terraform-infrastructure
Build scalable infrastructure as code with Terraform, managing AWS, Azure, GCP, and on-premise resources through declarative configuration, remote state, and automated provisioning.
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Installation Guide
How to use terraform-infrastructure on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your machine
- ›Node.js 16+ with npm — verify with
node --version - ›Active project directory where you want to add
terraform-infrastructure
Run the install command
Execute the skills CLI command in your project's root directory to begin installation:
Fetches terraform-infrastructure from aj-geddes/useful-ai-prompts and configures it for Cursor.
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate terraform-infrastructure. Access via /terraform-infrastructure in your agent's command palette.
Security Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Documentation
Terraform Infrastructure
Table of Contents
Overview
Build scalable infrastructure as code with Terraform, managing AWS, Azure, GCP, and on-premise resources through declarative configuration, remote state, and automated provisioning.
When to Use
- Cloud infrastructure provisioning
- Multi-environment management (dev, staging, prod)
- Infrastructure versioning and code review
- Cost tracking and resource optimization
- Disaster recovery and environment replication
- Automated infrastructure testing
- Cross-region deployments
Quick Start
Minimal working example:
# terraform/main.tf
terraform {
required_version = ">= 1.0"
required_providers {
aws = {
source = "hashicorp/aws"
version = "~> 5.0"
}
}
# Remote state configuration
backend "s3" {
bucket = "terraform-state-prod"
key = "prod/terraform.tfstate"
region = "us-east-1"
encrypt = true
dynamodb_table = "terraform-locks"
}
}
provider "aws" {
region = var.aws_region
default_tags {
// ... (see reference guides for full implementation)
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents |
|---|---|
| AWS Infrastructure Module | AWS Infrastructure Module |
| Variables and Outputs | Variables and Outputs |
| Terraform Deployment Script | Terraform Deployment Script |
Best Practices
✅ DO
- Use remote state (S3, Terraform Cloud)
- Implement state locking (DynamoDB)
- Organize code into modules
- Use workspaces for environments
- Apply tags consistently
- Use variables for flexibility
- Implement code review before apply
- Keep sensitive data in separate variable files
❌ DON'T
- Store state files locally in git
- Use hardcoded values
- Mix environments in single state
- Skip terraform plan review
- Use root module for everything
- Store secrets in code
- Disable state locking
List & Monetize Your Skill
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Use Cases
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Steps
- 1Install skill using provided installation command
- 2Test with simple use case relevant to your work
- 3Evaluate output quality and relevance
- 4Iterate on prompts to improve results
- 5Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Related Skills
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8aj-geddes/useful-ai-prompts
rest-api-design
7aj-geddes/useful-ai-prompts
accessibility-testing
6aj-geddes/useful-ai-prompts
ansible-automation
4aj-geddes/useful-ai-prompts
query-caching-strategies
3aj-geddes/useful-ai-prompts
fastapi-development
3aj-geddes/useful-ai-prompts
Reviews
- AAdvait Gonzalez★★★★★Dec 28, 2024
terraform-infrastructure fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- KKaira Garcia★★★★★Dec 28, 2024
Solid pick for teams standardizing on skills: terraform-infrastructure is focused, and the summary matches what you get after install.
- LLi Gonzalez★★★★★Dec 16, 2024
terraform-infrastructure has been reliable in day-to-day use. Documentation quality is above average for community skills.
- WWilliam Harris★★★★★Dec 8, 2024
Useful defaults in terraform-infrastructure — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- KKabir Ramirez★★★★★Dec 4, 2024
I recommend terraform-infrastructure for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- AAnaya Dixit★★★★★Dec 4, 2024
Keeps context tight: terraform-infrastructure is the kind of skill you can hand to a new teammate without a long onboarding doc.
- TTariq Abbas★★★★★Nov 27, 2024
terraform-infrastructure is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- IIsabella Khanna★★★★★Nov 23, 2024
terraform-infrastructure has been reliable in day-to-day use. Documentation quality is above average for community skills.
- TTariq Park★★★★★Nov 19, 2024
We added terraform-infrastructure from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- SSakshi Patil★★★★★Nov 15, 2024
Solid pick for teams standardizing on skills: terraform-infrastructure is focused, and the summary matches what you get after install.
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