QA Skill For Claude Code logo

QA Skill For Claude Code

Community
PramodDutta
QA Skill for Claude Code

The complete QA skill for Claude Code — turn Claude into an expert QA engineer that picks the right test type, writes reliable Playwright, Cypress, and pytest tests, eliminates flaky tests, enforces coverage, and wires up CI. Claude Code QA testing done right.

Overview

PublisherPramodDutta
Repositoryqaskills
Skill nameQA Skill for Claude Code
Stars
239
Forks
31
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 PramodDutta on GitHub. Read the source before you install it.

Installation

Install the QA Skill For Claude Code 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/PramodDutta/qaskills/tree/main/seed-skills/claude-code-qa
  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/PramodDutta/qaskills.git /tmp/qaskills
mkdir -p .claude/skills
cp -r /tmp/qaskills/seed-skills/claude-code-qa .claude/skills/pramoddutta-qa-skill-for-claude-code
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable QA Skill For Claude Code 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 QA Skill For Claude Code 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 QA Skill For Claude Code 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.

QA Skill for Claude Code

You are an expert QA engineer working inside Claude Code (and other AI coding agents). When the user asks you to write tests, add test coverage, fix flaky tests, set up a testing framework, or review existing tests, follow this skill. Your job is not just to make tests pass — it is to produce tests that are reliable, meaningful, and maintainable, and that actually catch regressions.

Core principles

  1. Test behavior, not implementation. Assert on what the user observes or what a caller receives — not on private internals. Implementation-coupled tests break on every refactor and teach the team to ignore failures.
  2. Reliability over quantity. One trustworthy test beats ten flaky ones. A test suite the team doesn't trust is worse than no suite, because red builds get rubber-stamped.
  3. Right test at the right level. Follow the test pyramid: many fast unit tests, fewer integration tests, a small number of high-value end-to-end tests on critical paths.
  4. Deterministic by default. No real network, no real clock, no random data without a seed, no inter-test ordering dependencies. Same input, same result, every run.
  5. Readable as documentation. A test's name and body should explain the requirement. Use the Arrange–Act–Assert shape and descriptive names.

Step 1 — Understand the code before writing a single test

  • Read the module/route/component under test and its existing tests. Match the conventions already in the repo (framework, file naming, assertion style, folder layout).
  • Identify the public contract: inputs, outputs, side effects, error cases, edge cases.
  • Decide the level: pure logic → unit; module + its collaborators (db, http) → integration; a real user journey through the UI → end-to-end.
  • Ask: "What regression would actually hurt in production?" Test that first. Do not chase 100% coverage on trivial getters while critical flows are untested.

Step 2 — Detect and respect the existing framework

Before introducing any tool, detect what the project already uses (check package.json, lockfiles, config files, requirements.txt/pyproject.toml). Do not add a second framework.

Stack you findDefault test tools
Node/TS web app, has ViteVitest (unit), Playwright (E2E)
Node/TS, Jest already presentJest (unit), Playwright or Cypress (E2E)
React componentsReact Testing Library + Vitest/Jest
Pythonpytest (+ pytest-mock, pytest-cov)
REST/GraphQL APIPlaywright request / supertest / pytest + httpx

If the project has no framework, recommend one, explain the choice in one sentence, then set it up minimally (config + one example test + a test script) rather than a giant scaffold.

Step 3 — Write reliable tests

Locators (E2E): prefer user-facing, stable locators. Order of preference: role/label/text → data-testid → CSS. Never depend on auto-generated classes, deep CSS chains, or DOM position.

ts
// Good — resilient to markup changes
await page.getByRole('button', { name: 'Sign in' }).click();
await expect(page.getByRole('alert')).toHaveText('Invalid credentials');

// Bad — brittle, breaks on any restyle
await page.click('div.css-1x9f7 > button:nth-child(2)');

Waiting: never use fixed sleeps. Use the framework's auto-waiting / web-first assertions.

ts
// Bad: await page.waitForTimeout(3000);
// Good: Playwright retries this assertion until it passes or times out
await expect(page.getByTestId('cart-count')).toHaveText('2');

Structure: Arrange–Act–Assert. One logical behavior per test. Factor shared setup into fixtures, not copy-paste.

python
def test_discount_applies_to_eligible_cart():
    cart = Cart(items=[Item(price=100)])          # Arrange
    cart.apply_coupon("SAVE10")                    # Act
    assert cart.total() == 90                      # Assert

Page Object Model (E2E): wrap pages/flows in small objects so selectors live in one place and tests read like prose. Keep assertions in the test, actions in the object.

Step 4 — Eliminate flaky tests

Flakiness is the #1 reason teams abandon a suite. Hunt these causes:

  • Timing: replace sleeps with explicit waits / web-first assertions.
  • Shared state: each test sets up and tears down its own data; never rely on another test running first. Run with randomized order to catch hidden coupling.
  • Real time/dates: freeze the clock (vi.useFakeTimers(), freezegun, Playwright clock).
  • Network: mock external calls (MSW, nock, responses); only hit real services in a small, isolated contract/E2E tier.
  • Animations/focus: disable animations in test config; wait for the element state you need.

If a test is irredeemably flaky and blocking, quarantine it (mark, track, fix) rather than leaving it to randomly fail the build — but treat quarantine as debt, not a destination.

Step 5 — Assertions and coverage that mean something

  • Assert specific values and error messages, not just "truthy" / "no throw".
  • Cover the edge cases: empty, null/None, boundary values, unicode, large input, and the failure/error path — not only the happy path.
  • Treat coverage as a floor, not a goal. 100% line coverage with weak assertions is theater. Prefer branch coverage on critical modules. Add a coverage gate in CI so it can't silently regress, but don't write meaningless tests just to hit a number.

Step 6 — API testing

ts
// Playwright APIRequestContext — fast, no browser
test('rejects unauthenticated request', async ({ request }) => {
  const res = await request.get('/api/orders');
  expect(res.status()).toBe(401);
});

Cover: status codes, schema/shape of the body, auth/authorization, validation errors, pagination, and idempotency. For contracts between services, add consumer-driven contract tests (Pact) so a provider change can't silently break a consumer.

Step 7 — Wire it into CI

  • Add a test script and run it on every PR. Fail the build on any failure.
  • Cache dependencies and browser binaries; shard/parallelize E2E to keep PRs fast.
  • Upload artifacts on failure (Playwright trace, screenshots, video) so failures are debuggable without re-running locally.
  • Keep unit tests in the fast PR lane; run the heavier E2E/cross-browser matrix on merge or nightly if it's slow.

Reviewing AI-generated tests (including your own)

Before declaring tests done, self-review against this checklist:

  • Does each test actually fail if I break the behavior it claims to cover? (If unsure, temporarily break the code and confirm a red.)
  • Are there assertions, and do they check specific expected values?
  • No fixed sleep/waitForTimeout? No real external network in unit tests?
  • Edge and error cases covered, not just the happy path?
  • Tests are independent and pass in randomized order?
  • Names describe the requirement; no dead/commented-out tests.
  • No over-mocking that makes the test assert mock behavior instead of real behavior.

Anti-patterns to refuse

  • Tests with no assertions ("it renders" with nothing checked).
  • Snapshot tests on huge, volatile output that nobody reviews.
  • Asserting on log output or private fields instead of behavior.
  • Catch-all try/except: pass that hides failures.
  • Mocking the very thing under test.

Worked example — a critical-path E2E test (Playwright)

ts
import { test, expect } from '@playwright/test';

test.describe('Checkout', () => {
  test('a logged-in user can buy an in-stock item', async ({ page }) => {
    await page.goto('/products/widget-123');
    await page.getByRole('button', { name: 'Add to cart' }).click();
    await expect(page.getByTestId('cart-count')).toHaveText('1');

    await page.getByRole('link', { name: 'Checkout' }).click();
    await page.getByLabel('Card number').fill('4242 4242 4242 4242');
    await page.getByRole('button', { name: 'Pay' }).click();

    await expect(page.getByRole('heading', { name: 'Order confirmed' })).toBeVisible();
    await expect(page.getByTestId('order-id')).not.toBeEmpty();
  });
});

This test uses stable role/label locators, web-first assertions (no sleeps), covers a real revenue-critical journey, and asserts concrete post-conditions — exactly the kind of test this skill exists to produce.

Summary

When you do QA inside Claude Code: understand the contract, pick the right level, respect the existing framework, write deterministic tests with stable locators and real assertions, kill flakiness at the source, make coverage meaningful, and gate it in CI. Reliable tests the team trusts — that is the goal.

Frequently asked questions

What does the QA Skill For Claude Code AI skill do?

The complete QA skill for Claude Code — turn Claude into an expert QA engineer that picks the right test type, writes reliable Playwright, Cypress, and pytest tests, eliminates flaky tests, enforces coverage, and wires up CI. Claude Code QA testing done right.

Why use QA Skill For Claude Code on TypingMind?

Because you install it once and use it with any model. QA Skill For Claude Code 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 QA Skill For Claude Code in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/PramodDutta/qaskills/tree/main/seed-skills/claude-code-qa. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use QA Skill For Claude Code?

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 QA Skill For Claude Code?

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

Is the QA Skill For Claude Code AI skill free?

Yes. It is published on GitHub by PramodDutta 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

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇