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Tdd

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poshan0126
tdd

Test-Driven Development loop. Write a failing test first, then the minimum code to pass it, then refactor. Repeat.

Overview

Publisherposhan0126
Repositorydotclaude
Skill nametdd
Stars
870
Forks
204
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

    Published by poshan0126 on GitHub. Read the source before you install it.

Installation

Install the Tdd 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/poshan0126/dotclaude/tree/main/skills/tdd
  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/poshan0126/dotclaude.git /tmp/dotclaude
mkdir -p .claude/skills
cp -r /tmp/dotclaude/skills/tdd .claude/skills/tdd
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tdd 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 Tdd 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 Tdd 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.

Build the following using strict Test-Driven Development:

Feature: $ARGUMENTS

The TDD Cycle

Repeat this cycle for each behavior. Never skip steps.

Red: Write a Failing Test

  1. Write ONE test for the smallest next behavior (not the whole feature)
  2. The test must:
    • Describe the behavior in its name: should return 0 for empty cart
    • Use Arrange-Act-Assert structure
    • Assert specific values, not vague truths
  3. Run the test. It MUST fail. If it passes, either:
    • The behavior already exists (skip to the next behavior)
    • The test is wrong (it's not testing what you think. Fix it)
  4. Verify the failure message makes sense. It should tell you what's missing

Green: Write the Minimum Code to Pass

  1. Write the simplest, most obvious code that makes the failing test pass
  2. Don't generalize. Don't make it elegant. Don't handle cases the test doesn't cover.
  3. Hardcoding is fine if only one test exists for that path. The next test will force generalization
  4. Run the test. It MUST pass. If it doesn't, fix the code (not the test. The test defined the behavior)
  5. Run ALL tests. Nothing previously passing should break.

Refactor: Clean Up Without Changing Behavior

  1. Look for: duplication, unclear names, functions doing too much, magic values
  2. Make ONE improvement at a time
  3. Run ALL tests after each change. If anything breaks, undo immediately.
  4. Stop refactoring when the code is clean enough. Don't gold-plate

Choosing What to Test Next

Work from simple to complex:

  1. Degenerate cases. Null input, empty collection, zero
  2. Happy path. The simplest valid input
  3. Variations. Different valid inputs that exercise different branches
  4. Edge cases. Boundary values, max sizes, special characters
  5. Error cases. Invalid input, failures, exceptions
  6. Integration. How this connects to the rest of the system

Each test should require a small code change. If you need to write more than ~10 lines of production code to pass a test, the test is too big. Split it.

Rules

  • Never write production code without a failing test that demands it.
  • Never write more than one failing test at a time. One red → green → refactor cycle at a time.
  • The test drives the design. If the code is hard to test, the design is wrong. Change the design, not the test approach.
  • Don't mock what you own. If you need to mock your own code to test it, the code needs restructuring.
  • Commit after each green+refactor cycle. Small, passing, meaningful commits.

Output

After each cycle, briefly state:

  • Test: what behavior was added
  • Code: what changed to make it pass
  • Refactor: what was cleaned up (or "none needed")

When the feature is complete, provide a summary of all behaviors covered and any gaps that would need integration or manual testing.

Frequently asked questions

What does the Tdd AI skill do?

Test-Driven Development loop. Write a failing test first, then the minimum code to pass it, then refactor. Repeat.

Why use Tdd on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/poshan0126/dotclaude/tree/main/skills/tdd. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Tdd?

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 Tdd?

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

Is the Tdd AI skill free?

Yes. It is published on GitHub by poshan0126 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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