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Principle Test Behavior Not Implementation

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cursor
principle-test-behavior-not-implementation

Apply when you write, change, or keep a test. Call the code the way its users do and assert the result they observe against a literal expected value. If the test would still pass when every imported function returns undefined, rewrite the assertion or delete the test.

Overview

Publishercursor
Repositoryplugins
Skill nameprinciple-test-behavior-not-implementation
Stars
9.2K
Forks
863
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Principle Test Behavior Not Implementation 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/cursor/plugins/tree/main/pstack/skills/principle-test-behavior-not-implementation
  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/cursor/plugins.git /tmp/plugins
mkdir -p .claude/skills
cp -r /tmp/plugins/pstack/skills/principle-test-behavior-not-implementation .claude/skills/principle-test-behavior-not-implementation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Principle Test Behavior Not Implementation 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 Principle Test Behavior Not Implementation 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 Principle Test Behavior Not Implementation 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.

Test Behavior, Not Implementation

A test calls the code the way its users do and asserts the result they observe against a literal expected value. A test that asserts which calls the code made, or restates a constant the code contains, does neither.

The check: before you keep a test, ask whether it would still pass if every function it imports returned undefined. If yes, it observes no behavior and cannot fail for a defect. Rewrite the assertion or delete the test.

Why: A test that cannot fail for a defect costs CI time and review attention and catches nothing. A constant pin also fails when someone edits the constant or the prompt it restates, so it prevents that edit.

Five shapes that still pass when every imported function returns undefined:

  • Weak or no assertion. No expect, or only toBeDefined, toBeTruthy, not.toThrow, toBeInstanceOf, toBeGreaterThan(0).
  • Mock or absence only. Only toHaveBeenCalled, not.toHaveBeenCalled, toBeUndefined, toEqual([]), toHaveLength(0), not.toBe(wrongValue).
  • Self-referential. The expected value comes from the code under test: expect(f(a)).toBe(f(a)), expect(parsed.url).toBe(buildUrl(...)).
  • Constant pin. The assertion restates a hand-maintained constant, config default, table row, or prompt string: expect(LIMITS.maxTools).toBe(8), expect(PROMPT).toContain("You are").
  • Fixture asserts fixture. The assertion reads data the test built or a value computed in beforeEach, and the subject never runs inside the body.

The fix: call the subject inside the test body with one concrete input and assert the literal output or the observable effect, expect(slugify("Hello, World!")).toBe("hello-world"). For an absence, assert the presence on the other input in the same test. For a constant, test the mechanism that reads it with one input instead of restating the value. For a mock, assert the payload it received or the state after the call, not that it was called. When no such assertion exists, delete the test.

Keep a test of a relation across a table's rows (a key present in two tables, a parent that exists), and a compile-time check in a *.test-d.ts file.

Frequently asked questions

What does the Principle Test Behavior Not Implementation AI skill do?

Apply when you write, change, or keep a test. Call the code the way its users do and assert the result they observe against a literal expected value. If the test would still pass when every imported function returns undefined, rewrite the assertion or delete the test.

Why use Principle Test Behavior Not Implementation on TypingMind?

Because you install it once and use it with any model. Principle Test Behavior Not Implementation 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 Principle Test Behavior Not Implementation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cursor/plugins/tree/main/pstack/skills/principle-test-behavior-not-implementation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Principle Test Behavior Not Implementation?

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 Principle Test Behavior Not Implementation?

As many as you like. As long as a model supports skills, you can use Principle Test Behavior Not Implementation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Principle Test Behavior Not Implementation AI skill free?

It is published on GitHub by cursor. Check the repository for licensing terms. 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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