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Terraform Test

Organization
hashicorp
terraform-test

Comprehensive guide for writing and running Terraform tests. Use when creating test files (.tftest.hcl), writing test scenarios with run blocks, validating infrastructure behavior with assertions, mocking providers and data sources, testing module outputs and resource configurations, or troubleshooting Terraform test syntax and execution.

Overview

Publisherhashicorp
Repositoryagent-skills
Skill nameterraform-test
Stars
880
Forks
130
Bundled files
3
LicenseMPL-2.0
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Terraform Test 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/hashicorp/agent-skills/tree/main/plugins/terraform/skills/terraform-test
  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/hashicorp/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/plugins/terraform/skills/terraform-test .claude/skills/terraform-test
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Terraform Test 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 Terraform Test 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 Terraform Test 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.

Terraform Test

Terraform's built-in testing framework validates that configuration updates don't introduce breaking changes. Tests run against temporary resources, protecting existing infrastructure and state files.

Reference Files

  • references/MOCK_PROVIDERS.md — Mock provider syntax, common defaults, when to use mocks (Terraform 1.7.0+ only — skip if the user's version is below 1.7)
  • references/CI_CD.md — GitHub Actions and GitLab CI pipeline examples
  • references/EXAMPLES.md — Complete example test suite (unit, integration, and mock tests for a VPC module)

Read the relevant reference file when the user asks about mocking, CI/CD integration, or wants a full example.

Core Concepts

  • Test file (.tftest.hcl / .tftest.json): Contains run blocks that validate your configuration
  • Run block: A single test scenario with optional variables, providers, and assertions
  • Assert block: Conditions that must be true for the test to pass
  • Mock provider: Simulates provider behavior without real infrastructure (Terraform 1.7.0+)
  • Test modes: apply (default, creates real resources) or plan (validates logic only)

File Structure

my-module/
├── main.tf
├── variables.tf
├── outputs.tf
└── tests/
    ├── defaults_unit_test.tftest.hcl         # plan mode — fast, no resources
    ├── validation_unit_test.tftest.hcl        # plan mode
    └── full_stack_integration_test.tftest.hcl # apply mode — creates real resources

Use *_unit_test.tftest.hcl for plan-mode tests and *_integration_test.tftest.hcl for apply-mode tests so they can be filtered separately in CI.

Test File Structure

hcl
# Optional: test-wide settings
test {
  parallel = true  # Enable parallel execution for all run blocks (default: false)
}

# Optional: file-level variables (highest precedence, override all other sources)
variables {
  aws_region    = "us-west-2"
  instance_type = "t2.micro"
}

# Optional: provider configuration
provider "aws" {
  region = var.aws_region
}

# Required: at least one run block
run "test_default_configuration" {
  command = plan

  assert {
    condition     = aws_instance.example.instance_type == "t2.micro"
    error_message = "Instance type should be t2.micro by default"
  }
}

Run Block

hcl
run "test_name" {
  command  = plan  # or apply (default)
  parallel = true  # optional, since v1.9.0

  # Override file-level variables
  variables {
    instance_type = "t3.large"
  }

  # Reference a specific module
  module {
    source  = "./modules/vpc"  # local or registry only (not git/http)
    version = "5.0.0"          # registry modules only
  }

  # Control state isolation
  state_key = "shared_state"  # since v1.9.0

  # Plan behavior
  plan_options {
    mode    = refresh-only  # or normal (default)
    refresh = true
    replace = [aws_instance.example]
    target  = [aws_instance.example]
  }

  # Assertions
  assert {
    condition     = aws_instance.example.id != ""
    error_message = "Instance should have a valid ID"
  }

  # Expected failures (test passes if these fail)
  expect_failures = [
    var.instance_count
  ]
}

Common Test Patterns

Validate outputs

hcl
run "test_outputs" {
  command = plan

  assert {
    condition     = output.vpc_id != null
    error_message = "VPC ID output must be defined"
  }

  assert {
    condition     = can(regex("^vpc-", output.vpc_id))
    error_message = "VPC ID should start with 'vpc-'"
  }
}

Conditional resources

hcl
run "test_nat_gateway_disabled" {
  command = plan

  variables {
    create_nat_gateway = false
  }

  assert {
    condition     = length(aws_nat_gateway.main) == 0
    error_message = "NAT gateway should not be created when disabled"
  }
}

Resource counts

hcl
run "test_resource_count" {
  command = plan

  variables {
    instance_count = 3
  }

  assert {
    condition     = length(aws_instance.workers) == 3
    error_message = "Should create exactly 3 worker instances"
  }
}

Tags

hcl
run "test_resource_tags" {
  command = plan

  variables {
    common_tags = {
      Environment = "production"
      ManagedBy   = "Terraform"
    }
  }

  assert {
    condition     = aws_instance.example.tags["Environment"] == "production"
    error_message = "Environment tag should be set correctly"
  }

  assert {
    condition     = aws_instance.example.tags["ManagedBy"] == "Terraform"
    error_message = "ManagedBy tag should be set correctly"
  }
}

Data sources

hcl
run "test_data_source_lookup" {
  command = plan

  assert {
    condition     = data.aws_ami.ubuntu.id != ""
    error_message = "Should find a valid Ubuntu AMI"
  }

  assert {
    condition     = can(regex("^ami-", data.aws_ami.ubuntu.id))
    error_message = "AMI ID should be in correct format"
  }
}

Validation rules

hcl
run "test_invalid_environment" {
  command = plan

  variables {
    environment = "invalid"
  }

  expect_failures = [
    var.environment
  ]
}

Sequential tests with dependencies

hcl
run "setup_vpc" {
  command = apply

  assert {
    condition     = output.vpc_id != ""
    error_message = "VPC should be created"
  }
}

run "test_subnet_in_vpc" {
  command = plan

  variables {
    vpc_id = run.setup_vpc.vpc_id
  }

  assert {
    condition     = aws_subnet.example.vpc_id == run.setup_vpc.vpc_id
    error_message = "Subnet should be in the VPC from setup_vpc"
  }
}

Plan options (refresh-only, targeted)

hcl
run "test_refresh_only" {
  command = plan

  plan_options {
    mode = refresh-only
  }

  assert {
    condition     = aws_instance.example.tags["Environment"] == "production"
    error_message = "Tags should be refreshed correctly"
  }
}

run "test_specific_resource" {
  command = plan

  plan_options {
    target = [aws_instance.example]
  }

  assert {
    condition     = aws_instance.example.instance_type == "t2.micro"
    error_message = "Targeted resource should be planned"
  }
}

Parallel modules

hcl
run "test_networking_module" {
  command  = plan
  parallel = true

  module {
    source = "./modules/networking"
  }

  assert {
    condition     = output.vpc_id != ""
    error_message = "VPC should be created"
  }
}

run "test_compute_module" {
  command  = plan
  parallel = true

  module {
    source = "./modules/compute"
  }

  assert {
    condition     = output.instance_id != ""
    error_message = "Instance should be created"
  }
}

State key sharing

hcl
run "create_foundation" {
  command   = apply
  state_key = "foundation"

  assert {
    condition     = aws_vpc.main.id != ""
    error_message = "Foundation VPC should be created"
  }
}

run "create_application" {
  command   = apply
  state_key = "foundation"

  variables {
    vpc_id = run.create_foundation.vpc_id
  }

  assert {
    condition     = aws_instance.app.vpc_id == run.create_foundation.vpc_id
    error_message = "Application should use foundation VPC"
  }
}

Cleanup ordering (S3 objects before bucket)

hcl
run "create_bucket" {
  command = apply

  assert {
    condition     = aws_s3_bucket.example.id != ""
    error_message = "Bucket should be created"
  }
}

run "add_objects" {
  command = apply

  assert {
    condition     = length(aws_s3_object.files) > 0
    error_message = "Objects should be added"
  }
}

# Cleanup destroys in reverse: objects first, then bucket

Multiple aliased providers

hcl
provider "aws" {
  alias  = "primary"
  region = "us-west-2"
}

provider "aws" {
  alias  = "secondary"
  region = "us-east-1"
}

run "test_with_specific_provider" {
  command = plan

  providers = {
    aws = provider.aws.secondary
  }

  assert {
    condition     = aws_instance.example.availability_zone == "us-east-1a"
    error_message = "Instance should be in us-east-1 region"
  }
}

Complex conditions

hcl
assert {
  condition = alltrue([
    for subnet in aws_subnet.private :
    can(regex("^10\\.0\\.", subnet.cidr_block))
  ])
  error_message = "All private subnets should use 10.0.0.0/8 CIDR range"
}

Cleanup

Resources are destroyed in reverse run block order after test completion. This matters for dependencies (e.g., S3 objects before bucket). Use terraform test -no-cleanup to skip cleanup for debugging.

Running Tests

bash
terraform test                                        # all tests
terraform test tests/defaults.tftest.hcl             # specific file
terraform test -filter=test_vpc_configuration        # by run block name
terraform test -test-directory=integration-tests     # custom directory
terraform test -verbose                              # detailed output
terraform test -no-cleanup                           # skip resource cleanup

Best Practices

  1. Naming: *_unit_test.tftest.hcl for plan mode, *_integration_test.tftest.hcl for apply mode
  2. Test naming: Use descriptive run block names that explain the scenario being tested
  3. Default to plan: Use command = plan unless you need to test real resource behavior
  4. Use mocks for external dependencies — faster and no credentials needed (see references/MOCK_PROVIDERS.md)
  5. Error messages: Make them specific enough to diagnose failures without running the test again
  6. Negative tests: Use expect_failures to verify validation rules reject bad inputs
  7. Variable coverage: Test different variable combinations to validate all code paths — test variables have the highest precedence and override all other sources
  8. Module sources: Test files only support local paths and registry modules — not git or HTTP URLs
  9. Parallel execution: Use parallel = true for independent tests with different state files
  10. Cleanup: Integration tests destroy resources in reverse run block order automatically; use -no-cleanup for debugging
  11. CI/CD: Run unit tests on every PR, integration tests on merge (see references/CI_CD.md)

Troubleshooting

IssueSolution
Assertion failuresUse -verbose to see actual vs expected values
Missing credentialsUse mock providers for unit tests
Unsupported module sourceConvert git/HTTP sources to local modules
Tests interferingUse state_key or separate modules for isolation
Slow testsUse command = plan and mocks; run integration tests separately

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 Terraform Test AI skill do?

Comprehensive guide for writing and running Terraform tests. Use when creating test files (.tftest.hcl), writing test scenarios with run blocks, validating infrastructure behavior with assertions, mocking providers and data sources, testing module outputs and resource configurations, or troubleshooting Terraform test syntax and execution.

Why use Terraform Test on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hashicorp/agent-skills/tree/main/plugins/terraform/skills/terraform-test. 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 Terraform Test?

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 Terraform Test?

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

Is the Terraform Test AI skill free?

Yes. It is published on GitHub by hashicorp under the MPL-2.0 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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