSave it as .claude/skills/infrastructure-as-code/SKILL.md (or your agent's skills folder).
name
infrastructure-as-code
description
Define, deploy, and manage cloud infrastructure as code using tools like Terraform, Pulumi, CloudFormation, and CDK, ensuring consistency, repeatability, and version control. Use when the user requests infrastructure as code or provides relevant inputs for this workflow.
license
MIT
metadata.author
awesome-ai-agent-skills
metadata.version
1.0.0

Infrastructure as Code

This skill enables the agent to design, generate, and manage infrastructure as code (IaC) for cloud environments. The agent can produce configurations for Terraform, Pulumi, AWS CloudFormation, and AWS CDK, implementing the full plan/apply workflow with proper state management, modular design, and drift detection. IaC ensures that infrastructure is versioned alongside application code, enabling reproducible deployments, peer review of infrastructure changes, and automated provisioning across environments.

Workflow

  1. Gather Infrastructure Requirements: The agent collects details about the desired infrastructure including the cloud provider (AWS, GCP, Azure), the resources needed (compute, storage, networking, databases), sizing and performance requirements, security constraints, and target environments (dev, staging, production). The agent identifies dependencies between resources to determine the correct provisioning order.

  2. Select IaC Tool and Initialize Project: Based on team expertise and project constraints, the agent recommends an IaC tool. Terraform is preferred for multi-cloud and provider-agnostic setups, Pulumi for teams that prefer general-purpose programming languages, and CloudFormation or CDK for AWS-native organizations. The agent initializes the project structure with separate directories for modules, environments, and shared configuration.

  3. Generate Infrastructure Code with Modules: The agent produces well-structured IaC code using reusable modules. Networking (VPC, subnets, security groups), compute (EC2, ECS, Lambda), and data (RDS, S3, DynamoDB) are separated into independent modules with clearly defined inputs and outputs. Variables are parameterized so the same module can be reused across environments with different sizing.

  4. Configure State Management: The agent sets up remote state storage (e.g., S3 + DynamoDB for Terraform, Pulumi Cloud for Pulumi) with state locking to prevent concurrent modifications. State files contain sensitive data and are never committed to version control. The agent configures state encryption at rest and strict access controls on the state backend.

  5. Execute Plan and Apply: The agent runs the plan step (terraform plan, pulumi preview) to generate a detailed diff of proposed changes, then presents the plan for user review before applying. The agent verifies that no unexpected resources are being destroyed or recreated. Only after explicit approval does the agent execute the apply step to provision infrastructure.

  6. Detect and Remediate Drift: The agent periodically runs drift detection (terraform plan, pulumi refresh) to compare actual infrastructure state against the declared configuration. Any out-of-band changes made via the console or CLI are flagged and either reconciled back to the IaC definition or explicitly imported into state. This ensures the IaC code remains the single source of truth.

Supported Technologies

  • IaC Tools: Terraform (HCL), Pulumi (TypeScript, Python, Go, C#), AWS CloudFormation (YAML/JSON), AWS CDK (TypeScript, Python), Ansible
  • Cloud Providers: AWS, Google Cloud Platform, Microsoft Azure, DigitalOcean, Cloudflare
  • State Backends: S3 + DynamoDB, Terraform Cloud, Pulumi Cloud, GCS, Azure Blob Storage
  • CI/CD Integration: Atlantis, Spacelift, Terraform Cloud, GitHub Actions, GitLab CI

Usage

Provide the agent with your cloud provider, the resources to provision, sizing requirements, and any constraints such as compliance standards or cost budgets.

Example prompt:

Create Terraform configuration for an AWS environment with:
- VPC with public and private subnets across 2 AZs
- An EC2 bastion host in the public subnet
- An RDS PostgreSQL instance in the private subnet
- Security groups allowing SSH to bastion and app-to-database traffic only

Examples

Example 1: Terraform Configuration for AWS VPC + EC2 + RDS

main.tf:

hcl
terraform {
  required_version = ">= 1.5"

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }

  backend "s3" {
    bucket         = "my-terraform-state"
    key            = "prod/terraform.tfstate"
    region         = "us-east-1"
    dynamodb_table = "terraform-locks"
    encrypt        = true
  }
}

provider "aws" {
  region = var.aws_region
}

module "vpc" {
  source  = "terraform-aws-modules/vpc/aws"
  version = "5.1.0"

  name = "${var.project}-vpc"
  cidr = "10.0.0.0/16"

  azs             = ["${var.aws_region}a", "${var.aws_region}b"]
  public_subnets  = ["10.0.1.0/24", "10.0.2.0/24"]
  private_subnets = ["10.0.10.0/24", "10.0.20.0/24"]

  enable_nat_gateway   = true
  single_nat_gateway   = true
  enable_dns_hostnames = true

  tags = var.common_tags
}

resource "aws_security_group" "bastion" {
  name_prefix = "${var.project}-bastion-"
  vpc_id      = module.vpc.vpc_id

  ingress {
    from_port   = 22
    to_port     = 22
    protocol    = "tcp"
    cidr_blocks = [var.allowed_ssh_cidr]
  }

  egress {
    from_port   = 0
    to_port     = 0
    protocol    = "-1"
    cidr_blocks = ["0.0.0.0/0"]
  }

  tags = merge(var.common_tags, { Name = "${var.project}-bastion-sg" })
}

resource "aws_instance" "bastion" {
  ami                         = data.aws_ami.amazon_linux.id
  instance_type               = "t3.micro"
  subnet_id                   = module.vpc.public_subnets[0]
  vpc_security_group_ids      = [aws_security_group.bastion.id]
  key_name                    = var.key_pair_name
  associate_public_ip_address = true

  tags = merge(var.common_tags, { Name = "${var.project}-bastion" })
}

resource "aws_security_group" "rds" {
  name_prefix = "${var.project}-rds-"
  vpc_id      = module.vpc.vpc_id

  ingress {
    from_port       = 5432
    to_port         = 5432
    protocol        = "tcp"
    security_groups = [aws_security_group.bastion.id]
  }

  tags = merge(var.common_tags, { Name = "${var.project}-rds-sg" })
}

resource "aws_db_instance" "postgres" {
  identifier             = "${var.project}-db"
  engine                 = "postgres"
  engine_version         = "16.1"
  instance_class         = var.db_instance_class
  allocated_storage      = 20
  max_allocated_storage  = 100
  storage_encrypted      = true
  db_name                = var.db_name
  username               = var.db_username
  password               = var.db_password
  db_subnet_group_name   = module.vpc.database_subnet_group_name
  vpc_security_group_ids = [aws_security_group.rds.id]
  skip_final_snapshot    = false
  final_snapshot_identifier = "${var.project}-db-final"
  backup_retention_period   = 7
  multi_az                  = var.environment == "production"

  tags = var.common_tags
}

data "aws_ami" "amazon_linux" {
  most_recent = true
  owners      = ["amazon"]

  filter {
    name   = "name"
    values = ["al2023-ami-*-x86_64"]
  }
}

output "bastion_public_ip" {
  value = aws_instance.bastion.public_ip
}

output "rds_endpoint" {
  value = aws_db_instance.postgres.endpoint
}

variables.tf:

hcl
variable "aws_region"       { default = "us-east-1" }
variable "project"          { default = "myproject" }
variable "environment"      { default = "production" }
variable "allowed_ssh_cidr" { description = "CIDR block allowed to SSH to bastion" }
variable "key_pair_name"    { description = "EC2 key pair name" }
variable "db_instance_class" { default = "db.t3.medium" }
variable "db_name"          { default = "appdb" }
variable "db_username"      { default = "appuser" }
variable "db_password"      { sensitive = true }
variable "common_tags" {
  type    = map(string)
  default = { ManagedBy = "terraform", Project = "myproject" }
}
Example 2: Pulumi TypeScript for a Serverless API
typescript
import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";
import * as apigateway from "@pulumi/aws-apigateway";

const config = new pulumi.Config();
const stage = pulumi.getStack();

// DynamoDB table for the API
const table = new aws.dynamodb.Table("items-table", {
  attributes: [{ name: "id", type: "S" }],
  hashKey: "id",
  billingMode: "PAY_PER_REQUEST",
  tags: { Environment: stage, ManagedBy: "pulumi" },
});

// Lambda function for API handlers
const lambdaRole = new aws.iam.Role("api-lambda-role", {
  assumeRolePolicy: JSON.stringify({
    Version: "2012-10-17",
    Statement: [{
      Action: "sts:AssumeRole",
      Effect: "Allow",
      Principal: { Service: "lambda.amazonaws.com" },
    }],
  }),
});

new aws.iam.RolePolicyAttachment("lambda-basic", {
  role: lambdaRole.name,
  policyArn: aws.iam.ManagedPolicies.AWSLambdaBasicExecutionRole,
});

new aws.iam.RolePolicyAttachment("lambda-dynamodb", {
  role: lambdaRole.name,
  policyArn: aws.iam.ManagedPolicies.AmazonDynamoDBFullAccess,
});

const handler = new aws.lambda.Function("api-handler", {
  runtime: aws.lambda.Runtime.NodeJS20dX,
  handler: "index.handler",
  code: new pulumi.asset.AssetArchive({
    ".": new pulumi.asset.FileArchive("./lambda"),
  }),
  role: lambdaRole.arn,
  environment: {
    variables: {
      TABLE_NAME: table.name,
      STAGE: stage,
    },
  },
  memorySize: 256,
  timeout: 30,
  tags: { Environment: stage, ManagedBy: "pulumi" },
});

// API Gateway REST API
const api = new apigateway.RestAPI("items-api", {
  routes: [
    { path: "/items", method: "GET", eventHandler: handler },
    { path: "/items", method: "POST", eventHandler: handler },
    { path: "/items/{id}", method: "GET", eventHandler: handler },
    { path: "/items/{id}", method: "DELETE", eventHandler: handler },
  ],
  stageName: stage,
});

export const apiUrl = api.url;
export const tableName = table.name;
Show full SKILL.md (401 more words)Show less

Best Practices

  • Never store state locally in production: Always use a remote backend with state locking (S3 + DynamoDB, Terraform Cloud, Pulumi Cloud). Local state files can be lost, corrupted, or create conflicts when multiple team members run applies concurrently.
  • Use modules for reusability: Extract common patterns (VPC, security groups, ECS services) into versioned modules. This reduces duplication and ensures that infrastructure standards are enforced consistently across all environments and teams.
  • Treat secrets as sensitive variables: Mark database passwords, API keys, and tokens as sensitive in Terraform or use Pulumi's secret encryption. Never hardcode secrets in IaC files. Integrate with AWS Secrets Manager or HashiCorp Vault for runtime secret injection.
  • Run plan in CI, apply with approval: Integrate IaC into your CI/CD pipeline so that every pull request shows the plan diff. Use tools like Atlantis or Spacelift for automated plan comments and require manual approval before apply runs in production.
  • Tag all resources consistently: Apply standard tags (Project, Environment, Team, ManagedBy) to every resource. Tags enable cost allocation, access control, and automated cleanup of orphaned resources.
  • Use workspaces or stacks for environments: Maintain separate state per environment (dev, staging, production) using Terraform workspaces or Pulumi stacks. Share the same code with environment-specific variable files to ensure parity.

Edge Cases

  • State lock contention: If a previous apply crashed or was interrupted, the state lock may remain held. Use terraform force-unlock (with the lock ID) only after confirming no other apply is running. Pulumi provides pulumi cancel for the same scenario.
  • Drift from manual changes: Resources modified through the cloud console or CLI will not match the IaC state. Run terraform plan regularly to detect drift and either revert the manual change or import it with terraform import. Avoid manual changes to IaC-managed resources.
  • Circular dependencies: Terraform cannot handle circular resource references (e.g., security group A references B and B references A). Break the cycle by creating the groups first with no rules, then add rules in separate aws_security_group_rule resources.
  • Provider version breaking changes: Major provider updates can change resource schemas and cause plan failures. Pin provider versions in required_providers and upgrade deliberately with a tested plan/apply cycle.
  • Large state files and performance: As infrastructure grows, state files can become large and slow down plan/apply operations. Use state splitting by organizing infrastructure into separate root modules (networking, compute, data) each with their own state file and use terraform_remote_state data sources to share outputs.

© seb1n, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in devops-and-infrastructure/infrastructure-as-code of seb1n/awesome-ai-agent-skills.

Open the folder on GitHubat commit 75865a5

Compare with similar skills

Infrastructure As Code 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.

Infrastructure As Code compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Infrastructure As Code this skillseb1n/awesome-ai-agent-skills206—~3.3kAutomated safety check: PassMIT
AWS Sst Developmentzxkane/aws-skills367—~2.7kAutomated safety check: WarnMIT
AWS Cloud Advisortech-leads-club/agent-skills7k—~2.1kAutomated safety check: PassCC-BY-4.0
Audit Infrastructure As Codecyberful/cyberful134—~649Automated safety check: PassAGPL-3.0
AWS Architecture Diagramawslabs/agent-plugins912—~3.8kAutomated safety check: NotesApache-2.0
Document Serviceawslabs/agent-plugins912—~4.4kAutomated safety check: PassApache-2.0

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Categories

Questions about Infrastructure As Code

What does Infrastructure As Code do?

Define, deploy, and manage cloud infrastructure as code using tools like Terraform, Pulumi, CloudFormation, and CDK, ensuring consistency, repeatability, and version control. Infrastructure As Code is an agent skill from seb1n/awesome-ai-agent-skills. Define, deploy, and manage cloud infrastructure as code using tools like Terraform, Pulumi, CloudFormation, and CDK, ensuring consistency, repeatability, and version control.

When should I use Infrastructure As Code?

Infrastructure As Code fits situations like: the user requests infrastructure as code; provides relevant inputs for this workflow.

How do I install Infrastructure As Code in Claude Code?

Run `npx skills add seb1n/awesome-ai-agent-skills --skill infrastructure-as-code -a claude-code`. Or copy the skill folder (devops-and-infrastructure/infrastructure-as-code in seb1n/awesome-ai-agent-skills) into .claude/skills/infrastructure-as-code in your project. Claude Code loads it when a task matches its description.

How do I install Infrastructure As Code in Codex?

Run `npx skills add seb1n/awesome-ai-agent-skills --skill infrastructure-as-code -a codex`. Or copy the skill folder (devops-and-infrastructure/infrastructure-as-code in seb1n/awesome-ai-agent-skills) into .agents/skills/infrastructure-as-code in your project. Codex loads it when a task matches its description.

Can I use Infrastructure As Code 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 seb1n/awesome-ai-agent-skills --skill infrastructure-as-code -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/infrastructure-as-code, .gemini/skills/infrastructure-as-code, .github/skills/infrastructure-as-code and .opencode/skills/infrastructure-as-code in your project.

What does Infrastructure As Code need to run?

Going by SKILL.md and its folder, Infrastructure As Code needs the command-line tools its instructions call (terraform and pulumi).

Does Infrastructure As Code access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Infrastructure As Code 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. Review the folder before installing.

What licence does Infrastructure As Code use?

Infrastructure As Code is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Infrastructure As Code use?

About 3.3k 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.

What are the alternatives to Infrastructure As Code?

Skills that share tags, products or a category with Infrastructure As Code: AWS Sst Development (zxkane/aws-skills, 367 stars), AWS Cloud Advisor (tech-leads-club/agent-skills, 7k stars), Audit Infrastructure As Code (cyberful/cyberful, 134 stars) and AWS Architecture Diagram (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 Infrastructure As Code?

seb1n (a GitHub user) maintains it in seb1n/awesome-ai-agent-skills, which has 206 GitHub stars. The repository holds 92 skills in this directory. The repository was last updated on August 9, 2026.

Source: seb1n/awesome-ai-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.