HashiCorp Agent Skills is a collection of reusable instructions and plugins that help coding agents work with Terraform and Packer. Developers use it to add HashiCorp product workflows to supported coding-agent tools, either individually or as product bundles.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add hashicorp/agent-skills --skill terraform-testgit clone --depth 1 https://github.com/hashicorp/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/hashicorp/agent-skills/terraform-test)<a href="https://agentmods.dev/skills/hashicorp/agent-skills/terraform-test"><img src="https://agentmods.dev/badge/skills/hashicorp/agent-skills/terraform-test/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/hashicorp/agent-skills/terraform-test"><img src="https://agentmods.dev/badge/skills/hashicorp/agent-skills/terraform-test.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00059 | $0.02712 |
| Opus 5 | $0.00030 | $0.01356 |
| Sonnet 5 | $0.00012 | $0.00542 |
| Haiku 4.5 | $0.00006 | $0.00271 |
Grade A, and why
terraform-test scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- terraform-test — 91% identical, 2 lines differ
- terraform-test — 91% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 452 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 examplesreferences/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): Containsrunblocks 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) orplan(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
# 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"
}
}
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 452 lines · 59 tokens per session scan A bba613c50727
terraform-test is a skill published in the GitHub repository hashicorp/agent-skills (865 stars, last pushed 4d ago), licensed MPL-2.0. It adds 59 tokens to every session and 2,712 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
tika-eval-compare
Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".
neuron-evaluation-engineer
Create and run AI evaluations with datasets, assertions, and output drivers in Neuron AI. Use this skill whenever the user mentions evaluation, testing AI systems, creating evaluators, dataset-driven testing, assertion-based validation, or wants to measure AI system performance. Also trigger for tasks involving…
jetson-validate-image
Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.
atmos-validation
Validate Atmos projects, components, arbitrary JSON Schema inputs, EditorConfig, and GitHub Actions; use affected-file selection and native CI annotations.
skill-benchmark
Benchmark AI skill effectiveness by measuring implementation quality against legacy constraints.