Common Tdd

Community

HoangNguyen0403

common-tdd

Guides quality-first TDD for new behavior, bug fixes, and test changes. Selects the smallest test layer, proves a distinct regression risk, and runs bounded RED-GREEN-REFACTOR verification.

Overview

Publisher	HoangNguyen0403
Repository	`agent-skills-standard`
Skill name	`common-tdd`
Stars	573
Forks	166
Bundled files	8
License	MIT
Links	Skill source Repository Homepage

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.
8 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by HoangNguyen0403 on GitHub. Read the source before you install it.

Installation

Install the Common Tdd 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/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/common/common-tdd
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/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/common/common-tdd

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/HoangNguyen0403/agent-skills-standard.git /tmp/agent-skills-standard
mkdir -p .claude/skills
cp -r /tmp/agent-skills-standard/.agents/skills/common/common-tdd .claude/skills/common-tdd

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

Use it in TypingMind

Enable Common 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 Common 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 Common 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.

Quality-First TDD

Priority: P0 (CRITICAL)

A passing test is insufficient; the test must prove an owned behavior and a distinct plausible fault.

Choose the mode

New behavior: strict RED -> GREEN -> REFACTOR. Do not write production code before the expected RED.
Legacy or bug fix: characterize only when needed, then reproduce the intended change as a failing regression (RED). Preserve unrelated existing code; do not delete it merely because it predates the test.

Before writing a test

Compare against the existing suite before adding or removing cases. Ensure the scenario is not already covered upstream or in nearby layers.

Create one Test Intent Record per behavior/risk:

contract: observable contract — an application-owned result or outward side effect
fault: distinct plausible fault this test catches
layer: smallest honest unit, component, contract, integration, or E2E layer
cases: minimal distinct equivalence classes; use a parameterized test for equivalent inputs
command: exact focused single-run command

Reject tests that duplicate existing suite coverage, assert internal mock choreography over outward side effects, depend on time/network/order, or invent numeric four-pillar scores without measured evidence.

Bounded loop

Run configured lint/type checks, inspect nearby tests, and derive the smallest command.
RED: add one intent group and run it in the foreground, sequentially, single-run mode.
Classify RED as expected_red, invalid_red, unexpected_green, or verification_infra_failed. If it is unexpected_green, inspect existing coverage and remove a redundant or weak case before implementing production code.
GREEN: implement only enough to satisfy expected_red; rerun the same command.
REFACTOR: improve structure without changing behavior; rerun the same command.
Escalate only when evidence requires it: related unit target, integration/contract target, then explicit release/full-suite gate.

Execution safety

Honor project timeouts; otherwise use a 120-second fallback to bound a focused command.
On timeout, terminate only the agent-owned process group and verify child cleanup.
Never watch, blanket-kill, or retry an unchanged failure. Record the new hypothesis or corrective change first.
Coverage percentages are diagnostic tools, never an admission criterion. Without a configured threshold, report risk gaps and never add padding tests for an arbitrary percentage.

Red flags and rationalizations

Stop on: add tests after, too small, passed first run, run the full suite again, or mock every collaborator.
Urgency, manual testing, test count, or a coverage target never bypasses the intent record, expected RED, bounded command, or fault proof.

Test shape

Verify one logical contract per test; multiple assertions are allowed when verifying related aspects or side effects of that single contract.
Assert observable outcomes and outward side effects, not mock choreography or call sequences.
Mock external boundaries only when isolation requires it; prefer real pure/domain behavior and simple fakes.
Keep test names behavior-focused, without ticket IDs or TODO/FIXME markers.

See references/quality-contract.md for the intent record, failure taxonomy, layer routing, and runner examples.

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 Common Tdd AI skill do?

Guides quality-first TDD for new behavior, bug fixes, and test changes. Selects the smallest test layer, proves a distinct regression risk, and runs bounded RED-GREEN-REFACTOR verification.

Why use Common Tdd on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HoangNguyen0403/agent-skills-standard/tree/develop/.agents/skills/common/common-tdd. 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 Common 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 Common Tdd?

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

Is the Common Tdd AI skill free?

Yes. It is published on GitHub by HoangNguyen0403 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.

View all

Proof Video

openclaw

OrganizationPopular

Add subtitles, captions, narration cues, or zoom to a proof video or PR recording using repo-local capture helpers and a system ffmpeg renderer.

Slack E2e

Test Slack with Convex-leased user OAuth or QA bots; check credentials, exercise owned messages, prove Gateway behavior, and distinguish API evidence from real Slack client interactions.

Telegram E2e Userbot

Prove user-visible OpenClaw Telegram behavior on Telegram's Test Server with Convex-leased team credentials; drive real-user turns and record messages, edits, deletions, reactions, typing, or rich…

Module Regression

Govern cross-module regression in large repositories with a REGRESSION.md ledger that records each module's downstream consumers and executable acceptance command. After a change, run the changed…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Quality-First TDD

Priority: P0 (CRITICAL)

Choose the mode

Before writing a test

Bounded loop

Execution safety

Red flags and rationalizations

Test shape

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now