Run Acceptance Tests

Organization

hashicorp

run-acceptance-tests

Guide for running acceptance tests for a Terraform provider. Use this when asked to run an acceptance test or to run a test with the prefix `TestAcc`, when a test fails with missing environment variables, or when diagnosing a failing or suspiciously passing acceptance test.

Overview

Publisher	hashicorp
Repository	`agent-skills`
Skill name	`run-acceptance-tests`
Stars	880
Forks	130
Bundled files	Instructions only
License	MPL-2.0
Links	Skill source Repository

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by hashicorp on GitHub. Read the source before you install it.

Installation

Install the Run Acceptance Tests AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/hashicorp/agent-skills/tree/main/plugins/terraform/skills/run-acceptance-tests
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/hashicorp/agent-skills/tree/main/plugins/terraform/skills/run-acceptance-tests

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/run-acceptance-tests .claude/skills/run-acceptance-tests

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Run Acceptance Tests 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 Run Acceptance Tests 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 Run Acceptance Tests 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.

An acceptance test is a Go test function with the prefix TestAcc.

Before running: acceptance tests create real infrastructure against the provider's live API, which may incur cost. Confirm the configured credentials point at a test account before proceeding.

To run a focused acceptance test named TestAccFeatureHappyPath:

Run go test -run=TestAccFeatureHappyPath -timeout 60m with the following environment variables:
- TF_ACC=1
Default to non-verbose test output. Always pass an explicit -timeout: go test kills any test run after 10 minutes by default, and acceptance tests routinely exceed that.
The acceptance tests may require additional environment variables for specific providers. To discover which ones:
- Read the test's PreCheck / testAccPreCheck function and search the test files: grep -rn "os.Getenv" --include="*_test.go".
- Check the repository's README, CONTRIBUTING, or .env.example for documented test setup.
- The provider's Configure method shows how credentials are resolved; use the provider-configuration skill (if available) to understand a credential provider chain.
Set the variables for the single test invocation (EXAMPLE_API_KEY=... TF_ACC=1 go test ...) rather than exporting them into the shell profile, and never write secret values into files inside the repository.

To diagnose a failing acceptance test, use these options, in order. These options are cumulative: each option includes all the options above it.

Run the test again. Use the -count=1 option to ensure that go test does not use a cached result.
Offer verbose go test output. Use the -v option.
Offer debug-level logging. Enable debug-level logging with the environment variable TF_LOG=debug.
Offer to persist the acceptance test's Terraform workspace. Enable persistence with the environment variable TF_ACC_WORKING_DIR_PERSIST=1.

A passing acceptance test may be a false negative. To "flip" a passing acceptance test named TestAccFeatureHappyPath:

Edit the value of one of the TestCheckFuncs in one of the TestSteps in the TestCase.
Run the acceptance test. Expect the test to fail.
If the test fails, then undo the edit and report a successful flip. Else, keep the edit and report an unsuccessful flip.

If a test run is interrupted, real resources may be left behind; run the provider's sweepers if it registers them (see the provider-test-patterns skill's sweeper reference, if available). For writing or restructuring tests, use the provider-test-patterns skill.

Frequently asked questions

What does the Run Acceptance Tests AI skill do?

Why use Run Acceptance Tests on TypingMind?

Because you install it once and use it with any model. Run Acceptance Tests 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 Run Acceptance Tests in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hashicorp/agent-skills/tree/main/plugins/terraform/skills/run-acceptance-tests. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Run Acceptance Tests?

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 Run Acceptance Tests?

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

Is the Run Acceptance Tests 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Frequently asked questions

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