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Writing Tests

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rileyhilliard
writing-tests

Writes behavior-focused tests using Testing Trophy model with real dependencies. Use when writing tests, choosing test types, or avoiding anti-patterns like testing mocks.

Overview

Publisherrileyhilliard
Repositoryclaude-essentials
Skill namewriting-tests
Stars
127
Forks
19
Bundled files
5
LicenseMIT
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.

  • 5 bundled files

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

  • Open source

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

Installation

Install the Writing Tests 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.
  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/rileyhilliard/claude-essentials.git /tmp/claude-essentials
mkdir -p .claude/skills
cp -r /tmp/claude-essentials/plugins/ce/skills/writing-tests .claude/skills/writing-tests
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Writing 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 Writing 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 Writing 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.

If the current repo has its own rules/skills covering this topic (check .claude/rules/ and repo CLAUDE.md), those take precedence — apply this skill only where they're silent.

Writing Tests

Core principle: Test user-observable behavior with real dependencies. Tests should survive refactoring.

"The more your tests resemble the way your software is used, the more confidence they can give you." — Kent C. Dodds

Why this matters: Tests exist to give you confidence. The Testing Trophy prioritizes integration tests because they test real behavior across real modules — giving maximum confidence per test written. Unit tests in isolation often just test mocks, not your actual system.

Testing Trophy Model

PriorityTypeWhen
1stIntegrationDefault - multiple units with real dependencies
2ndE2EComplete user workflows
3rdUnitPure functions only (no dependencies)

Mocking Guidelines

Default: Don't mock. Use real dependencies.

Only mock:

  • External HTTP/API calls
  • Time/randomness
  • Third-party services (payments, email)

Never mock:

  • Internal modules
  • Database queries (use test DB)
  • Business logic
  • Your own code calling your own code

Before mocking, ask: "What side effects does this have? Does my test need those?" If unsure, run with real implementation first, then add minimal mocking only where needed.

Test Type Decision

Complete user workflow? → E2E test
Pure function (no side effects)? → Unit test
Everything else → Integration test

Assertion Strategy

ContextAssert OnAvoid
UIVisible text, rolesCSS classes, internal state
APIResponse body, statusInternal DB state
LibraryReturn valuesPrivate methods

Anti-Patterns

PatternFix
Testing mock callsTest actual outcome
Test-only methods in productionMove to test utilities
sleep(500)Poll for actual condition
Asserting on internal stateAssert on observable output
Incomplete mocksMirror real API completely

Quality Checklist

  • Happy path covered
  • Error conditions handled
  • Real dependencies used (minimal mocking)
  • Tests survive refactoring
  • Test names describe behavior

Language-Specific Patterns

Async Waiting

Wait for the actual condition, not a guess about how long it takes.

typescript
// Bad: arbitrary delay
await new Promise(r => setTimeout(r, 2000));
expect(element).toBeVisible();

// Good: poll for condition
await waitFor(() => expect(element).toBeVisible());

Prefer framework built-ins:

  • Testing Library: findBy queries, waitFor
  • Playwright: auto-waiting, expect(locator).toBeVisible()
  • pytest: asyncio.wait_for, tenacity

Language-specific waiting patterns:


Remember: Behavior over implementation. Real over mocked. Outputs over internals.

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 Writing Tests AI skill do?

Writes behavior-focused tests using Testing Trophy model with real dependencies. Use when writing tests, choosing test types, or avoiding anti-patterns like testing mocks.

Why use Writing Tests on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rileyhilliard/claude-essentials/tree/main/plugins/ce/skills/writing-tests. 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 Writing 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 Writing Tests?

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

Is the Writing Tests AI skill free?

Yes. It is published on GitHub by rileyhilliard under the MIT 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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