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Write Unit Tests

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tldraw
write-unit-tests

Writing unit and integration tests for the tldraw SDK. Use when creating new tests, adding test coverage, or fixing failing tests in packages/editor or packages/tldraw. Covers Vitest patterns, TestEditor usage, and test file organization.

Overview

Publishertldraw
Repositorytldraw
Skill namewrite-unit-tests
Stars
50.4K
Forks
3.5K
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 tldraw on GitHub. Read the source before you install it.

Installation

Install the Write Unit 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/tldraw/tldraw.git /tmp/tldraw
mkdir -p .claude/skills
cp -r /tmp/tldraw/skills/write-unit-tests .claude/skills/write-unit-tests
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Write Unit 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 Write Unit 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 Write Unit 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.

Writing tests

Unit and integration tests use Vitest and run from workspace directories, not the repo root.

Read a neighboring test before writing a new one — the existing suites are the specification for how we test, and they stay current in a way prose can't. Good starting points:

  • packages/tldraw/src/test/SelectTool.test.ts — tool state machine assertions
  • packages/tldraw/src/test/resizing.test.ts — pointer-driven interaction with handles
  • packages/tldraw/src/lib/shapes/arrow/ArrowShapeUtil.test.ts — shape util plus bindings
  • packages/editor/src/lib/editor/managers/ClickManager/ClickManager.test.ts — a UI-free manager
  • packages/editor/src/lib/primitives/Vec.test.ts — a plain primitive

For the available TestEditor methods, read the class itself rather than a list here: packages/tldraw/src/test/TestEditor.ts.

Which workspace

  • packages/editor — core primitives, geometry, managers, base editor behavior that must not depend on default shapes or UI.
  • packages/tldraw — anything needing default shapes or tools, which is most integration tests.

Each package has its own TestEditor, and they are not interchangeable: packages/editor/src/lib/test/TestEditor.ts has no default shapes or tools, packages/tldraw/src/test/TestEditor.ts wires up the full SDK. Import from the package you're testing in.

bash
cd packages/tldraw && yarn test run
cd packages/tldraw && yarn test run --grep "SelectTool"
cd packages/tldraw && yarn test          # watch mode

Placement

Unit tests sit next to the file they cover (Vec.tsVec.test.ts). Cross-cutting integration tests live in packages/tldraw/src/test/. Shape and tool tests sit with the implementation, not in src/test/.

Gotchas

These are the things reading an existing test won't tell you.

Wheel and pinch events are batched. dispatch() alone won't apply them — emit a tick to flush:

typescript
editor.dispatch(wheelEvent)
editor.emit('tick', 16)

See packages/editor/src/lib/editor/Editor.test.ts for the full pattern.

toCloselyMatchObject is ours, not Vitest's. Use it instead of toMatchObject whenever floating-point geometry is involved, or tests fail on rounding noise. It takes an optional roundToNearest. Defined in packages/tldraw/src/test/TestEditor.ts.

Animation-dependent code needs the rAF stub. vi.useFakeTimers() alone isn't enough, because requestAnimationFrame isn't driven by the fake clock. Tests that animate replace it at module scope — see the top of packages/tldraw/src/lib/shapes/arrow/ArrowShapeUtil.test.ts.

Dispose the editor in afterEach. editor?.dispose() releases the reactive subscriptions and timers the editor holds; without it they leak across tests in the same file. Suites that build up shapes also tend to clear them in beforeEach so each test starts from a known page.

Always mockRestore() a vi.spyOn on the editor. Editor instances outlive individual assertions within a suite, so an unrestored spy silently changes later tests.

Conventions

  • Use createShapeId() for shape IDs so they're stable and typed.
  • Prefer comparing whole objects over field-by-field assertions when it gives a clearer failure.
  • Use editor.expectToBeIn('select.idle') for state machine assertions rather than reaching into internals.
  • @ts-expect-error is the way to assert that invalid props are rejected at the type level.

Frequently asked questions

What does the Write Unit Tests AI skill do?

Writing unit and integration tests for the tldraw SDK. Use when creating new tests, adding test coverage, or fixing failing tests in packages/editor or packages/tldraw. Covers Vitest patterns, TestEditor usage, and test file organization.

Why use Write Unit Tests on TypingMind?

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

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

Which AI models can use Write Unit 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 Write Unit Tests?

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

Is the Write Unit Tests AI skill free?

It is published on GitHub by tldraw. 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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